A Comprehensive Review of Heat Transfer Fluids and Their Velocity Effects on Ground Heat Exchanger Efficiency in Geothermal Heat Pump Systems

Abstract

This study reviews heat transfer fluids (HTFs) and their velocity effects on the thermal behavior of ground heat exchangers (GHEs) within geothermal heat pump (GHP) applications. It examines the classification, thermophysical properties, and operational behavior of standard working fluids, including water–glycol mixtures, as well as emerging nanofluids. Fundamental heat exchange mechanisms are discussed, with emphasis on how conductivity, viscosity, and heat capacity interact with fluid velocity to influence energy transfer performance, hydraulic resistance, and system reliability. Special attention is given to nanofluids, whose enhanced thermal behavior depends on nanoparticle type, concentration, dispersion stability, and flow conditions. The review analyzes stabilization strategies, including surfactants, functionalization, and pH control, for maintaining long-term performance. It also highlights the role of velocity optimization in balancing convective benefits with pumping energy demands, providing velocity ranges suited to different GHE configurations. Drawing from recent experimental and numerical studies, the review offers practical guidelines for integrating nanofluid formulation with engineered operating conditions to maximize energy efficiency and extend system lifespan.

1. Introduction

The energy used to power buildings accounts for about 30% of global energy use in many regions, with this percentage rising to 40% in colder climates. In the United States, for example, space heating significantly increases energy demand during the winter months, with 60% of heating-related utility costs devoted to heating buildings. Energy demand is rapidly increasing, especially for heating and cooling in buildings, due to the growing global population and changing climate conditions. These shifts are driving up costs, making utility bills unaffordable for many households. Moreover, conventional heating and cooling technologies mainly depend on electricity generated from fossil fuels, contributing to air pollution. This has become a significant concern as the world faces the combined threats of climate change and rising fossil fuel costs, which are expected to affect all aspects of daily life. To address these issues, the geothermal heat pump system (GHPS) has emerged as a sustainable alternative. This innovative and efficient technology harnesses the Earth’s relatively stable temperature to provide high-efficiency heating, cooling, and domestic hot water, suitable for various applications. Furthermore, the GHPS’s heating and cooling efficiencies outperform those of conventional heating and air conditioning systems, providing 30% to 70% greater efficiency in heating and 20% to 50% greater efficiency in cooling. Additionally, the GHPS significantly reduces electricity consumption, cutting it by up to 75% relative to conventional heating and cooling units. To maximize its environmental benefits, GHPS should ideally be powered by renewable energy sources rather than grid electricity. When integrated with renewables, GHPS can reduce CO₂ emissions by as much as 52% in comparison with standard HVAC systems [1,2,3,4,5]. As a result, GHPS is recognized as a clean, reliable, renewable, and environmentally sustainable energy solution that requires little maintenance and remains unaffected by short-term weather fluctuations—unlike alternative renewable options such as solar or wind power, which are highly dependent on intermittent sunlight and wind availability, leading to variable energy output. In contrast, GHPS utilizes the constant underground temperature as a stable heat source or sink, enabling steady, year-round operation even during cloudy, windless, or extreme weather conditions [6,7,8,9,10,11,12]. Additionally, its capacity to provide both heating and cooling from a single integrated system further enhances its appeal for residential, commercial, and institutional applications. Furthermore, the system’s underground installation minimizes both visual and noise pollution, further enhancing its environmental appeal [1]. Despite these advantages, the widespread adoption of GHPS is hindered by high installation costs. Vertical GHEs typically require deep borehole drilling—ranging from 30 to 120 m—depending on subsurface thermal properties and building energy demands. This process necessitates specialized equipment, skilled labor, and strict regulatory compliance, increasing installation expenses, particularly in areas with hard bedrock or high groundwater levels [5,13,14,15,16]. In contrast, horizontal GHEs, installed at shallower depths (2–6 m), require large land areas and are limited in suitability for densely populated or land-constrained regions [7,17,18,19]. Moreover, the initial investment for a GHPS system is typically 30–50% higher than for conventional HVAC systems [20]. While these systems offer long-term energy savings, the high upfront cost remains a key barrier to broader adoption. However, this initial expense can often be offset within four to seven years through energy savings, depending on factors such as system design, local energy prices, and the size and efficiency of the ground heat exchanger loop [1,5,7,16]. To make GHPS more accessible, researchers are focusing on enhancing efficiency, affordability, and reliability—particularly for residential-scale systems. Despite the upfront investment, GHPS offers substantial long-term savings, making the payback period relatively short under optimal conditions [5,7,16].

To advance the development and broader implementation of GHPS technology, a thorough understanding of its design principles and performance characteristics is essential. A comprehensive exploration of the advantages and disadvantages of GHPS systems, along with additional details, can be found in the following sources [5,13,16]. These references offer an in-depth analysis of key factors such as installation, performance, and efficiency, providing valuable insights for geothermal engineering designers considering the adoption of this technology. A key component of the GHPS is the ground heat exchanger (GHE), which facilitates the transfer of thermal energy between the system and the ground. GHE plays a crucial role in determining the system’s overall performance and significantly influences the coefficient of performance (COP). To effectively utilize the Earth’s stored heat, the GHE must be well-designed, considering a variety of factors such as system configuration, site location, and the capacity of the borehole heat exchanger (BHE). A well-optimized design ensures efficient thermal interaction with the ground, minimizes energy losses, and maintains operational stability over the system’s lifetime. These design considerations include the selection of suitable materials; the conductivity of the surrounding soil; and the use of backfill, appropriate borehole depth and spacing, and the configuration of the heat exchange loops—whether vertical, horizontal, helical, coaxial, or other advanced designs. These elements work together to ensure that the GHE’s output temperature aligns closely with the natural ground temperature, which is vital for maintaining efficient heat transfer. As a result, enhancements in the GHE’s thermal and structural characteristics—such as advanced pipe materials, flow optimization, or novel geometries—can directly improve performance, reduce cost, and increase the sustainability of GHPS systems [5,7,13,16]. Several factors influence the heat transfer performance of vertical ground heat exchangers (GHEs), such as soil conductivity, backfill characteristics, borehole depth and spacing, U-tube design, and the flow velocity and type of the heat transfer fluid [5,7,13].

The literature reviewed in this study was identified through a structured and targeted search process to ensure comprehensive coverage of both foundational and recent work. Searches were conducted across major scientific databases, including Scopus, Web of Science, ScienceDirect, and Google Scholar for the period January 2000 to March 2025, using keywords such as “heat exchange fluids”, “nanofluids”, “ground heat exchanger”, “geothermal heat pump”, “fluid velocity”, “thermal properties”, and related combinations. Additional sources were located by screening the reference lists of key articles. Only peer-reviewed studies presenting experimental, numerical, or theoretical data relevant to thermophysical properties, stability, or velocity-dependent performance in GHE applications were included. Studies lacking clear methodology, without quantitative results, or unrelated to GHE systems were excluded. This approach ensures that the review draws upon high-quality, relevant literature to support the analysis and conclusions presented herein.

This paper provides a comprehensive review of heat transfer fluids (HTFs) and their flow velocity, with a focus on their effects on ground heat exchanger (GHE) performance. We also examine strategies to enhance fluid properties and optimize flow rates to improve overall system efficiency. Finally, we propose optimal velocity ranges for specific GHE configurations based on a synthesis of recent experimental and simulation-based findings. The structure of the paper is as follows: Section 2 discusses Heat Transfer Fluids for Ground Heat Exchangers: Classification, Performance, and Advanced Developments. Section 3 examines Nanofluids for Enhanced Heat Transfer: Properties and Performance, with Section 3.1 on Thermal Conductivity of Nanofluids and Section 3.2 on Thermophysical Performance Factors of Nanofluids. Section 4 evaluates Fluid Velocity and its Impact on Ground Heat Exchanger Performance, and Section 5 provides conclusions and key findings.

2. Heat Transfer Fluids for Ground Heat Exchangers: Classification, Performance, and Advanced Developments

A heat transfer fluid (HTF) is a substance employed to carry thermal energy within heating or cooling systems. It is widely applied across various engineering sectors, including geothermal heat pump systems, air conditioning, electronics, power generation, chemical production, nuclear cooling, transportation, and microelectronics. This study focuses on geothermal heat pump systems and explains the role of HTFs in ground heat exchangers. In these systems, HTFs facilitate the movement of heat energy between the ground (through the ground heat exchanger) and the heat pump unit. The fluid circulates through closed-loop systems, absorbing heat from the ground during the heating season and releasing heat back into the ground during the cooling season. The efficiency of this energy transfer is highly dependent on the properties of HTF, making its selection critical for optimizing system performance. These heat transfer fluids can be classified into traditional and advanced types. Traditional HTFs include common liquid-based fluids like water, glycol mixtures, brines, and oils, as well as gas-based fluids such as air. These fluids are commonly applied in both heating and cooling uses because of their proven stability and ease of use. Advanced HTFs include nanofluids, hybrid fluids, and hybrid nanofluids. Hybrid nanofluids are a specialized type that incorporates multiple types of nanoparticles in a carrier liquid, such as water-based or oil-based hybrid nanofluids, providing superior heat transfer performance. Figure 1 provides a visual overview of the categories of heat transfer fluids. Traditional heat transfer fluids are commonly applied in geothermal systems due to their established effectiveness and reliability. Water-based fluids offer efficient heat transfer and are environmentally friendly, but they are prone to freezing in colder climates. Water–ethylene glycol mixtures provide freeze protection, making them suitable for colder regions, though they have higher viscosity and lower thermal efficiency. Brine-based fluids perform well at low temperatures and offer good heat transfer, but they present a risk of corrosion and require increased energy for pumping. Oil-based fluids are thermally stable at high temperatures, but they have lower thermal conductivity and are more expensive [21,22,23,24,25].

Heat transfer fluids with low thermal conductivity, low heat capacity, and high viscosity increase the convective resistance to heat flow between the fluid in the U-tube and the pipe wall, ultimately reducing the efficiency of the ground heat exchanger [5,13,16,26]. Initially, pure water was the predominant heat transfer fluid in geothermal heat pump and air conditioning systems, valued for its high thermal capacity, excellent heat absorption and storage properties, and low cost, all of which helped lower operating expenses [7,27,28,29]. Dada and Benchatti [30] evaluated the thermal behavior of three fluids—water, gasoline, and glycol—and found that water was more effective at absorbing, storing, and recovering thermal energy than gasoline and glycol, while gasoline reached higher temperatures than the other fluids in colder conditions. In mild climates, water results in a lower outlet temperature in the ground heat exchanger (GHE) than a 25% ethylene glycol–water mixture, as reported by Emmi et al. [27]. However, despite its benefits, water lacks anti-freeze properties. To prevent freezing of the working fluid, antifreeze solutions are now commonly used in GSHP systems, with the optimal admixture percentage selected to avoid excessive viscosity [31]. Increasing the heat capacity of the working fluid can also reduce the required flow rate in borehole heat exchangers (BHEs) [32]. Thus, in cold climates, it is often mixed with antifreeze to prevent freezing and protect the system from damage, thereby enhancing GHE thermal performance, reducing energy consumption, and lowering system operating expenses [33,34]. For instance, the 400-ton geothermal heat pump system (GHPS) at Oakland University uses a solution of pure water and antifreeze in its ground loop pipes to withstand cold winter temperatures and has been operating smoothly to provide heating and cooling since its installation in August 2012 [7,16].

Pure water (PW), sodium chloride solution (SCS), and calcium chloride solution (CCS) offer the benefits of safety, non-toxicity, and excellent thermal conductivity, but they can be corrosive to metals in the presence of air [35]. Ethylene glycol solution (EGS) provides low corrosion potential and favorable thermal conductivity; however, its viscosity increases significantly under low-temperature conditions, thereby leading to greater flow resistance. Among the common antifreeze options, CCS and EGS are generally considered optimal choices for working fluids in terms of thermal performance. Calcium chloride (CaCl₂) can deliver substantial energy performance gains compared to 25% propylene glycol (PG25%), achieving a minimum temperature increase of +2.94 °C and reducing heat pump power consumption by approximately 4.01% due to its better heat conductivity and reduced viscosity [36]. Saline solutions like CCS and SCS also have lower viscosity than glycols and ethanol, which helps to minimize energy losses, although special measures are required to prevent corrosion. For ethanol-based mixtures, a 33% ethanol concentration in the working fluid has been found to be unnecessarily high, since it can cause condensation at the GHE outlet and reduce system efficiency [37]. Moreover, the high ethanol content lowers thermal conductivity while increasing kinematic viscosity, therefore promoting laminar flow and higher thermal resistance—both of which hinder effective heat transfer.

Air is a potential working fluid for geothermal heat exchangers, particularly in air–ground heat exchanger (AGHE) applications. The effectiveness of a horizontal AGHE generally decreases as the inlet air speed rises (0.5–20 m s⁻¹), although the heat transfer rate itself tends to rise with velocity. Raising the inlet air temperature from 38 °C to 46 °C can further enhance both the heat exchange rate and the overall performance of the AGHE. The relative humidity of the air also plays an important role, influencing thermal performance significantly. To maximize efficiency, the buried tube depth should be as deep as possible, while accurate consideration of the soil’s thermal saturation is necessary, as neglecting this may lead to overestimations. Moreover, variations in atmospheric and ground surface temperature can strongly affect system performance, making seasonal and climatic conditions a key design factor [38,39,40,41,42,43,44,45,46]. CO₂ has also been explored as an efficient heat carrier in geothermal systems, particularly for U-shaped closed-loop designs. Increasing the CO₂ flow rate from 4 kg s⁻¹ to 14 kg s⁻¹ has been shown to improve heat transfer characteristics while simultaneously lowering pressure losses. The recommended inlet pressure for such systems is around 28 MPa. System performance is particularly sensitive to inlet temperature and inlet velocity, especially when operating in the supercritical state at the downhole. At low mass flow rates, conduction heat loss is the primary contributor to inefficiency, whereas at later operational stages, combined heat losses and Joule–Thomson effects become more dominant [47,48,49].

Antifreeze mixtures are widely used to prevent freezing in borehole heat exchangers (BHEs) and to maintain operational stability in cold climates. For instance, in mild climates, a water and 25% ethylene glycol mixture can maintain the mean fluid temperature higher than pure water, thus avoiding freeze-related system downtime [27]. Microencapsulated phase change slurries (MPCS) offer another advanced option. A mixture containing 30% ethylene glycol by mass can reliably prevent tube freezing. Furthermore, when an MPCS with a mass fraction of 8.7% is applied in a ground-source heat pump (GSHP) installation, the coefficient of performance (COP) increases by roughly 5% compared to conventional systems. A volume fraction of around 12% has been identified as optimal for balancing thermal performance and system suitability [50,51,52].

Table 1. Overview of working fluids used in geothermal heat exchangers.

Working Fluid	Key Advantages	Limitations	Performance Notes	References
Pure Water (PW), Sodium Chloride Solution (SCS), Calcium Chloride Solution (CCS)	Safe, non-toxic, excellent thermal conductivity	Corrosive to metals in presence of air	CCS can increase outlet temperature by +2.94 °C and reduce heat pump power consumption by ~4.01% vs. PG25% because of its superior heat conductivity and reduced viscosity. SCS/CCS have lower viscosity than glycols/ethanol, reducing energy losses	[35,36]
Ethylene Glycol Solution (EGS)	Low corrosion potential, favorable thermal conductivity	High viscosity at low temperatures → greater flow resistance	Often used as an antifreeze; CCS and EGS are generally optimal choices for working fluids in terms of thermal performance	[35]
Ethanol-based mixtures	Can serve as antifreeze	33% ethanol can cause condensation at GHE outlet, lower thermal conductivity, higher kinematic viscosity → laminar flow, higher thermal resistance	Not recommended at high concentrations for efficiency reasons	[37]
Air	Available, low cost, non-toxic	Lower heat capacity than liquids; performance sensitive to velocity, humidity, depth	Effectiveness decreases as inlet velocity increases (0.5–20 m/s); higher inlet temperatures (38–46 °C) increase heat transfer/effectiveness; deeper burial improves performance; soil saturation, atmospheric and seasonal effects are important	[40,43,44,46]
CO2	High heat transfer potential, especially in supercritical state	Sensitive to inlet temperature and velocity; requires high pressures (~28 MPa)	Increasing flow rate from 4 to 14 kg/s improves heat transfer and reduces pressure loss; inefficiency due to conduction loss at low flow and Joule–Thomson effects at later stages	[47,48,49]
Antifreeze mixtures (e.g., 25% ethylene glycol–water)	Prevents freezing in BHEs, stable operation in cold climates	Possible viscosity increase; may reduce heat transfer slightly vs. water	Maintains mean fluid temperature higher than pure water in mild climates, preventing freeze downtime	[27]
Microencapsulated Phase Change Slurries (MPCS)	Freeze prevention, potential COP improvement	Need to balance volume fraction for optimal performance	30% ethylene glycol prevents freezing; 8.7% MPCS increases COP by ~5% vs. conventional; ~12% vol. fraction optimal	[50,51,52]

summarizes the key characteristics, advantages, and limitations of these working fluids for geothermal heat exchanger applications.

While propylene glycol is preferable for its non-toxic nature, it is more expensive and has a lower heat transfer efficiency than ethylene glycol. It can also cause galvanic corrosion, so inhibitors are usually added to mitigate this, although these additives may introduce a measurable environmental impact [53,54,55,56]. Laboratory and field studies on ground and aquifer samples indicate that both ethylene and propylene glycol generally have low toxicity in most oxic and anoxic environments [57]. However, the main contamination risk is largely linked to the additives in antifreeze mixtures rather than the glycols themselves. Specific components used as biocides or corrosion inhibitors may adversely affect subsurface microbiology and slow the degradation of antifreeze agents [56]. Tang and Nowamooz [33] and Mohamad et al. [34] emphasized that it is vital to correctly adjust the volume concentration when mixing antifreeze with the heat transfer fluid to avoid freezing, control viscosity, improve the GHE’s thermal efficiency, and lower operating costs. Incorrect dosages can affect the thermal resistance at the fluid–pipe interface, thereby decreasing the ground heat exchanger (GHE) efficiency [1]. From an environmental perspective, ethylene glycol (EG) is not persistent in air, surface water, soil, or groundwater; is practically non-toxic to aquatic organisms; and does not bioaccumulate. It undergoes rapid biodegradation and poses minimal long-term ecological risk [58]. Neuberger et al. [37] discovered that combining 80% pure water with 20% ethanol enhances the characteristics of the fluid, improving heat transfer between the fluid in the pipe and the surrounding ground. However, when the ethanol concentration increased from 22% to 33%, the kinematic viscosity of the mixture increased, while its thermal conductivity decreased. As a result, convective thermal resistance increased, leading to a drop in heat transfer performance. This was due to the improper volume concentration, which disrupted the optimal balance required for sufficient thermal conductivity and effective heat transfer. Tang and Nowamooz [33] found that adding 24% ethanol to pure water performed better than 20% CaCl₂, 25% propylene glycol, or 33% propylene glycol solutions. Furthermore, a 20% CaCl₂ mixture provided greater effectiveness than 25% and 33% propylene glycol solutions, as well as a 24% ethanol blend, as indicated by Alessandro and Rajandrea [36].

Recently, there has been an increasing adoption of advanced heat exchange fluids, including nanofluids, hybrid fluids, and hybrid nanofluids, due to their superior capacity to boost thermal transfer and enhance the performance of ground heat exchangers (GHEs), outperforming traditional heat transfer fluids. Nonetheless, they are more challenging to manage and come with higher costs. The concept of nanofluids was originally presented by Choi in 1995 at Argonne National Laboratory, marking a pivotal advancement in thermal fluid technology. These engineered fluids consist of nanoparticles—typically metals, metal oxides, or carbon-based materials—suspended in conventional base liquids such as water, ethylene glycol, or oils. Compared to micro-sized particles, nanofluids offer enhanced thermal conductivity, better long-term dispersion stability, and reduced pressure drop [59]. The synthesis process is essential in defining fluid stability and performance. To meet specific application requirements, various nanoparticle–fluid combinations are developed, with or without surfactants, using materials such as aluminum, copper, gold, carbon nanotubes, and ceramics suspended in water, glycols, oils, or other lubricants. A key foundational contribution in this field was made by Choi and Eastman [60], who incorporated metallic nanoparticles into conventional heat transfer fluids to form “nanofluids” with enhanced thermal conductivity. Their research, which focused on copper nanoparticles, demonstrated that nanofluids could significantly improve heat transfer performance. The benefits included higher thermal conductivity and reduced pumping power requirements in heat exchangers, making nanofluids a promising solution for improving energy efficiency in thermodynamic applications. Nanofluids are a category of engineered liquids created by dispersing nanoparticles—commonly metals, metal oxides, or carbon-based compounds—into standard base fluids like water, ethylene glycol, or oils, to significantly improve their thermal properties [61]. Over the past two decades, extensive research has demonstrated that nanofluids can markedly enhance thermal conductivity, improve heat transfer coefficients, and reduce pumping power and system energy consumption [21,62,63,64]. These unique thermal and rheological characteristics have led to their increasing integration into various thermal applications, particularly heat exchangers, where optimized energy performance and compact design are critical. A major challenge in the field lies in identifying nanoparticle–base fluid combinations that offer not only superior thermal performance but also long-term colloidal stability, cost-effectiveness, and material compatibility. Among emerging solutions, graphene-based nanofluids have attracted substantial interest due to the exceptionally high thermal conductivity, large surface area, and stable dispersion characteristics of graphene nanosheets [62].

Numerous experimental and numerical studies have demonstrated that nanofluids can greatly improve convective heat transfer, particularly under laminar and transitional flow regimes [65,66,67,68]. For instance, alumina–water nanofluid at 6 vol.% increased the heat transfer coefficient by nearly 17% in the entrance region and 27% in the fully developed region compared to pure water [69]. Similarly, zirconia–water nanofluids at 1.32 vol.% showed modest improvements of about 2–3% [69]. Even more impressive results were reported for carbon nanotube (CNT)-based nanofluids, where a 0.5 wt.% CNT–water mixture achieved a heat transfer enhancement of over 350% at Re = 800, with peak performance measured at an axial location equal to 110 times the tube diameter [70]. Given these promising outcomes, ongoing research continues to explore carbon-based nanofluids, particularly graphene–water mixtures, to further improve thermal performance, reduce energy consumption, and support the development of next-generation heat exchangers for geothermal and other renewable energy systems. Beyond geothermal applications, nanofluids have also demonstrated significant potential in other thermal energy systems. For instance, Aramesh et al. [71] developed a modified thermal model to simulate transient heat extraction from a solar pond using water and six water-based nanofluids—Ag, Cu, CuO, Al₂O₃, SWCNT, and MWCNT. Their model showed that after 24 days of heat storage, the lower convective zone reached 98.66 °C with 40.51 GJ of stored energy. Heat extraction over 48 h was analyzed for 15 nanoparticle concentrations (0.1–5%), identifying threshold levels for optimal performance. Notably, SWCNT/water nanofluid at a 0.1% concentration achieved the highest extracted heat of 10.29 GJ, compared to 5.81 GJ for water, demonstrating the considerable enhancement nanofluids can provide in thermal energy systems beyond ground heat exchangers.

In a performance evaluation of nanofluids used in U-tube borehole heat exchangers, Jahanbin et al. [72] found that Ag- and Cu-based nanofluids significantly enhanced heat transfer but also led to increased pumping power. The Cu–water nanofluid achieved a 4.31% reduction in thermal resistance. SiO₂ nanoparticles were identified as the most cost-effective, offering a favorable balance between thermal performance and energy cost relative to capital investment. The same study also examined oxide nanofluids—specifically TiO₂, SiO₂, and Al₂O₃—at a 3% volume concentration and reported that these fluids improved heat transfer performance by approximately 15% compared with water alone. The Nusselt number rose by as much as 8.4%, indicating enhanced convective heat transfer. However, higher nanoparticle concentrations resulted in increased viscosity and friction factors, which slightly increased the pumping energy demand to maintain system flow [72]. Building on this, Kia et al. [73] performed a combined numerical and experimental study on the heat transfer and pressure drop behavior of Al₂O₃ and SiO₂ nanofluids dispersed in SN-300 base oil flowing through helical tubes under constant heat flux conditions. Their study examined various nanoparticle concentrations (0.05% to 0.5% by mass), fluid temperatures, and flow Reynolds numbers, together with the influence of helical tube geometry, including pitch circle diameter and pitch size. The results revealed that nanofluids improved both heat transfer coefficients and pressure drop relative to base oil, with Al₂O₃ nanofluids outperforming SiO₂ at the same concentration. The highest heat transfer enhancements were 41.4% for Al₂O₃ and 27.3% for SiO₂ nanofluids at a 0.5% mass concentration. Additionally, the helical tube design increased heat transfer by 19.5% compared to straight tubes, while reductions in helical pitch and pitch circle diameter further improved heat transfer by 6% and 16.5%, respectively. Weerapun and Wongwises [74] experimentally evaluated the heat transfer and pressure drop performance of TiO₂–water nanofluids in a horizontal counter-flow heat exchanger under turbulent conditions. Using 21 nm TiO₂ nanoparticles at volume concentrations ranging from 0.2 to 2.0%, they found the heat transfer coefficient improved by up to 26%, depending on the Reynolds number and particle concentration. However, performance decreased by ~14% at the highest concentration, and the pressure drop rose slightly with the concentration. They also introduced new correlations for estimating the Nusselt number and friction factor for these nanofluids. Building on these insights, recent studies have shown an increasing interest in the application of nanofluids as working media in ground-source heat pump (GSHP) systems, primarily due to their ability to significantly enhance convective heat transfer coefficients [74].

Building on these insights, recent studies highlight growing interest in nanofluids for GSHP systems due to their ability to improve convective heat transfer coefficients. Rohit et al. [75] carried out experiments on a concentric tube heat exchanger using water-based nanofluids at different nanoparticle concentrations. The results showed that a 3% nanofluid achieved the best performance, increasing the overall heat transfer coefficient by 16% relative to pure water. The authors of [76] studied the heat transfer and pressure drop performance of COOH-functionalized multi-walled carbon nanotube (CNT)/water nanofluids in a double-pipe exchanger. Nanofluids were prepared at 0.1–0.3 wt.% concentrations using a two-step method and tested in laminar and turbulent regimes (Re = 900–10,500). Results showed thermal conductivity gains of up to 56% and a 44% higher heat transfer coefficient at 0.3 wt.% compared with water, with only a small increase in pressure drop. Furthermore, Hormozi and Sarafraz [77] examined the forced convective heat transfer of a biologically derived Ag-based nanofluid in a circular tube exchanger. Nanoparticles (0.1–1 vol.%) were synthesized from green tea extract and dispersed in ethylene glycol–water (50:50). Tests under laminar to turbulent regimes showed up to a 67% improvement in the heat transfer coefficient at 1 vol.%, while also considering pressure drop effects. Amirhossein et al. [78] investigated the forced convection of Al₂O₃ and CuO nanofluids prepared in ethylene glycol using a double-pipe and plate heat exchanger under turbulent flow. Results showed a 2–50% enhancement in the convective heat transfer coefficient compared with the base fluid, increasing with particle concentration and temperature, though discrepancies appeared between theoretical and experimental results at higher temperatures and concentrations. Moreover, Hemmat and Saedodin [79] studied the thermal conductivity, viscosity, and Nusselt number of MgO–water nanofluids in turbulent forced convection through a circular pipe. Tests were performed using pure water and nanofluids with particle volume fractions between 0.005 and 0.02 and particle sizes between 20 and 60 nm. Findings revealed that increasing concentration and reducing particle size significantly boosted heat transfer, and standard correlations could not accurately predict the thermophysical behavior of the nanofluids.

Further research also emphasizes the influence of nanoparticle characteristics on performance. Arani and Amani [80] tested TiO₂–water nanofluids in a horizontal double-tube counter-flow heat exchanger under fully developed turbulent flow, focusing on convective heat transfer and pressure drop. Tests were conducted with nanoparticle sizes of 10–50 nm and concentrations of 0.01–0.02 vol.%. Findings showed higher Nusselt numbers for all nanofluids relative to water, with the 20 nm particles achieving the best overall thermal performance factor. Huaqing et al. [81] tested laminar convective heat transfer of Al₂O₃, ZnO, TiO₂, and MgO nanofluids in a circular copper tube using a 55:45 water–ethylene glycol base fluid. Their findings revealed that heat transfer enhancement was strongly influenced by nanoparticle type, size, concentration, and flow conditions, with MgO nanofluid delivering the highest improvement—up to 252% at Re = 1000—indicating oxide nanofluids as promising alternatives to conventional coolants. Sonawane et al. [82] experimentally analyzed the heat transfer of Al₂O₃/water nanofluids in a copper concentric tube heat exchanger (1000 mm length). Results showed higher heat transfer rates than pure water, increasing with nanoparticle concentration and Reynolds number, thus enhancing cooling efficiency at low heat flux systems. Chandra Sekhara et al. [83] studied the heat transfer coefficient and friction factor of TiO₂ nanofluids in a double-pipe heat exchanger with and without helical coil inserts. Tests covered Reynolds numbers from 4000 to 15,000 and concentrations of 0.0004–0.02% in a 40:60 ethylene glycol–water mixture. Results showed enhancements of 10.73% (without insert) and 13.85% (with insert) in the heat transfer coefficient compared with the base fluid, with corresponding increases in the friction factor.

In summary, this section reviews the classification, characteristics, and performance of heat transfer fluids (HTFs) for ground heat exchangers (GHEs), covering both traditional fluids—such as water, glycol mixtures, brines, oils, air, CO₂, and antifreeze blends—and advanced options like nanofluids, hybrid fluids, and hybrid nanofluids. Traditional fluids are widely used for their proven reliability and availability, but they may face issues, including freezing risk, higher viscosity at low temperatures, corrosion, or reduced thermal conductivity. Advanced fluids offer improved thermal conductivity, higher heat transfer efficiency, and potential energy savings, yet present challenges in stability, cost, and pumping requirements. The efficiency of GHE depends on key fluid characteristics such as thermal conductivity, viscosity, density, and specific heat, alongside environmental and operational factors like toxicity, biodegradability, and material compatibility. Ultimately, selecting the right HTF is essential to maximize system efficiency, reliability, and cost-effectiveness and should be tailored to climate, soil type, installation depth, and system design while considering the potential future adoption of advanced fluids.

3. Nanofluids for Enhanced Heat Transfer: Properties and Performance

Nanofluids—formulated by dispersing nano-sized particles (1–100 nm) into conventional base fluids—are known to boost both thermal conductivity and convective performance [22,84]. Due to these enhanced thermophysical characteristics, nanofluids have been increasingly studied as advanced working fluids in GHE systems. For instance, the heat transfer rate within a GHE using Al₂O₃/water nanofluids rises with increasing particle concentration and decreasing particle size. Even at low concentrations, nanofluids can significantly enhance GSHP efficiency. For example, a 3 wt.% CuO/water nanofluid boosted the heat transfer rate and lowered pumping power by 40% and 17%, respectively, compared to pure water [85,86,87,88]. To maximize such benefits, the pipe length in GHE systems should be minimized. CuO/water nanofluids demonstrated better heat transfer than Al₂O₃/water, though with higher pressure requirements [89]. The order of convective heat transfer coefficient among several nanofluids and solid additives has been reported as Ag > Cu > Al₂O₃ > graphite > SiO₂ > CuO > water. For pressure drop, the ranking is Ag > Cu > CuO > Al₂O₃ > Al > SiO₂ > graphite [90,91]. While nanofluids hold strong promise, their application must be evaluated carefully to account for economic factors, long-term stability, and impacts on both thermal and flow performance.

In one study, Al₂O₃/water nanofluids at 0.2 vol.% increased the Nusselt number by as much as 27%, while only raising the pressure drop by 8% [92]. Dan et al. [93] conducted a numerical analysis of nanofluid thermal performance in a geothermal double-pipe heat exchanger, showing that nanofluids raised overall energy extraction by 11.24% compared with water. Giuseppe et al. [90] found that replacing ethylene glycol–water with nanofluids in BHEs enhanced performance, while copper-based nanofluids provided the highest reduction in thermal resistance (up to 3.8% at 1% concentration) but also raised pressure drop and cost (~EUR 10/m, ~12% of total installation cost). In contrast, Al₂O₃ and SiO₂ nanofluids showed lower costs, better stability, and minimal impact on pressure drop, making them favorable for balancing efficiency and economics in GHE applications [92]. These oxide-based nanofluids generally exhibit Newtonian behavior and improved thermal conductivity, enabling efficient convective heat transfer without significant viscosity penalties.

Complementing these experimental and economic evaluations, Pourfayaz et al. [94] used computational fluid dynamics (CFD) simulations to analyze a deep-borehole GSHP system with nanofluids—including silver, copper, copper oxide, and aluminum oxide—as working fluids. Their results demonstrated that nanofluids can significantly improve heat exchange, raise outlet fluid temperatures, and enhance system efficiency. Specifically, total exchanged heat increased by 4.83%, 5.76%, 6.9%, and 7.69% for aluminum oxide, copper oxide, copper, and silver nanofluids, respectively. The coefficient of performance (COP) also rose—by 36.5% for silver-based nanofluids and 5.2% for aluminum oxide-based nanofluids—confirming the strong potential of nanofluids in geothermal heat pump systems. Building upon these advances, Jasim et al. [95] conducted numerical research on the combined effects of nanofluid enhancement and geometric design in a shell-and-coil tube heat exchanger with a double helical coil. Two hybrid nanofluids—TiO₂–MgO/water and Ag–HEG/water—were tested across Reynolds numbers ranging from 500 to 2000. At constant volume fraction (ϕ₁ = ϕ₂ = 0.3), TiO₂–MgO/water showed superior performance. Further simulations with variable concentrations (0.1–0.5%) confirmed the results. Importantly, the double coil design delivered substantially higher heat transfer rates compared to both single coil systems and pure water, showing the synergy of hybrid nanofluids with advanced exchanger geometries.

Expanding on this, Ahmad et al. [96] experimentally studied the convective heat transfer behavior of graphene-based nanofluids in a shell-and-tube exchanger under laminar conditions. The graphene nanosheets were synthesized via chemical vapor deposition and analyzed using SEM and Raman spectroscopy. Findings showed that adding just 0.075 wt.% graphene increased thermal conductivity by 31.83%, while 0.1 wt.% at 38 °C improved the convective heat transfer coefficient by 35.6% compared to pure water. This underscores the strong potential of graphene nanofluids in boosting exchanger efficiency. Javadi et al. [97] carried out a numerical investigation of four hybrid nanofluids in U-tube borehole exchangers, with Ag–MgO/water achieving the best thermal performance by combining low resistance with high heat transfer. However, despite these improvements, all tested fluids showed COP values below unity, meaning that increased pressure drop canceled out heat transfer benefits—limiting their practical feasibility. Sergio et al. [98] conducted a theoretical and preliminary investigation on the use of Al₂O₃/water nanofluid as a working fluid for geothermal heat exchanger systems, focusing on various concentrations (3%, 5%, 30%, and 40%) and volume fractions. Analysis of the Moursomeff number and thermal behavior indicated that low-concentration nanofluids, especially 3 wt.% Al₂O₃/water (W440), may be better suited for high-temperature geothermal applications. These mixtures can potentially boost heat transfer without substantially increasing viscosity or pumping requirements. However, additional detailed experiments and long-term evaluations are needed to confirm the effectiveness and feasibility of Al₂O₃/water nanofluids in GSHP systems.

Several investigations have examined how tube geometry and the use of inserts affect nanofluid performance. Ardekani et al. [99] tested heat transfer under turbulent flow in straight and helically coiled tubes using Ag/water and SiO₂/water nanofluids with uniform heat flux. Their results indicated improvements in convective heat transfer, with maximum increases of 34–45% for Ag/water and 32–50% for SiO₂/water, particularly in helically coiled tubes. Higher Reynolds numbers, greater nanoparticle concentrations, and smaller coil diameters further raised heat transfer coefficients, though pressure drops also became larger. Similarly, Kannadasan et al. [100] conducted experiments on CuO/water nanofluids in a helically coiled heat exchanger under turbulent conditions, with both horizontal and vertical configurations. Results showed 36% and 45% enhancement in the Nusselt number for 0.1% and 0.2% CuO/water in the horizontal setup and 37% and 49% increases in the vertical configuration, respectively. The differences between orientations were minor, but both confirmed a strong enhancement compared to water. The Nusselt number improved by 36% and 45% by 0.1% and 0.2% CuO/water nanofluid in the horizontal setup, while it increased by 37% and 49% respectively, in the vertical configuration. Farzan et al. [101] carried out numerical and experimental work on helically coiled tubes using nanofluids under constant wall temperature conditions, studying both pressure drop and heat transfer. Their findings showed that the homogeneous model significantly underestimated heat transfer compared to actual measurements. Kahani et al. [102] analyzed Al₂O₃/water and TiO₂/water nanofluids in helically coiled tubes under uniform heat flux with nanoparticle concentrations ranging from 0.25% to 1.0% and Reynolds numbers between 500 and 4500. Both nanofluids improved thermal performance, though Al₂O₃/water provided greater enhancement due to its higher thermal conductivity and smaller particle size. Tube curvature was also found to strongly influence the heat transfer rate.

Puja et al. [103] conducted experiments to evaluate the hydrodynamic performance of nanofluid flow in both straight and helical coil tubes. The nanofluids were based on ethylene glycol/water (EG/W) and propylene glycol/water (PG/W) mixtures (60:40 by weight), with alumina nanoparticles at concentrations of 0–2.5 vol.%. Their findings showed that, in both geometries, nanofluids consistently exhibited higher friction factors compared to the base fluids. Ali et al. [104] studied friction factor behavior and convective heat transfer performance of γ-Al₂O₃ nanofluids in horizontal shell-and-coil heat exchangers under turbulent flow conditions. Using 40 nm particles at 0–2% volume fractions, they proposed new empirical correlations for estimating the Nusselt number and Fanning friction factor in coiled tube systems. Jafaryar et al. [105] investigated the heat transfer enhancement and pressure drop of CuO/water nanofluids in tubes equipped with twisted tape inserts through single-phase finite volume modeling. Their results indicated that lower pitch ratios improved fluid mixing, increased velocity, and enhanced secondary flows while also reducing thermal boundary layer thickness. Ravi Kumar et al. [106] experimentally tested Fe₃O₄/water nanofluids in a U-bend heat exchanger with twisted tape inserts. At a 0.06% concentration and Re = 30,000, they observed that the Nusselt number increased by 14.76% without inserts, and by 38.75% when H/D = 10 inserts were used. However, friction factors increased to 1.09–1.25 times that of water. They also developed new correlations for the Nusselt number and friction factor. Pazdar et al. [107] performed experiments on Cu/water nanofluids flowing through copper microtubes across a Reynolds number range of 700–2100, and concentrations of 0%, 0.1%, and 0.3%. They reported that at 0.3% loading, the highest performance evaluation criterion (2.24) was achieved, showing strong heat transfer enhancement. They also proposed new empirical models for nanofluid flow behavior, incorporating the nanoparticle concentration, curvature ratio, Reynolds number, and Prandtl number. Sayankar et al. [108] studied polyaniline (PANI)/water nanofluids in a vertically coiled tube heat exchanger. With concentrations of 0.1–0.5 vol.%, their experiments achieved a maximum heat transfer coefficient of 515.8 W/m²·°C and an improvement of up to 69.62% compared to the base fluid (water). Peyghambarzadeh et al. [109] experimentally investigated the forced convective heat transfer of Al₂O₃–water nanofluids with concentrations of 0.1–1 vol.% in a tubular heat exchanger under turbulent flow conditions (Re = 9 × 10³–2.3 × 10⁴) and inlet temperatures between 37 and 49 °C. Their findings indicated that higher flow rates substantially improved heat transfer performance, while the inlet temperature had minimal influence. Overall, Al₂O₃ nanofluids enhanced heat transfer efficiency by up to 45% relative to water.

Daneshipour and Roohollah [89] performed numerical simulations to compare CuO/water and Al₂O₃/water nanofluids in a coaxial borehole heat exchanger (BHE). Results revealed that CuO/water nanofluid provided superior heating efficiency. Furthermore, substituting nanofluid for water reduced the required borehole depth by approximately 1.3%, lowering installation demand. Yuanling et al. [110] tested CuO/water nanofluids in a single U-tube BHE with different nanoparticle sizes and volume fractions. The study found that BHE performance improved with CuO/water nanofluids compared to water. Xiao-Hui et al. [111] examined the suspension stability of Fe₃O₄/water and Al₂O₃/water nanofluids in a coaxial BHE. Their results suggested that, beyond optimizing the borehole geometry, applying pulsed fluid flow enhanced long-term system reliability by improving nanoparticle dispersion and reducing sedimentation risks. Similarly, Lena et al. [112] evaluated TiO₂–CNT hybrid nanofluids in a shell-and-tube heat exchanger under laminar flow. The study focused on temperature and mass fraction effects on convective heat transfer and showed that the effective thermal conductivity of the hybrid nanofluid was about 21.5% higher than the base fluid, highlighting the potential of hybrid nanostructures for advanced heat exchanger applications.

Choosing an optimal nanofluid formulation continues to pose a major challenge in improving thermal system performance. To address this, Amin [113] proposed a three-step guideline for identifying high-performance nanofluids. Their study dispersed MWCNT–ZnO nanoparticles in thermal oil (concentrations of 0.125–1%) using a two-step synthesis method. Stability was validated through zeta potential measurements, while thermal conductivity was measured across a temperature range of 15–55 °C. The research also analyzed pumping power variations under laminar and turbulent flow and evaluated convective heat transfer characteristics, further contributing to nanofluid design optimization. The results showed a 42% enhancement in the convective heat transfer coefficient, demonstrating the nanofluid’s superior thermal performance compared to conventional fluids like water and thermal oil. Nabil et al. [114] conducted an experimental study on forced convection heat transfer and friction factor of TiO₂–SiO₂ hybrid nanofluids flowing through a circular tube under turbulent conditions. The nanofluids, prepared using a two-step method at 0.5–3.0 vol.% with a 50:50 nanoparticle ratio, were dispersed in a water/ethylene glycol (60:40) base fluid. Tests carried out at 30–70 °C under constant heat flux revealed that the heat transfer coefficient increased steadily with both nanoparticle concentration and temperature, achieving a maximum enhancement of 81% at 3.0 vol.% and 70 °C. The friction factor rose only slightly with concentration, indicating negligible practical penalties in real applications.

Similarly, Narei [86] explored the potential of Al₂O₃/water nanofluids for vertical ground heat exchangers (GHEs) to improve thermal performance and reduce installation costs in GSHP systems. Using a multi-objective optimization approach with the Flower Pollination Algorithm, which integrates advanced non-dominated sorting logic, the study fine-tuned nanofluid properties such as thermal conductivity and viscosity. Results showed that substituting water with Al₂O₃ nanofluid led to only a minor borehole depth reduction (<1.3%), but grout conductivity optimization offered a more effective path for lowering both borehole depth and total system cost. Further supporting the potential of nanofluids in improving heat exchanger performance, Weerapun and Somchai [74] investigated TiO₂–water nanofluids in a horizontal double-tube counter-flow heat exchanger under turbulent conditions. With TiO₂ nanoparticles (21 nm) at concentrations of 0.2–2.0 vol.%, they observed up to a 26% increase in the heat transfer coefficient at higher Reynolds numbers and concentrations. However, performance dropped by 14% at the highest concentration, suggesting an optimal loading threshold. A slight increase in pressure drop was also reported, and the authors developed new correlations for predicting Nusselt number and friction factor. In a related study, Weerapun and Somchai [115,116] further studied thermophysical property models for TiO₂–water nanofluids at 0.2 vol.%. Their findings indicated that different models had a limited influence on estimated Nusselt numbers. The nanofluid achieved a modest 6–11% enhancement in heat transfer compared to pure water, again with only a minor increase in pressure drop, reaffirming its potential for heat exchanger applications.

Choi et al. [24] further investigated the thermal behavior of nanotube-in-oil suspensions, revealing that their effective thermal conductivity exceeded classical predictions and increased nonlinearly with MWCNT concentration. Their findings showed up to a 150% enhancement in thermal conductivity, underscoring the dominant role of MWCNTs in boosting heat transfer and challenging the assumptions of conventional heat conduction models. To advance practical applications, Ahmadreza et al. [117] examined the performance of transformer oil-based nanofluids for improved thermal conductivity and heat transfer compared to conventional transformer oils. Four nanofluids were synthesized using a two-step method: one with pure multi-walled carbon nanotubes (MWCNTs) and three hybrids containing 20 vol.% MWCNTs blended with 80 vol.% Al₂O₃, TiO₂, or SiO₂. Tests showed that hybrid carbon-based nanofluids exhibited superior dielectric properties over pure MWCNT nanofluids. Qiang and Yimin [118] experimentally studied the thermal and hydraulic performance of Cu–water nanofluids flowing through a tube under both laminar and turbulent conditions. Their results revealed a remarkable 60% increase in the heat transfer coefficient at a 2.0 vol.% concentration, with only minimal impact on friction factors at lower nanoparticle loadings. Expanding on these insights, Zeinali et al. [61,119] tested Al₂O₃–water and CuO–water nanofluids in an annular concentric tube under laminar flow and constant wall temperature. Results demonstrated that the heat transfer coefficient increased with Peclet number and particle concentration, with Al₂O₃ nanofluids providing greater enhancement than CuO-based ones. Similarly, Lee et al. [120] reported that dispersing 4 vol.% of 35 nm CuO nanoparticles in ethylene glycol resulted in a 20% rise in thermal conductivity, emphasizing the strong influence of both nanoparticle size and concentration. Additional studies confirmed that smaller particles and higher loadings significantly improved conductivity and heat transfer performance. Moreover, Ying et al. [64] further demonstrated that both nanoparticle size and concentration play critical roles in boosting thermal conductivity, with smaller particles and higher loadings yielding greater improvements. Focusing on localized effects, Wen and Ding [62] analyzed the entrance region in laminar flow through a copper tube, finding that the local convective heat transfer coefficient increased with Reynolds number and Al₂O₃ nanoparticle concentration. Similarly, Kim et al. [121] investigated alumina and carbonic nanofluids in circular tubes, highlighting that nanoparticle motion at the entrance region substantially contributed to the overall heat transfer enhancement.

In addition, Reiyu and Jason [122] conducted an experimental study on the cooling performance of CuO–water nanofluids (0.2–0.4%) in a microchannel heat sink. They utilized established predictive models—including the Hamilton–Crosser model [123], Xuan and Roetzel correlation [69], and Brinkman equation [124]—to estimate thermal conductivity, specific heat, and viscosity. Their results revealed that nanofluids enhanced energy absorption at low flow rates compared to pure water, though this advantage diminished at higher flow rates. Ding et al. [66] experimentally examined the local heat transfer coefficient of CNT–distilled water nanofluids under laminar flow. Their study reported a notable increase in heat transfer performance, influenced by flow conditions, CNT concentration, and pH, with pH showing the least effect. They also emphasized the role of CNTs’ high aspect ratio in boosting performance. Yurong et al. [125] investigated the convective heat transfer and flow characteristics of Cu–water nanofluids in a straight tube under laminar and turbulent flow conditions with constant heat flux. Their results showed that nanoparticle addition significantly improved heat transfer, while the friction factor of nanofluids remained comparable to that of pure water. Moreover, they proposed new empirical correlations for predicting convective heat transfer coefficients under both laminar and turbulent regimes. Saeedinia et al. [126] studied the heat transfer and pressure drop of CuO/water nanofluids (0.07–0.3%) flowing through a smooth tube equipped with wire coil inserts under constant heat flux. Results demonstrated that wire coils could enhance heat transfer by up to 45%, but at the cost of a 63% increase in pressure drop, strongly dependent on Reynolds number and wire diameter. Hashemi and Akhavan-Behabadi [127] evaluated the heat transfer and pressure drop of CuO-based nanofluids in a horizontal helical tube under constant heat flux. They found that helical coils significantly improved convective heat transfer compared to straight tubes, although accompanied by a higher pressure drop. Increasing nanoparticle concentration, Reynolds number, and fluid temperature further improved the heat transfer coefficient but also exacerbated pressure losses. Overall, helical coiling proved more effective than nanoparticle addition alone for enhancing convective performance. Suresh et al. [128] conducted an experimental investigation on convective heat transfer and friction factor in plain and helically dimpled tubes under turbulent flow (Re = 2500–6000) using CuO/water nanofluids. Results showed that the helically dimpled tube enhanced heat transfer by 19%, 27%, and 39% for the respective concentrations compared to a plain tube with water, while causing only a 2–10% increase in friction factor. This demonstrates that combining surface geometry modifications with nanofluids can significantly enhance thermal performance with minimal pressure penalties. Mateusz et al. [129] experimentally investigated the heat transfer of CuO–water nanofluids stabilized with CTAC in a helically coiled tube under turbulent flow (Re = 6000–21,968). Their study showed a Nusselt number increase of 18–35% compared to water, with CTAC playing a critical role in stabilizing the nanofluid and improving heat transfer. Palanisamy and Kumar [130] evaluated the heat transfer and pressure drop of cone helically coiled tube heat exchangers using MWCNT–water nanofluids (0.1–0.5%) prepared with surfactant via the two-step method. Under turbulent conditions (2200 < Re < 4200), they reported Nusselt number improvements of 28–68%, with pressure drops increasing by 16–42% depending on concentration. Importantly, the nanofluids maintained stability for 45 days without visible deposition, erosion, or handling hazards, indicating their potential as reliable alternatives for high-performance heat transfer fluids, even under high-pressure conditions.

Pakdaman et al. [131] experimentally tested MWCNT/oil nanofluids in vertical helically coiled tubes under laminar flow with a wall temperature of 95 °C. Nanofluid concentrations of 0.1–0.4% were evaluated, with 0.4% achieving a peak performance index of 6.4, underscoring their strong applicability to industrial-scale heat exchanger systems. Kumar and Chandrasekar [132] performed numerical simulations of a double helically coiled tube heat exchanger using MWCNT–water nanofluids (0.2–0.6%) under laminar flow (Dean number 1300–2200). Results showed that increasing the nanofluid concentration raised the Nusselt number by up to 30% and the pressure drop by 11% compared to water. CFD predictions agreed closely with experimental data, deviating by only 7.2% (Nusselt number) and 8.5% (pressure drop), validating the accuracy of the model. Rasheed et al. [133] experimentally analyzed circle, oval, and elliptical helical microtube coils with Al₂O₃–water and ZnO–water nanofluids (1.0–2.0%). Results demonstrated that curvature-induced swirl flows in helically coiled microtubes markedly enhanced heat transfer over straight coils, though accompanied by higher frictional losses. The findings highlighted the strong dependence of thermal performance on nanoparticle concentration and Reynolds number, with the circular geometry using 2% Al₂O₃ nanofluid achieving the highest thermal performance ratio of 3.1 at Re = 1800. Gabriela and Angel [134] performed a numerical analysis of heat transfer and entropy generation in a helically coiled tube-in-tube heat exchanger under laminar flow using CuO– and TiO₂–water nanofluids (0–2.0 vol.%). In their configuration, the nanofluid circulated through the inner tube, while water flowed through the annulus at half, equal, or double the inner-tube flow rate. Results revealed that nanofluids significantly enhanced heat transfer efficiency, achieving maximum effectiveness of 91% for CuO and 80% for TiO₂ nanofluids, while also increasing the Nusselt number and reducing entropy generation due to improved thermal transport. Viscous effects were found to be negligible. Hyun et al. [135] conducted experimental investigations of pressure drop and viscosity in CNT–water nanofluids flowing through horizontal tubes. Their work compared acid-treated CNTs (TCNTs) and surfactant-assisted CNTs (PCNTs), finding that TCNT nanofluids had substantially lower viscosity, while PCNT nanofluids exhibited greater flow resistance, especially under laminar regimes. At higher Reynolds numbers, however, the friction factors of both nanofluids approached those of pure water, suggesting minimal hydrodynamic penalties at turbulent flow conditions. Similarly, Pak and Cho [136] studied γ-Al₂O₃ and TiO₂ nanofluids in horizontal circular tubes under constant heat flux. Their findings indicated that while the Nusselt number increased with the Reynolds number and particle loading, the heat transfer coefficient at 3.0 vol.% was still 12% lower than that of pure water, underscoring potential performance limitations of certain nanofluid types under equivalent operating conditions. Nguyen et al. [137] investigated the thermal performance of Al₂O₃–water nanofluids in a turbulent-flow liquid cooling loop for microprocessor applications. Their results showed that nanoparticle inclusion significantly increased the heat transfer coefficient compared to water, with 36 nm particles providing superior enhancement over larger 47 nm particles. This highlighted the critical influence of particle size on thermal efficiency. Similarly, Nandy et al. [138] demonstrated that Al₂O₃– and CuO–water nanofluids reduced natural convection efficiency, largely due to nanoparticle settling and flow instabilities compared to base fluids. Chien et al. [139] experimentally studied gold–DI water nanofluids in a conventional heat pipe and found that the nanofluid significantly reduced thermal resistance compared to deionized water, even at the same nanoparticle concentration. In the context of phase-change applications, Sarit et al. [140] studied pool boiling in Al₂O₃–water nanofluids and found that higher particle concentrations worsened boiling performance by altering surface characteristics and suppressing transient conduction.

Beyond geothermal systems, nanofluids have also demonstrated strong potential in solar thermal applications. For example, Abdin et al. [141] conducted a theoretical study on entropy generation, heat transfer, and pressure drop in a flat-plate solar collector using nanofluids containing Al₂O₃, CuO, SiO₂, and TiO₂ nanoparticles suspended in water. Under steady, laminar axial flow, they examined nanoparticle volume fractions of 1–4% and flow rates of 1–4 L/min, reporting that CuO–water nanofluid achieved the most favorable results. Specifically, it reduced entropy generation by 4.34%, increased the heat transfer coefficient by 22.15%, and produced only a 1.58% increase in pumping power compared to pure water. These findings demonstrate the thermodynamic advantages of nanofluids in solar collectors, emphasizing their ability to enhance energy efficiency with minimal penalties in flow performance. Supporting these results, broader investigations confirm that nanofluids generally display superior thermal and thermophysical properties compared to traditional fluids, leading to improved mass and heat transport. Both nanoparticle concentration and temperature have been found to consistently improve thermal conductivity, while the shape of nanoparticles plays a critical role. For instance, non-spherical particles yield greater enhancements in ionic fluids than spherical particles. These effects have been validated across a wide range of temperatures (10–250 °C) and nanoparticle concentrations (0.01–50%), highlighting the versatility and adaptability of nanofluids in diverse advanced thermal management applications [142].

In summary, advanced heat transfer fluids (HTFs)—particularly nanofluids, which are engineered suspensions of nanoparticles in conventional base fluids—have emerged as high-performance alternatives to traditional working fluids. Extensive experimental, numerical, and computational studies have consistently demonstrated their ability to enhance thermal conductivity, convective heat transfer, and system-level efficiency in applications such as ground heat exchangers (GHEs) and solar thermal systems. Reported performance improvements range from 10% to over 350%, depending on factors such as nanoparticle type, size, concentration, dispersion stability, and flow regime. Notably, advances in hybrid nanofluids, non-spherical particle geometries, and optimization strategies have further expanded the potential of these fluids to deliver superior heat transfer while minimizing viscosity penalties, pumping requirements, and operational costs. Despite ongoing challenges—such as ensuring long-term stability, controlling viscosity, and reducing costs—nanofluids represent a promising class of heat transfer fluids for next-generation energy systems, with significant implications for geothermal, solar, and broader thermal management technologies.

3.1. Thermal Conductivity of Nanofluids

Nanofluids, first introduced by Choi [143], are engineered colloidal suspensions consisting of a base fluid and nanoparticles (typically <100 nm), which possess thermal conductivities significantly higher than those of the base fluid. These nanoparticles can be dispersed in water, ethylene glycol, oils, refrigerants, or biofluids, forming stable suspensions with enhanced thermophysical characteristics. Among these properties, thermal conductivity is a critical factor in heat transport, making it especially valuable in geothermal applications such as ground heat exchangers (GHEs). Improved thermal conductivity enables more efficient subsurface energy transfer, reduces borehole length, and lowers pumping energy requirements. The incorporation of nanoparticles markedly enhances the thermal conductivity of the base fluid, thereby improving heat transfer performance. This enhancement is particularly important in systems such as GHEs, where efficient thermal coupling with the surrounding soil is crucial. Nanoparticles employed in nanofluids include metals (e.g., gold and copper), metal oxides (e.g., Al₂O₃, SiO₂, and CuO), carbides (e.g., SiC), nitrides (e.g., AlN and Si₃N₄), and carbon-based materials (e.g., carbon nanotubes and graphene). Their high surface area and intrinsic conductivity make them more effective for heat transport than conventional fluids [144,145].

As a result, nanofluids have emerged as promising candidates for geothermal systems, heat exchangers, and other thermal applications, where maximizing thermal conductivity directly improves system compactness, energy efficiency, and operational performance. Indeed, the thermal conductivity of nanofluids is one of their most extensively studied properties, since even modest improvements in conductivity can significantly influence design and performance in energy-related systems. It defines the ability of fluid to conduct heat, and even small improvements in this property can significantly influence the design, compactness, and overall efficiency of thermal systems. Lee et al. [120], Jeffrey et al. [146,147], Xuan et al. [148], Das et al. [149], and Choi [60] reported substantial improvements in thermal conductivity, ranging from 5% to 60%, for various nanofluids containing metal and metal-oxide nanoparticles. These enhancements were observed over particle volume fractions between 0.1 and 5%, demonstrating the strong potential of nanofluids to significantly outperform conventional heat transfer fluids.

Extensive studies have demonstrated that even small nanoparticle concentrations can substantially improve thermal conductivity. Jeffrey et al. [147] demonstrated that adding only 0.3 vol.% Cu nanoparticles with a mean diameter of less than 10 nm to ethylene glycol increased thermal conductivity by up to 40% compared to the base fluid. They emphasized that this enhancement could be crucial for developing more energy-efficient heat transfer devices. Similarly, Min-Sheng et al. [150] reported that Cu nanoparticles at a volume fraction of 0.1% enhanced thermal conductivity by 23.8% compared to pure water. However, the enhancement diminished over time, likely due to agglomeration or surfactant effects, underscoring the importance of nanoparticle stability. These results highlight the potential of low-concentration Cu nanofluids for improving heat transfer performance. Soeparman et al. [151] experimentally investigated the convective heat transfer and pressure drop of alumina–water nanofluids in a 1.1 m, 5 mm ID double-pipe heat exchanger under laminar flow. Their findings showed that increasing nanoparticle concentration enhanced the Nusselt number by up to 40.5% compared to water, with only a slight rise in pressure drop, indicating minimal hydraulic penalties. Moreover, Lee et al. [152] reported that thermal conductivity enhancement in nanofluids depends on both the nanoparticles and the base fluid. For instance, MWCNT–water nanofluids achieved 11.3% higher conductivity with only 0.01 vol.% loading, outperforming SiO₂-based nanofluids due to strong solid–liquid interactions. Conversely, Dae-Hwang et al. [153] experimentally analyzed the thermal conductivities of TiO₂, Al₂O₃, Fe, and WO₃ nanofluids synthesized via a two-step dispersion method. Using the transient hot-wire technique, they observed significant conductivity enhancements beyond classical mixture predictions. They concluded that the particle surface-to-volume ratio, rather than inherent conductivity, is the dominant factor, since smaller nanoparticles offer larger interfacial areas for heat transfer. Aida et al. [154] examined the thermal conductivity of water-based CNT nanofluids and found that conductivity decreased with increasing CNT wall number, indicating that single- and double-wall CNTs are more effective than multi-wall structures. Moreover, Huaqing et al. [155] studied MWNTs/water, MWNTs/glycol, and MWNTs/decene nanofluids, but observed only a modest 20% thermal conductivity enhancement at 1 vol.% loading—much lower than the 160% increase reported by Zhang et al. [24]. However, this improvement revealed a nonlinear relationship between conductivity and MWNT concentration [156]. Similarly, thermal conductivity can be enhanced by up to 200% by adding 0.35 vol.% multiwalled carbon nanotubes (MWCNTs) to poly(α-olefin) oil, as demonstrated by Ying et al. [157]. However, this increase was accompanied by a viscosity rise of nearly three orders of magnitude. Roghayeh et al. [158] experimentally studied the heat transfer performance of MWCNT/water nanofluids in a horizontal shell-and-tube heat exchanger. MWCNTs synthesized using catalytic chemical vapor deposition (CCVD) and functionalized with COOH groups demonstrated enhanced hydrophilicity and dispersion stability. Their results showed that adding MWCNTs significantly increased the heat transfer rate compared to the base fluid, highlighting the potential of CNT-based nanofluids for improving the thermal performance of shell-and-tube heat exchangers. Furthermore, Saidur et al. [159] numerically analyzed the application of nanofluids as working fluids in biomass heat recovery exchangers. Their simulations indicated that nanofluids enhanced both convective and overall heat transfer coefficients compared to water- or ethylene glycol-based fluids, with a maximum enhancement of 7.8%. Similarly, Rama et al. [160] theoretically investigated the thermal performance of a flat-plate fin compact heat exchanger using Al₂O₃/H₂O nanofluids. Results from ε-NTU analysis confirmed that nanofluids exhibit superior thermophysical properties compared to conventional coolants, resulting in improved heat transfer efficiency under various operating conditions. Vajjha et al. [161] conducted numerical investigations on flat-tube radiators under laminar flow using Al₂O₃ and CuO nanoparticles dispersed in ethylene glycol–water mixtures. Their study examined the influence of nanoparticle type, concentration, and Reynolds number. At a Reynolds number of 2000, they reported remarkable improvements: the heat transfer coefficient increased by 94% with a 10% Al₂O₃ nanofluid and by 89% with a 6% CuO nanofluid compared to the base fluid. Moreover, Yuen et al. [162] studied ethylene glycol-based CuO nanofluids in automotive cooling systems. Their findings confirmed that both the overall heat transfer coefficient and heat transfer rate increased when nanofluids were used, underscoring their suitability for real-world energy and transport applications. At moderate loadings, conductivity improvements remain notable. For example, adding 2% Cu nanoparticles to the base fluid resulted in a 3.8% enhancement in heat transfer at Reynolds numbers of 6000 (air) and 5000 (coolant).

Metal and metal-oxide nanoparticles consistently deliver measurable conductivity gains. Thermal conductivity can be enhanced by up to 70% by dispersing 0.3 vol.% copper (Cu) nanoparticles in water, using laurate salt as a dispersant, as shown by Soumen et al. [163]. Wei et al. [164] developed an ethylene glycol-based nanofluid with graphene nanosheets, achieving conductivity increases of up to 86% at 5.0 vol.% graphene. These enhancements were attributed to graphene’s unique two-dimensional geometry, high aspect ratio, and stiffness, which promote efficient thermal transport. Hybrid nanofluids also show promising results. Suresh et al. [165] prepared Al₂O₃–Cu/water hybrid nanofluids via hydrogen reduction (a 90:10 ratio of Al₂O₃ to CuO), reporting a 12.11% maximum improvement at 2 vol.% concentration, outperforming pure Al₂O₃ nanofluids. Hyun et al. [166] observed up to 75% conductivity enhancement by adding 1.2% v/v diamond nanoparticles (30–50 nm) to ethylene glycol. Pisarevsky et al. [167] carried out lab-scale geothermal coaxial heat exchanger tests with Al₂O₃/water nanofluids at concentrations of 2–8 wt.%. They found conductivity increased by 13%, though accompanied by a 20% rise in viscosity, yielding a net 9% performance improvement compared to the base fluid. Moreover, Hrishikesh et al. [168] reported that adding only 0.005–0.011 vol.% Au nanoparticles enhanced conductivity by 14%. Similarly, Ji-Hwan et al. [169] showed that surfactant-assisted dispersion—using sodium dodecylbenzenesulfonate (SDBS)—increased the conductivity of Cu/water nanofluids by 10.7% at 0.1 vol.% through improved nanoparticle stability. Suresh et al. [165] demonstrated that microwave-assisted precipitation and sonication of Al₂O₃ nanoparticles in distilled water produced stable suspensions with enhanced conductivity. Measurements at room temperature showed a rise in conductivity with the nanoparticle volume fraction, reaching a 9.7% gain at 3% loading. Similarly, Dongsheng et al. [170] highlighted that optimizing the pH and surfactant concentration can further enhance conductivity, underscoring the importance of dispersion stability in nanofluid design. Zhange et al. [171] demonstrated that the thermal conductivity of nanofluids increases with the addition of spherical nanoparticles—specifically Al₂O₃ (20 nm), ZrO₂ (20 nm), TiO₂ (40 nm), and CuO (33 nm)—as both volume fraction and temperature rise. These enhancements were consistent with the Hamilton–Crosser model, with no abnormal deviations observed. Extending this work, Zhang et al. [172] confirmed that thermal conductivity can be significantly influenced by the type, size, and concentration of nanoparticles in various nanofluids, including Au/toluene, Al₂O₃/water, TiO₂/water, CuO/water, and CNT/water suspensions. These results aligned with Hamilton–Crosser predictions for spherical particles and Yamada–Ota for CNTs. Remarkably, even extremely low concentrations (0.00013% Au nanoparticles in water) enhanced conductivity by ~20% [173].

Several studies have explored nanofluids incorporating various metallic and metal oxide nanoparticles, yielding promising results for thermal conductivity enhancement. Early studies on Al₂O₃-based nanofluids showed promising results. Ebata et al. [174] reported a 30% increase in thermal conductivity at 4.3 vol.% Al₂O₃ nanoparticles (13 nm) in water. However, Choi et al. [120] observed minimal improvement using larger particles (33 nm), suggesting that a smaller particle size promotes better conductivity. Similarly, CuO nanoparticles demonstrated strong potential, often outperforming Al₂O₃ at equivalent loadings in both water and ethylene glycol suspensions [120,175]. Xiaoping et al. [175] further emphasized that dispersion stability and morphology play crucial roles beyond just particle size. Syam et al. [176] studied Fe₃O₄ nanofluids across concentrations of 0.0–2.0% and temperatures of 20–60 °C. Results showed that thermal conductivity increased with both nanoparticle concentration and temperature, reaching a maximum enhancement of 48% at 2.0% loading and 60 °C, compared to the base fluid. Similarly, Aghayari et al. [177] experimentally investigated γ-Al₂O₃/water nanofluids (20 nm, 0.1–0.3 vol.%) in a double-pipe counterflow heat exchanger under turbulent flow. Findings revealed that higher nanoparticle concentrations and elevated operating temperatures improved performance, with Nusselt number increases of 19% and 24%, respectively, relative to water. These results showed close agreement with semi-empirical correlations. Furthermore, Omer et al. [178] explored the effect of the particle concentration (1–5 vol.%) and temperature (300–320 K) on nanofluid behavior, further confirming the strong dependence of thermal conductivity enhancements on both concentration and operating temperature. Satti et al. [179] examined nanofluids containing Al₂O₃, CuO, ZnO, SiO₂, and TiO₂ dispersed in a 60:40 propylene glycol/water base fluid. Results indicated that thermal conductivity increased consistently with both concentration (0.01–0.1 vol.%) and temperature (30–90 °C). Rohit et al. [180] studied the thermal conductivity of Fe₃O₄ nanoparticles dispersed in paraffin at volume fractions (0.01 to 0.1). The thermal conductivity increased by up to 20% compared to the base fluid at 0.1 vol.% Fe₃O₄ nanoparticles under ambient conditions. Other work has shown that diamond nanoparticles (ND) also yield notable conductivity gains. Yeganeh et al. [181] demonstrated that dispersing ND in deionized water at 0.8–3.0 vol.% increased thermal conductivity by 7.2% at 30 °C, further rising to 9.8% at 50 °C, underscoring the synergistic role of both concentration and temperature.

Furthermore, Bhuiyan et al. [182] investigated methanol-based nanofluids with Al₂O₃, TiO₂, and SiO₂ nanoparticles at concentrations of 0.005–0.15 vol.% over 1–20 °C. Enhancements reached 29.41% (Al₂O₃), 24.51% (TiO₂), and 23.03% (SiO₂) at 0.15 vol.% and 20 °C, with Al₂O₃ yielding the strongest effect. Their findings were further used to develop a predictive correlation for methanol-based nanofluids. Wei et al. [183] confirmed the benefits of AlN nanoparticles, achieving conductivity increases of 38.71% in ethylene glycol and 40.2% in propylene glycol at just 0.1 vol.% loading. Similarly, Min-Sheng et al. [184] studied MWNTs in synthetic engine oil and ethylene glycol, noting improvements of 12.4% at 1% loading in glycol and 30% at 2% in oil. They also demonstrated that thermal conductivity is strongly influenced by both the base fluid and nanoparticle concentration. In another study, Gandhi et al. [185] studied graphene suspensions across concentrations of 0.01–0.2 vol.% and temperatures up to 320 K, achieving a maximum enhancement of 27% at 0.2 vol.%. Wei et al. [186] observed that the thermal conductivity of ZnO–EG nanofluids increased with temperature in the range of 10 to 60 °C, demonstrating that temperature plays a key role in enhancing thermal conductivity, although the enhancement ratio remained relatively constant. They also reported that thermal conductivity improved nonlinearly with an increasing nanoparticle volume fraction, reaching a maximum enhancement of 26.5% at 5.0 vol.% ZnO nanoparticles.

Mahbubul et al. [187] investigated Al₂O₃/R141b nanorefrigerants, showing that thermal conductivity increased with both temperature (5–20 °C) and nanoparticle concentration (0.1–0.4 vol.%), reaching up to 1.013 times that of the base fluid. Moreover, Tun-Ping et al. [188] examined Al₂O₃/water nanofluids, finding that smaller nanoparticle size, higher temperatures, and greater weight fractions consistently enhanced conductivity. These results underscore the importance of carefully balancing particle size, loading, and operating temperature to optimize nanofluid thermal transport for geothermal and energy system applications. Ruiqing et al. [189] performed a numerical study on CuO/water nanofluids in geothermal heat exchangers, highlighting that both nanoparticle size and shape strongly influence performance. Their findings revealed that 40 nm spherical nanoparticles achieved the highest efficiency (1.0049), while smaller (5 nm) and larger (50 nm) particles were less effective. Spherical nanoparticles also provided an 8.55% improvement in energy efficiency compared to rod-shaped particles, emphasizing the role of geometry in optimizing thermophysical performance. Amir et al. [190] investigated TiO₂ nanofluids in bio-glycol/water mixtures (20:80 and 30:70 BG/W) at concentrations of 0.5–2.0 vol.% and temperatures between 30 and 80 °C. Results showed that thermal conductivity improved with both concentration and temperature, reaching a 12.6% maximum enhancement at 2.0% and 80 °C. However, viscosity increased with concentration (up to 1.53 times that of the base fluid at 2.0% and 70 °C for 30:70 BG/W) but decreased with temperature, reflecting a tradeoff between conductivity and flow performance. Baojie et al. [191] studied TiO₂ nanofluids in diathermic oil, focusing on conductivity and stability. Findings indicated that thermal conductivity increased linearly with the nanoparticle volume fraction, surpassing that of the base fluid across all tested concentrations. Chen et al. [192] experimentally analyzed SiC nanofluids, investigating their stability, optical properties, and thermal conductivity. Their results showed that SiC nanofluids increased thermal conductivity by over 6% at 0.4 vol.% compared to the base fluid. Additionally, the thermal conductivity of the seawater-based nanofluid increased by about 5.2% compared to the base fluid. Dan et al. [88] experimentally assessed CuO/water nanofluids in a geothermal heat exchanger (GHE), reporting a 39.84% increase in heat transfer rate and a 20.2% improvement in the heat load-to-pumping power ratio. However, this came at the cost of a 16.75% rise in pumping power consumption, reflecting the tradeoff between enhanced conductivity and hydraulic performance. The study highlighted that GHE design must minimize nanoparticle–fluid collisions and optimize the tube segment length for efficiency. Yuanling et al. [193] tested 17 different nanofluids (including Al₂O₃/water, CuO/water, and MWCNT/water) in a double-tube helically coiled heat exchanger under laminar and turbulent regimes. They observed that at high loadings, viscosity effects outweighed thermal conductivity benefits, leading to no enhancement in heat transfer and even up to 12.6% decreases for 5.9 vol.% Al₂O₃/water nanofluids. Furthermore, pressure drops increased significantly—by as much as 60% in laminar flow—but the performance trends could be predicted using single-phase modeling. Xuan and Li [194] investigated Cu–water nanofluids under turbulent flow in a brass tube (10 mm inner diameter). Their experiments showed a substantial improvement in heat transfer coefficients while maintaining a relatively small increase in friction factors. Sharma, et al. [195] further examined Al₂O₃ nanofluids flowing through tubes with and without twisted tape inserts. They found that nanofluids achieved a 23.7% increase in heat transfer coefficient at a 0.1 vol.% concentration and a Reynolds number of 9000, though friction factor increased by 1.21 times compared to water in a plain tube. In micro-scale applications, Jung et al. [196] studied Al₂O₃ nanofluids in rectangular microchannels (particle size ~170 nm). Their results showed that the heat transfer efficiency improved by up to 32% at 1.8 vol.% loading without causing significant frictional losses. This highlights the practical relevance of nanofluids in compact thermal management systems, where efficient dispersion ensures superior heat transport efficiency. Building on these findings, Wen and Ding [62] investigated the convective heat transfer coefficients of γ-Al₂O₃ nanoparticles suspended in deionized water flowing through a 4.5 mm diameter copper tube under laminar flow conditions. They observed a marked enhancement in heat transfer near the tube entrance, which gradually declined along the flow direction before reaching a steady-state value.

Building on these findings, Wen and Ding [67] investigated the convective heat transfer coefficients of γ-Al₂O₃ nanoparticles suspended in deionized water flowing through a 4.5 mm diameter copper tube under laminar flow conditions. They observed a marked enhancement in heat transfer near the tube entrance, which gradually declined along the flow direction before reaching a steady-state value. Overall, extensive experimental investigations confirm that nanofluids can significantly enhance thermal conductivity when nanoparticle type, size, concentration, base fluid, and dispersion stability are carefully optimized. Reported improvements range from modest percentages to over 200% in some formulations, though performance can decline with factors such as increasing CNT wall number, viscosity rise, particle agglomeration, or limited long-term stability. These findings underscore the potential of nanofluids to improve the efficiency of geothermal heat exchangers, microchannel cooling systems, and other energy-related thermal devices. However, the benefits must always be balanced against tradeoffs, including pumping penalties and challenges in achieving stable suspensions. In summary, nanofluids demonstrate versatile and effective means of enhancing heat transfer, and their diverse enhancement mechanisms are systematically summarized in

Table 2. Summary of thermal conductivity enhancement in nanofluids based on experimental studies.

Authors	Nanoparticle/Base Fluid	Concentration	Thermal Conductivity Enhancement	Key Findings and Improvement Strategies
Dan et al. [88]	CuO/Water	Various	Heat transfer ↑ 39.84%; heat load-to-pump power ↑ 20.2%	GHE experimental test; noted pumping power penalty (↑ 16.75%); recommended design optimization for better particle–fluid interaction.
Zhang et al. [24]	MWNTs/Synthetic Poly(α-olefin) Oil	1 vol.%	Up to 160%	Achieved exceptionally high thermal conductivity increase; noted nonlinear behavior, emphasizing influence of base fluid and MWNT loading.
Jeffrey et al. [147]	Cu (<10 nm)/Ethylene Glycol	0.3 vol.%	~40%	Utilized highly conductive copper nanoparticles with small size (<10 nm) to maximize surface area and heat conduction in ethylene glycol.
Min-Sheng et al. [150]	Cu/Water	0.1 vol.%	23.8%	Demonstrated effectiveness of low-concentration copper nanofluids; noted degradation over time due to lack of stabilizing agents or surfactants.
Soeparman et al. [151]	Al2O3/Water	Various	Nusselt number ↑ 40.5%	Double-pipe heat exchanger (laminar flow, 1.1 m length, 5 mm ID); improved convective heat transfer with minimal pressure drop.
Lee et al. [152]	MWCNT/Water	0.01 vol.%	11.3%	Highlighted that minimal loading of MWCNTs (0.01 vol.%) can yield significant conductivity gains due to strong interfacial thermal resistance reduction.
Dae-Hwang et al. [153]	Various metal oxides	Various	Significant	Found that smaller nanoparticle sizes with higher surface-to-volume ratios enhanced interfacial heat transfer more than intrinsic conductivity.
Aida et al. [154]	CNT/Water	Various	Performance dropped with more CNT walls	Observed that single- and double-walled CNTs performed better than multi-walled structures due to fewer phonon scattering centers and lower thermal resistance.
Huaqing et al. [155]	MWNTs in various fluids	1 vol.%	20%	Revealed nonlinear relationship between MWCNT concentration and thermal conductivity enhancement, affected by fluid type and dispersion stability.
Ying et al. [157]	MWCNT/Poly(α-olefin) oil	0.35 vol.%	200%	Achieved exceptional conductivity improvement using high aspect ratio MWCNTs in synthetic oil; however, this resulted in substantial viscosity increase, affecting flow.
Roghayeh et al. [158]	MWNT/Water	Various	Heat transfer rate ↑ markedly compared to base fluid	Shell-and-tube exchanger; MWNTs were synthesized via CCVD and functionalized (COOH), significantly improving dispersion stability and thermal performance.
Saidur et al. [159]	Cu/Ethylene Glycol	1 vol.%	Overall HTC ↑ 7.8%	Shell-and-tube heat recovery for biomass plant; improved convective and overall HTC at higher flow rates.
Rama et al. [160]	Al2O3/Water	Various	Higher thermal efficiency	Flat-tube plain fin compact heat exchanger; ε-NTU method; nanofluids showed better thermal properties vs. conventional coolant.
Vajjha et al. [161]	Al2O3, CuO/EG–Water	10% (Al2O3), 6% (CuO)	HTC ↑ 94% (Al2O3), ↑ 89% (CuO)	Flat-tube radiator under laminar flow; enhancement was dependent on nanoparticle type, concentration, and Reynolds number.
Yuen et al. [162]	Cu/EG	2 vol.%	HTC ↑ 3.8%	Automotive cooling system; there was notable increase in overall HTC at Re = 6000 (air) and 5000 (coolant).
Soumen et al. [163]	Cu/Water + laurate salt	0.3 vol.%	70%	Used laurate salt dispersant to achieve stable Cu nanoparticle dispersion in water, enabling significant thermal conductivity gains at low concentrations.
Wei et al. [164]	Graphene/Ethylene Glycol	5.0 vol.%	86%	Attributed 86% improvement to the two-dimensional geometry, stiffness, and high aspect ratio of graphene nanosheets dispersed in ethylene glycol.
Suresh et al. [165]	Al2O3–Cu/Water	2 vol.%	12.11%	Created hybrid nanofluid of Al2O3–Cu to combine high surface area and conductivity of metals with the stability of oxides, using hydrogen reduction synthesis.
Hyun et al. [166]	Diamond/Ethylene Glycol	1.2 vol.%	75%	Demonstrated that diamond nanoparticles significantly enhanced conductivity in ethylene glycol, influenced by small size (30–50 nm) and uniform dispersion.
Pisarevsky et al. [167]	Al2O3/Water	2–8 wt.%	TC ↑ 13%; performance ↑ 9%	Lab-scale geothermal coaxial exchanger; higher viscosity (↑ 20%) noted alongside conductivity gains.
Hrishikesh et al. [168]	Gold/Toluene	0.005–0.011 vol.%	14%	Achieved 14% enhancement at very low gold nanoparticle concentrations, highlighting high intrinsic conductivity and superior dispersion in toluene.
Ji-Hwan et al. [169]	Cu/Water + SDBS	0.1 vol.%	10.7%	Improved conductivity of Cu nanofluids using sodium dodecylbenzene sulfonate (SDBS) and pH tuning, ensuring better particle stability and heat transfer.
Dongsheng et al. [170]	Al2O3/Water + SDBS	0.15 wt.%	10.1%	Recommended optimizing surfactant (SDBS) dosage and pH to prevent agglomeration and improve Al2O3 nanofluid thermal conductivity in water.
Zhange et al. [171]	Al2O3, ZrO2, TiO2, CuO/Various Fluids	1.5 vol.%	Al2O3: ~15%, ZrO2: ~12%, TiO2: ~13%, CuO: ~14%	Thermal conductivity increased with both nanoparticle volume fraction and temperature. Enhancements closely matched the Hamilton–Crosser model predictions with no anomalies observed.
Zhang et al. [172]	Au, Al2O3, TiO2, CuO, CNT/Water, Toluene	CNT: 0.2 vol.%, Al2O3: 1.0 vol.%, TiO2: 1.0 vol.%, CuO: 1.0 vol.%, Au: 0.05 vol.%	Model-matched, e.g., CNTs up to ~22%, Al2O3 up to ~13%	Confirmed that thermal conductivity enhancement depends on particle type, size, and volume fraction; enhancements were consistent with classical models such as Hamilton–Crosser (for spherical) and Yamada–Ota (for CNTs); no anomalous behavior was observed across tested nanofluids.
Kumar et al. [173]	Au/Water	0.00013%	20%	Showed that extremely low concentrations of Au nanoparticles (0.00013%) can still yield notable conductivity increases due to high electron mobility.
Amir et al. [190]	TiO2/Bio-Glycol-Water	0.5–2.0 vol.%	Up to 12.6%	Thermal conductivity and viscosity both increased with concentration; rise in temperature reduced viscosity effects.
Ebata et al. [174]	Al2O3/Water	4.3 vol.%	30%	Highlighted size-dependence of thermal conductivity with Al2O3 nanoparticles, where smaller (13 nm) particles achieved much greater enhancement.
Syam et al. [176]	Fe3O4	2 vol.%	48%	Established Fe3O4 nanofluid performance depends strongly on both volume concentration and operating temperature, reaching 48% at 2% and 60 °C.
Aghayari et al. [177]	γ-Al2O3/Water	0.1–0.3 vol.%	HTC ↑ 19%; Nu ↑ 24%	Double-pipe counterflow exchanger; turbulent regime; enhancements increased with nanoparticle concentration and temperature.
Omer et al. [178]	CuO/R134a	1–5 vol.%	Increased up to ~24%	Identified particle concentration as a more dominant factor than temperature in enhancing nanorefrigerant conductivity.
Satti et al. [179]	Al2O3, CuO, ZnO, SiO2, TiO2/PG-Water (60:40)	0.1–0.5 vol.%	Increased up to ~40%	Showed that both nanoparticle concentration and temperature significantly influence thermal conductivity in mixed oxide nanofluids.
Rohit et al. [180]	Fe3O4/Paraffin	0.01–0.1 vol.%	Up to 20%	Thermal conductivity improved at low loading under ambient conditions, confirming feasibility in latent heat storage applications.
Yeganeh et al. [181]	Nanodiamonds/DI Water	0.8–3.0 vol.%	9.8% at 50 °C	Showed that nanodiamond-based nanofluids exhibit improved thermal conductivity at higher temperatures and concentrations.
Bhuiyan et al. [182]	Al2O3, TiO2, SiO2/Methanol	0.005–0.15 vol.%	Up to 29.41%	Evaluated and compared thermal conductivity across three types of nanoparticles; Al2O3 yielded the highest enhancement; developed empirical correlation.
Wei et al. [183]	AlN/Ethylene/Propylene Glycol	0.1 vol.%	38.71%/40.2%	Demonstrated that aluminum nitride (AlN) nanoparticles can enhance conductivity in glycol-based fluids by over 38%, proving its effectiveness as a thermally conductive filler.
Wei et al. [183]	AlN/Ethylene Glycol and Propylene Glycol	0.1 vol.%	38.71% (EG), 40.2% (PG)	Aluminum nitride nanoparticles significantly enhanced thermal conductivity in both ethylene and propylene glycol; shown to be effective at low concentrations.
Min-Sheng et al. [184]	MWNT/Synthetic Oil and EG	1–2 vol.%	12.4% (EG), 30% (oil)	MWNTs improved conductivity more in synthetic oil than in EG; effectiveness depended on both nanoparticle loading and base fluid.
Gandhi et al. [185]	Graphene/Various Fluids	0.01–0.2 vol.%	Up to 27%	Thermal conductivity increased nonlinearly with nanoparticle concentration, reaching a peak at 0.2 vol.%.
Wei et al. [186]	ZnO/Ethylene Glycol	5.0 vol.%	26.5%	Observed temperature-sensitive nonlinear increases in thermal conductivity; enhancement scaled with volume fraction.
Mahbubul et al. [187]	Al2O3/R141b	0.1–0.4 vol.%	1.003–1.013× base fluid	Thermal conductivity increased with both temperature and concentration, demonstrating enhanced performance under mild heating.
Ping et al. [188]	Al2O3/Water	Various	Not specified	Smaller particle size and higher temperature/weight fraction led to better conductivity performance in Al2O3 nanofluids.
Ruiqing et al. [189]	CuO/Water	Various	Efficiency ↑ 8.55% (spherical vs. rod)	Numerical study of GHE; optimal particle size (40 nm spherical); shape significantly influenced thermal performance.
Baojie et al. [191]	TiO2/Diathermic Oil	Various	Linear increase	Demonstrated linear thermal conductivity improvement with concentration; validated stability of oil-based nanofluids.
Chen et al. [192]	SiC/Saline Water	0.4 vol.%	>6%	Tested in solar distillation; conductivity improvements and optical properties confirmed suitability for thermal applications.
Xuan and Li [194]	Cu/Water	Various	Significant	Under turbulent flow in brass tube, observed strong enhancement in convective heat transfer with manageable frictional penalties.
Sharma, et al. [195]	Al2O3/Water	0.1 vol.%	23.7%	With twisted tape inserts, heat transfer improved notably; friction factor increased but remained within acceptable range.
Jung et al. [196]	Al2O3/Water	1.8 vol.%	Heat transfer coefficient increased by up to 32%	Demonstrated improved convective heat transfer in rectangular microchannels using Al2O3 nanofluids; well-dispersed particles enhanced heat transfer without significant increase in frictional losses, showing practical viability for microscale systems.

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Figure 2 further compares the top nanofluids—MWCNT/Oil, Graphene/EG, Cu/Water, Al₂O₃/Water, and MWCNT/Water—in terms of thermal conductivity enhancement, ground heat exchanger (GHE) usage, and adoption potential, highlighting how performance advantages interact with real-world feasibility.

According to Figure 2, MWCNT/Oil shows the highest thermal conductivity enhancement at 200.00%, as highlighted by Ying et al. [157], mainly because of the exceptional intrinsic conductivity of multi-walled carbon nanotubes and their stable dispersion in nonpolar oil-based fluids. However, it has no reported GHE applications, likely due to high cost, limited compatibility with aqueous systems, and challenges in large-scale preparation. Graphene/EG achieves a similarly high enhancement of 86.00%, which was demonstrated by Wei et al. [164], leveraging graphene’s excellent thermal transport properties but also showing no GHE deployment, with stability issues, elevated viscosity at effective concentrations, and the low heat capacity of ethylene glycol likely contributing to its limited use. In contrast, Al₂O₃/Water, with a more modest enhancement of 30.12%, reported by Ebata et al. [174], records the highest GHE usage, at 71.43% [94,110]. This broad adoption stems from its stability, low cost, chemical compatibility, and proven long-term performance in geothermal systems, making it a practical choice despite lower thermal conductivity than carbon-based nanofluids. Cu/Water offers a 28.57% improvement [94,110] with moderate GHE adoption, benefiting from copper’s high thermal conductivity but constrained by oxidation, stability concerns, and possible erosion of heat exchanger surfaces. MWCNT/Water, at 11.30% (Lee et al. [152]), remains mainly at the experimental stage for GHE use, with viscosity often increasing and offsetting conductivity gains in practice.

These comparative results highlight the tradeoffs between thermal conductivity enhancement and practical deployment in GHE systems. In summary, in geothermal applications, nanofluids with moderate conductivity gains but high stability and compatibility—such as Al₂O₃/Water—are presently the most viable for GHE deployment, while high-performance carbon-based nanofluids remain promising for future use pending advances in cost reduction and long-term stability.

3.2. Thermal Conductivity Performance Factors of Nanofluids

Extensive research shows that nanofluids can significantly enhance thermal conductivity compared to conventional fluids, but the magnitude of enhancement is strongly governed by several interrelated factors. However, the extent of this enhancement strongly depends on several key factors that govern heat transfer in these systems. Among the most influential are the intrinsic properties of the nanoparticles—including particle size, shape, and material—as well as the characteristics of the base fluid, operating temperature, and suspension stability. Additionally, the use of surfactants or dispersants, pH level (acidity or alkalinity), and clustering or agglomeration play important roles in determining thermal conductivity [59,152,197,198,199]. The combined influence of these parameters often determines whether a nanofluid performs exceptionally well in real-world conditions or fails to deliver its laboratory-measured potential. The thermal conductivity of nanofluids is influenced not only by temperature but also by the interdependent thermal and rheological properties of the base fluid and nanoparticles, as temperature variations affect Brownian motion, particle dispersion, and the likelihood of nanoparticle aggregation, all of which in turn impact heat transfer performance. Figure 3 illustrates these key factors influencing nanofluid thermal conductivity.

There are various types of particle materials used in nanofluid preparation, including metals, nonmetals, nitrides, metal carbides, and oxide ceramics. Additionally, nanomaterials such as single-walled or multi-walled carbon nanotubes are employed for their exceptionally high thermal conductivity. Common working fluids used as base fluids for preparing nanofluids in heat transfer applications include engine oil, biofluids, propylene glycol, ethylene glycol, and water. Beyond particle geometry, the type of base fluid also plays a decisive role, as it influences viscosity, dispersion quality, and overall heat transfer efficiency. The interplay between these factors ultimately determines the effectiveness of nanofluids in improving thermal conductivity and their suitability for practical applications such as geothermal heat exchangers, refrigeration systems, and microchannel cooling. The careful selection and matching of these particle and base fluid properties is critical, as compatibility can outweigh raw thermal conductivity gains when it comes to actual deployment in systems such as geothermal heat exchangers. Understanding and optimizing these parameters is essential for achieving efficient thermal management, energy savings, and long-term operational stability in engineering systems. A systematic approach—evaluating each factor both individually and in synergy—is needed to maximize performance gains while maintaining stability, cost-effectiveness, and manufacturability. For instance, Tun-Ping et al. [188] and Manna et al. [200] both reported that the thermal conductivity of alumina (Al₂O₃)/water nanofluids increased as the particle size decreased, emphasizing the importance of smaller, well-dispersed nanoparticles for better heat transfer performance. Similarly, Elena et al. [201] revealed that thermal conductivity in alumina-based nanofluids is substantially influenced by agglomeration behavior, particle geometry, and interfacial (Kapitza) resistance. Their findings revealed that elongated or dendritic structures improve conductivity more effectively than spherical ones and that reducing interfacial resistance is crucial for achieving optimal heat transfer performance.

Normally, two particle shapes are commonly considered in nanofluid research: spherical and cylindrical nanoparticles. Cylindrical nanoparticles typically exhibit a higher aspect ratio, which contributes to greater surface area and more efficient thermal pathways compared to spherical particles. Hua-qing et al. [202] were among the first to prepare nanosized SiC suspensions and measure their thermal conductivities using the transient hot-wire method while investigating the effect of nanoparticle shape (spherical vs. cylindrical) on the thermal conductivity enhancement of SiC nanofluids. Their results indicated that particle morphology—beyond just material type—plays a decisive role in conductivity performance. Yang et al. [203] conducted an experimental and theoretical study showing that nanofluids demonstrate significantly higher thermal conductivity and viscosity than base fluids, with both increasing as the nanoparticle volume fraction and temperature increase. Hua-qing et al. [202] and Yang et al. [203] highlighted the importance of nanoparticle shape in thermal conductivity enhancement, with cylindrical particles often yielding superior results. Wongwises and Somchai [74] investigated the thermal conductivity of nanofluids by dispersing TiO₂ nanoparticles in water at volume concentrations ranging from 0.2 to 2 vol.%. Their results showed that the measured thermal conductivity of the nanofluids increased with higher nanofluid temperatures.

Studies have shown that the concentration, particle size, and surface characteristics of nanoparticles in nanofluids, along with their interaction with dispersants, play a crucial role in determining suspension stability. Without proper stabilization, nanoparticles tend to agglomerate, leading to sedimentation and reduced thermal conductivity. To counteract this, several techniques are commonly employed, including mechanical agitation [23,204], pH adjustment of the suspension [205,206], and the use of surfactants [207,208], which improve particle dispersion and prevent coagulation, thereby maintaining long-term stability and enhancing heat transfer performance.

There are relatively few comprehensive studies investigating the influence of pH variations of the base fluid on nanofluid thermal conductivity behavior. For example, Huaqing et al. [209] studied the effect of pH on Al₂O₃/water nanofluid conductivity and observed that higher pH reduced the conductivity improvement. The results showed that thermal conductivity increased by 23% at pH 2 but declined to 19% at pH 11.5. Similarly, Karimian and Babalou [210] investigated the stabilization of Al₂O₃–CeO₂ bidispersed suspensions and reported that pH significantly affects nanoparticle dispersion stability, which in turn influences thermal conductivity. At pH 10, optimal dispersion was achieved, minimizing particle agglomeration and improving thermal conductivity, while deviation from this pH reduced stability and heat transfer effectiveness.

Donggeun et al. [211] experimentally analyzed how nanoparticle surface charge influences nanofluid conductivity. They concluded that pH significantly impacts thermal performance, with values further from the particles’ isoelectric point enhancing suspension stability and thereby improving thermal conductivity. Erzsébet and Etelka [206] further highlighted that pH-dependent adsorption of humic acid on magnetite nanoparticles alters their surface charge and aggregation behavior, with stable colloidal dispersions forming away from the isoelectric point, thereby preventing particle agglomeration and improving long-term suspension stability. Furthermore, Ji-Hwan et al. [169] found that pH levels influence nanofluid conductivity and the use of surfactants during the nanofluid preparation stage. Similarly, Dongsheng et al. [170] examined the role of pH in Al₂O₃–H₂O nanofluids and reported that it affects thermal conductivity. They found that both conductivity and stability improvements are highly dependent on pH levels and the concentration of SDBS (sodium dodecylbenzenesulfonate), a surfactant commonly used to improve nanoparticle dispersion. These findings underscore the importance of chemical conditioning and dispersion stability during synthesis, as poor suspension can significantly reduce thermal performance in practical systems.

Additives and surfactants are widely used to maintain nanoparticle suspension and prevent agglomeration, thereby contributing to the improvement of heat conductivity in nanofluids by enhancing particle dispersion, stability, and surface-level interaction between nanoparticles and the surrounding fluid. A series of experiments involving Cu in ethylene glycol, both with and without added surfactants, was conducted by Jeffrey et al. [147]. Further, Zhu et al. [212] investigated the application of sodium dodecyl benzene sulfonate (SDBS) as an additive and examined its effect on Cu–H₂O nanofluid conductivity. The findings indicated that conductivity enhancement was highly dependent on the SDBS concentration in the nano-suspensions.

Other nanomaterials, such as nanodiamonds, have also shown promise. Syam et al. [213] prepared nanodiamond–water nanofluids and investigated their thermal and physical characteristics, including conductivity and flow properties, to assess their suitability for thermal applications. They found that at 1.0 vol.% concentration, thermal conductivity rose by 12.7% at 25 °C and by 22.8% at 50 °C. This clearly demonstrates that higher temperatures further enhance the thermal conductivity of nanodiamond-based nanofluids, making them promising for advanced heat transfer systems.

Building on these approaches, Ghozatloo et al. [67] developed graphene-based nanofluids functionalized with alkali groups, synthesized via a CVD technique followed by a mild oxidation process involving potassium carboxylate. This chemical modification improved the hydrophilicity and dispersion stability of graphene in aqueous suspensions. They found that thermal conductivity rose by 14.1% at 25 °C and 17% at 50 °C with only 0.05 wt.% AFG, underscoring the role of nanoparticle functionalization, temperature, and low loading in enhancing heat transfer capabilities.

Interestingly, Suganthi et al. [214] showed that maximum thermal conductivity enhancement was achieved at the lowest temperatures but decreased as the temperature increased, ranging between 10 and 30 °C. This behavior was linked to the formation of a thicker molecular layer of ethylene glycol at lower temperatures, where the more ordered structure of the liquid molecules enhanced thermal conductivity relative to that of the bulk fluid. Beyond 30 to 60 °C, no further enhancement was observed. This was attributed to the increase in thermal conductivity resulting from enhanced Brownian motion of particles at higher temperatures, which was counteracted by a drop in conductivity due to the thinning of structured liquid layers. Shylaja et al. [215] reported that sand-based nanofluids dispersed in propylene glycol achieved a thermal conductivity enhancement of 46.2% at a concentration of 2 vol.% and a temperature of 10 °C, highlighting the significant potential of such nanofluids for low-temperature heat transfer applications.

Saidur et al. [197] conducted experimental research on the synthesis, hysteresis behavior, and flow resistance of Al₂O₃/water and TiO₂/water nanofluids, tested at concentrations ranging between 0.05 and 0.3 vol.% and temperatures between 25 and 80 °C. The thermal conductivity improved with increasing nanoparticle concentrations. Similarly, Angue et al. [216] emphasized that thermal conductivity is influenced by nanoparticle size and operating temperature, while Ravikanth and Debendra [217] confirmed that both the nanoparticle concentration and fluid temperature are critical determinants of thermal conductivity performance.

Furthermore, thermal conductivity is highly dependent on both the fluid medium and nanoparticle content, as shown by Min-Sheng et al. [184]. Das et al. [149] concluded that temperature and surface coatings notably influence nanofluid conductivity. Gayatri et al. [218] produced Al–5 wt.% Zn nanofluids through mechanical alloying and dispersed them in ethylene glycol at concentrations of 0.01 to 0.10 vol.%. Their experiments revealed that conductivity is strongly impacted by nanoparticle loading, particle dimensions, temperature, and nanoparticle–fluid interactions. The Al₅Zn_0.5 nanofluids reached a maximum enhancement of 16% at a loading of 0.10 vol.%. Manoj et al. [198] studied the heat transfer conductivity of Al₂Cu and Ag₂Al nanofluids dispersed in water and ethylene glycol. Their findings showed that nanofluid conductivity rose by 50–150% compared to pure fluids. The improvement in conductivity was strongly influenced by the composition, volume percentage, particle size, and thermophysical characteristics of the suspended nanoparticles. Madhusree and Dey [219] added Cu nanoparticles at 0.11–2% volume concentrations into gear oil using oleic acid as a surfactant. The study demonstrated that conductivity varied with temperature (10–80 °C) and nanoparticle loading, reaching up to 24% enhancement at 2 vol.% Cu nanoparticles at ambient temperature. Baogang et al. [220] studied the thermal conductivity of graphite/oil nanofluids produced using a ball milling technique. They found that conductivity improved by up to 36% with the addition of only 1.36 vol.% graphite into the oil. In this case, the improvement in thermal conductivity strongly depended on the graphite loading, increasing nonlinearly with higher concentrations, while showing only a weak dependence on temperature.

Moreover, Ravikanth and Debendra [217] analyzed the thermal conductivity of Al₂O₃, CuO, and ZnO nanofluids in a mixture of ethylene glycol and water at a 60:40 ratio. They used nanoparticle loadings up to 10% and tested temperatures ranging from 298 to 363 K. Their findings revealed that conductivity was influenced by both temperature and nanoparticle content, with higher values obtained at elevated temperatures and concentrations. Akhavan et al. [221] conducted experiments on CuO–oil nanofluids with 0.2–2 wt.% nanoparticles across various temperatures. They showed that conductivity improved with nanoparticle loading, reaching a maximum of 6.2% at 2 wt.%. Madhusree and Dey [222] explored the thermal conductivity of CuO–gear oil nanofluids, considering the roles of temperature and nanoparticle volume fraction. Thermal conductivity was measured between 5 °C and 80 °C. They reported improvements of 10.4% at 0.025 vol.% CuO at ambient temperature and 11.9% at 80 °C.

Zeinab et al. [223] evaluated the effects of the nanoparticle concentration and temperature on the thermal conductivity of GO/water nanofluids. They observed that with a nanosheet loading of 0.25 wt.%, conductivity rose by 33.9% at 20 °C and 47.5% at 40 °C, indicating a strong temperature dependence. Yolanda et al. [224] experimentally analyzed the thermal conductivity of NH₃–H₂O nanofluids with ammonia mass fractions between 10% and 50% at temperatures from 293.15 K to 313.15 K. Their results indicated that conductivity increased with temperature but decreased with higher ammonia levels, showing that fluid mixtures can vary significantly depending on component ratios and thermal conditions. Ultimately, the interplay between particle properties, fluid characteristics, operating temperature, and stabilization methods determines whether a nanofluid achieves laboratory-level conductivity gains in practical applications.

Particle clustering is an additional factor that significantly influences the heat transfer efficiency of nanofluids. When the nanoparticle concentration and exposure duration increase, nanofluids tend to aggregate, which reduces the available surface area for thermal exchange between particles, leading to a reduction in the fluid’s conductivity. For example, Phillbot et al. [225] and Yang et al. [226] performed extensive investigations on the effects of nanoparticle clustering, emphasizing that the formation, size, and spatial distribution of clusters can significantly alter thermal conductivity—either enhancing or reducing performance, depending on the clustering dynamics. Haitao et al. [227] tested Fe₃O₄/water nanofluids and found that both clustering and nanoparticle alignment played key roles in improving thermal conductivity by facilitating directed heat transfer mechanisms. Collectively, these findings highlight that composition, temperature, concentration, and particle morphology are fundamental parameters for optimizing the conductivity of nanofluids and multiphase fluids. A comprehensive summary of the key parameters affecting the thermal conductivity of nanofluids is presented in

Table 3. Summary of factors affecting the thermal conductivity of nanofluids.

Factor	Influence on Thermal Conductivity	Nanoparticle/Base Fluid	Conditions/Details	Researcher
Particle Size	Smaller particles (e.g., 20–50 nm) significantly enhance conductivity—up to 25–36% higher than larger particles (e.g., >70 nm) because of increased surface area and minimized thermal boundary resistance.	Al2O3/Water	Heat transfer improved from 0.62 to 0.84 W/m·K when particle size was reduced from 80 nm to 25 nm.	Tun-Ping et al. [188] and Manna et al. [200]
Particle Shape	High-aspect-ratio shapes such as rods and tubes (e.g., CNTs) increase thermal conductivity by 30–45% over spherical particles by facilitating percolation paths and continuous heat transport networks.	CNTs, Al2O3, SiC/Water	Thermal conductivity increased by 40% for MWCNTs vs. 22% for spherical Al2O3 at 1 vol.%	Elena et al. [201], Hua-qing et al. [202], Yang et al. [203]
Nanoparticle Material	Materials with high intrinsic conductivity (e.g., Cu and CNTs) can boost thermal conductivity by up to 200%, whereas metal oxides (e.g., ZnO and TiO2) offer moderate gains of 20–50%, depending on concentration and dispersion.	CNTs, Cu, Ag, ZnO, TiO2/Water, EG	0.5 vol.% CNTs → ~32% increase; 1 vol.% Cu → 48% increase; TiO2 at 3 vol.% → 26% increase	Huaqing et al. [209], Yang et al. [226] Haitao et al. [227]
Base Fluid Type	Water-based nanofluids typically exhibit 15–35% higher conductivity than those in EG or mineral oil due to better dispersion and lower viscosity.	Al2O3/Water, Oil, EG	Al2O3 in water: 1 vol.% → 22% gain; same in EG → 14% gain; in oil → <10% gain	Min-Sheng et al. [184], and Dongsheng et al. [170].
Temperature	Thermal conductivity increases with rising temperature owing to intensified Brownian motion—e.g., 15–40% improvement from 25 °C to 60 °C at 1 vol.% nanoparticle concentration.	Al2O3, CuO/Water, EG	Al2O3 (1 vol.%) → increased from 0.6 to 0.83 W/m·K (25 °C to 60 °C); CuO nanofluids show similar trends	Saidur et al. [197], Syam et al. [213], Suganthi et al. [214].
Volume Concentration	Thermal conductivity improves significantly with volume concentration up to 4–5 vol.%, beyond which agglomeration occurs; e.g., 2 vol.% CuO → ~48% enhancement; 5 vol.% Al2O3 → ~30% increase; above 6 vol.% → decline or plateau observed.	Al2O3, CuO, ZnO, GO/Water, EG	3 vol.% ZnO: ~41% gain; 6 vol.% GO → saturation; >7 vol.% → sedimentation	Manoj et al. [198], Zeinab et al. [223], Huaqing et al. [209]
Surfactants/Additives	Proper surfactants improve dispersion and conductivity by 10–25%; e.g., 0.2 wt.% SDBS in Cu–water nanofluid increased conductivity by 20%. Excessive surfactant (e.g., >0.4 wt.% ) may cause foaming or insulating barriers.	Cu/Water/SDBS, ZnO–EG/SDS	SDS improved ZnO–EG dispersion by 18%; SDBS also reduced aggregation in Cu nanofluids	Jeffrey et al. [147], Zhu et al. [212], Ghozatloo et al. [67]
pH Level	pH tuning (optimal range: 4–6) stabilizes particle dispersion via electrostatic repulsion, enhancing conductivity by 10–15%; extreme pH (<2 or >10) causes aggregation and conductivity loss.	Al2O3/Water	pH 4.5 → 14% increase; pH > 10 → sedimentation and 10% reduction in conductivity	Huaqing et al. [209], Ji-Hwan et al. [169], Dongsheng et al. [170], Erzsébet and Etelka [206], Karimian and Babaluo [210], and Donggeun et al. [211].
Clustering/Agglomeration	Light clustering forms thermal bridges that may slightly enhance conductivity; however, excessive clustering reduces it by 10–25% by decreasing the effective heat transfer surface and promoting sedimentation.	Fe3O4/Water, Al2O3/Water	Fe3O4 at 3 vol.% → peak gain; further increase → clustering → 18% drop in conductivity	Phillbot et al. [225], Yang et al. [226], Haitao et al. [227].
Synergistic Effects	Combining optimal shape, concentration, surfactant, and temperature can yield 50–150% improvement in conductivity depending on system design.	Al2Cu, Graphite/Oil, CuO/Oil	Al2Cu at 1 vol.% + SDS at 60 °C → up to 120% increase in conductivity over base oil	Madhusree and Dey [219]. Baogang et al. [220], Akhavan et al. [221].

. Figure 4 complements this by summarizing the relative contribution of each factor to thermal conductivity enhancement, providing a visual comparison that highlights the most influential parameters.

Figure 4 highlights that the most dominant factor driving enhancements in nanofluid thermal conductivity is the combined or synergistic interaction of multiple parameters (~41.5%), indicating that thermal performance is often the result of complex interdependent effects rather than a single variable. This is followed in importance by the intrinsic nanoparticle material (~36.4%), which governs thermal pathways due to its conductivity properties, and the particle volume concentration (~33.1%), which dictates the density of heat-conducting channels within the fluid. The particle size (~31%) and particle shape (~25.4%) also provide significant contributions, as smaller and more optimized geometries increase the surface area for energy transport. In contrast, operational parameters such as temperature (~21%), surfactants/additives (~18.6%), and pH level (~23%) exert only moderate effects, primarily influencing stability and dispersion. The least favorable influence is attributed to clustering or agglomeration (10.2%), which at high levels reduces the effective heat transfer surface, promotes sedimentation, and consequently diminishes overall conductivity [188,198,199,200,201,202,203,209,213,214,215,223,224,225,226,227].

In summary, in nanofluid thermal conductivity enhancement, synergistic optimization of multiple factors yields the largest performance gains, while particle clustering/agglomeration remains the most detrimental influence, underscoring the importance of maintaining dispersion stability for real-world applications.

4. Influence of Fluid Velocity on Ground Heat Exchanger Performance

Building upon the thermal characteristics of nanofluids discussed in the previous sections, particularly their enhanced thermal conductivity and convective heat transfer performance—it becomes crucial to consider how operational parameters, such as fluid velocity, affect system performance. While nanofluids offer improved thermophysical characteristics, their full benefit is realized only under optimal flow conditions within the ground heat exchanger (GHE). Therefore, this section examines how variations in fluid velocity influence heat transfer effectiveness, pressure losses, and the thermal response of GHE systems in geothermal heat pump (GHP) applications, as well as identifies optimal velocity ranges for different GHE configurations.

In geothermal heat pump systems, the working fluid circulates through the GHE, transporting thermal energy from the heat pump to the ground during heating and cooling cycles. Its flow behavior—particularly velocity—directly affects thermal performance. For efficient operation, the heat transfer fluid should have high thermal conductivity, adequate heat capacity, and reduced viscosity, as these properties influence both energy exchange rates and hydraulic performance. One of the most significant factors in this context is convective resistance to heat transfer, which occurs within the circulating fluid in the U-tube and surrounding ground. Higher velocities generally enhance convective heat transfer by lowering this thermal resistance, thereby boosting the overall heat exchange efficiency of the system [13,26]. However, excessive velocity can lead to increased pressure drop and higher pumping power requirements, potentially reducing system efficiency and lifespan.

Experimental studies have shown that velocity has a critical influence on GHE thermal behavior. For instance, Zhou et al. [17] conducted a detailed investigation into the effect of fluid velocity on the heat transfer performance of vertical GHEs configured as single U-tube (32 mm), double U-tube (25 mm), and double U-tube (32 mm) systems. Their findings indicated optimal fluid velocity ranges of 0.4–0.6 m/s for single U-32, 0.4–0.5 m/s for double U-25, and 0.3–0.4 m/s for double U-32, with recommended borehole depths of 80–100 m and 90–110 m for double U-25 and double U-32, respectively—ensuring efficient thermal performance without excessive pressure loss. Building on these results, Li et al. [228] recommended maintaining a water flow velocity range of 0.4–0.7 m/s in single U-tube configurations to achieve optimal thermal efficiency. Furthermore, Salhein [1] investigated the effect of varying water velocities in single vertical GHEs with an outer diameter of 32 mm at depths of 50 m and 20 m. The author recommended an optimal velocity range of 0.28–0.38 m/s for the 50 m depth, and 0.17–0.22 m/s for the 20 m depth. Zhou et al. [17] numerically analyzed the relationship between water velocity and pressure loss in a vertical single-U tube with a 100 m depth and 25 mm diameter. Their simulation showed that pressure loss increases steadily with flow velocity, and a sharp rise occurs beyond 0.8 m/s. Below this threshold, every 0.2 m/s increase in velocity caused an average pressure rise of 26.7 kPa, while above it, the increase nearly doubled to 48.7 kPa—suggesting that fluid velocity should remain under 0.8 m/s when prioritizing pressure loss reduction.

Additionally, Zhou et al. [17] also analyzed pressure loss in a 25 mm single-U tube (100 m depth) and found a steady increase with velocity, followed by a sharp rise beyond 0.8 m/s. Below this threshold, a 0.2 m/s increase caused an average rise of 26.7 kPa, while above it, the increase nearly doubled to 48.7 kPa. Below this point, pumping penalties were moderate; beyond it, the efficiency of the tradeoff became significant. Miyara et al. [229] confirmed that although a higher velocity reduces the residence time, the net heat transfer rate can still increase due to higher flow rates. Salhein et al. [1,7,16] reported that in vertical single U-tubes (98 m depth), optimal flow velocities were 0.33–0.43 m/s for 25 mm, 0.35–0.45 m/s for 32 mm, and 0.38–0.48 m/s for 40 mm. With increasing pipe length, the circulating flow velocity generally rises due to changes in hydraulic dynamics and thermal gradients, as shown in Figure 5.

Figure 5 illustrates the correlation between geothermal pipe length and circulating water velocity in a vertical ground heat exchanger system. As the pipe length increases from 20 m to 100 m, the water velocity shows a steady upward trend, rising from approximately 0.19 m/s to 0.4 m/s. This nonlinear growth is modeled using a polynomial regression equation:

$$y=-4\times {10}^{-5}{x}^2+0.0072x+0.0662$$

(1)

where $y$ is the water velocity $(\mathrm{m}/\mathrm{s})$, and $x$ is the geothermal pipe length $\left(\mathrm{m}\right)$. The curve highlights that while increasing pipe length initially results in significant velocity gains, the rate of increase gradually diminishes, indicating a saturation behavior at longer lengths. This highlights the importance of understanding this relationship to optimize fluid velocity control, thereby enhancing heat transfer efficiency and system performance.

Han and Yu [230] conducted a steady-state analysis to evaluate the influence of fluid velocity and borehole depth on the thermal performance of vertical GHEs. Their simulation results indicated that total extracted heat increased with both higher fluid velocity and greater GHE depth. However, once the flow velocity exceeded a critical value—approximately 0.3 m/s for a 30 m deep borehole—the thermal output plateaued, with minimal gains observed from further velocity increases. They concluded that the optimal circulation speed lies around 0.3–0.4 m/s. Beyond this flow level, further gains in thermal performance are mainly influenced by GHE depth rather than by increasing fluid velocity. Similarly, Benamar et al. [231] analyzed how varying water velocities affect the heat transfer performance in vertical U-tube systems using a 32 mm pipe diameter. They identified the optimal velocity range for maximizing thermal performance to be between 0.3 and 0.4 m/s. Paolo Maria et al. [232] carried out simulations on horizontal ground heat exchangers using CFD and found that increasing the flow velocity from 0.25 to 1 m/s significantly improved thermal performance across linear, helical, and slinky configurations. The results emphasized fluid velocity as a key factor in enhancing heat exchange efficiency. Ranjeet et al. [233] analyzed how fluid velocity influences the average thermal energy transfer to the ground across various ground heat exchanger (GHE) configurations, including linear, helical, and slinky geometries. Their results demonstrated that increasing inlet velocity from 0.25 m/s up to 1 m/s significantly enhanced heat exchange for the helical and slinky types—by 46% and 32%, respectively—due to their greater surface area exposure. However, the linear GHE showed minimal improvement, suggesting that the geometry plays a critical role in determining how effectively increased velocity translates to improved thermal performance.

Alessandro and Rajandrea [234] demonstrated that adjusting the flow velocity of water can effectively lower the thermal resistance of the borehole, thereby improving the heat transfer process between the water in the GHE pipe and the surrounding ground. You et al. [235] examined the effect of circulating water velocity on the performance of heat exchangers using three flow rates, 0.26 m/s, 0.51 m/s, and 1.02 m/s, while maintaining a constant inlet water temperature of 35 °C. They reported heat exchange rates of 84 W/m, 116 W/m, and 94 W/m, respectively. The highest performance was observed at 0.51 m/s; however, further increasing the velocity to 1.02 m/s led to reduced heat exchanger efficiency. This confirms that optimal thermal efficiency occurs within the 0.5–0.6 m/s velocity window, beyond which system performance declines. Moreover, Li et al. [236] examined the influence of fluid velocity on the heat transfer efficiency of vertical U-tube ground heat exchangers using coupled fluid–structure simulations. When the fluid velocity was raised from 0.4 m/s up to 1.0 m/s, the heat transfer rate per unit depth increased by 123.34%. Kong et al. [237] investigated how inlet velocity affects heat transfer in GHEs with smooth and petal-shaped U-tubes. They observed that raising the flow velocity from 0.2 m/s to 1.2 m/s increased the heat exchange rate by 43%. However, while petal designs increased turbulence, they also caused higher pressure losses, making smooth U-tubes more effective for enhancing heat exchange through velocity optimization. Wang et al. [238] evaluated the influence of fluid velocity on the thermal performance of deep borehole heat exchangers (DBHEs) at around 2000 m using a numerical model. Their analysis, spanning a wide velocity range of 0.04–1.3 m/s, revealed that the most effective heat transfer and maximum outlet temperatures occurred when the fluid velocity ranged between 0.3 and 0.7 m/s. Additional numerical investigations evaluated flow velocities ranging from 0.2 to 1.4 m/s, with Reynolds numbers spanning 3000 to 45,000 under seasonal conditions. These simulations revealed a nonlinear relationship between velocity and pressure loss. In a representative case involving a single U-tube (25 mm diameter, 100 m depth), pressure loss increased steadily with velocity. Below 0.8 m/s, each 0.2 m/s increment led to an average rise of 26.7 kPa. However, beyond 0.8 m/s, the pressure loss nearly doubled—averaging 48.7 kPa per 0.2 m/s increment—highlighting the sharp escalation in hydraulic resistance at higher velocities. This indicates that maintaining flow speeds below 0.8 m/s is advisable when seeking to minimize pumping energy and operational stress on the system [17]. A lower inlet velocity results in greater temperature differences between the U-pipes (central heat exchanger), indicating that higher flow velocity reduces thermal interference (Yong et al. [228] and Xiao-Yan et al. [239]). As velocity increases, the overall thermal resistance of the ground heat exchanger (GHE) partially decreases (Liu et al. [240]). However, this comes with a tradeoff—increasing fluid velocity raises the pressure loss between the inlet and outlet pipes. Specifically, at flow velocities exceeding 0.8 m/s, the pressure drop becomes significantly higher. Therefore, moderate velocities are preferred (Zhou et al. [17]), as indefinitely increasing velocity is impractical due to escalating pressure loss and excessive pump power consumption. To achieve fully developed turbulent flow, the Reynolds number should exceed 10,000 (Re > 10,000), which substantially improves convective heat transfer (Liu et al. [240]). Nevertheless, once turbulent flow is established, further increases in velocity offer diminishing returns compared to laminar-to-turbulent transition gains (Yong et al. [228]). Therefore, extreme increases in flow rate are not recommended, as the velocity should be kept moderate—neither too low nor too high—to optimize heat transfer while minimizing energy consumption and hydraulic penalties.

Furthermore, Zhou et al. [241] compared steel and PE U-tube pipes across inlet velocities ranging from 0.2 m/s to 0.8 m/s and found that steel pipes delivered 14–20% higher thermal performance and exhibited up to 7% lower thermal resistance. They also reported that heat transfer per unit borehole depth (QL) increased significantly with velocity, with the PE pipe’s QL rising by 86% as velocity increased from 0.2 m/s to 0.8 m/s, reinforcing the beneficial effect of velocity on GHE efficiency. In addition, Akio et al. [229] carried out experimental research on the thermal behavior of various GHE configurations—double-tube, U-tube, and multi-tube systems installed in steel pile foundations under actual cooling-mode operation. Among these, the double-tube design showed the highest rate of heat exchange. For example, at a flow rate of 4 L/min sustained over 24 h, the mean heat exchange rates were 49.6 W/m for the double-tube, 34.8 W/m for the multi-tube, and 30.4 W/m for the U-tube. When the flow rate was raised from 2 to 4 L/min, thermal performance improved considerably; however, further increases to 8 L/min yielded only marginal improvements. These findings indicated that the optimal flow rate range lies between 4 and 6 L/min, beyond which thermal improvements become negligible. Yuanlong and Jie [242] investigated how fluid velocity affects both the heat exchange rate and outlet fluid temperature in a 32 mm U-tube system using a three-dimensional transient heat transfer model. They evaluated flow rates ranging from 0.1 m³/h to 1.2 m³/h and found that the outlet temperature initially increased, reaching a peak at around 0.7 m³/h, but declined as flow rates exceeded this value. An optimal velocity range of 0.57–0.76 m³/h (approximately 0.3–0.4 m/s) was recommended for achieving maximum thermal efficiency. Li et al. [243] conducted a computational investigation of the transient heat transfer characteristics of a vertical double U-tube borehole heat exchanger (BHE), analyzing the combined effects of inlet velocity, temperature, and operation time on soil temperature distribution. Their results indicated that increasing the charging temperature had a greater influence than flow velocity, and the heat transfer rate difference was more pronounced between 0.1 and 0.3 m/s than between 0.3 and 0.5 m/s. Consequently, an ideal flow velocity of about 0.3 m/s was recommended. Additionally, charging time was found to have the strongest impact on the radial heat transfer zone, offering valuable guidance for BHE design and borehole thermal energy storage applications.

Furthermore, Salhein et al. [1,7,16] analyzed the heat exchange behavior involving water circulation through vertical underground pipes and the adjacent soil using a heat transfer mathematical model, with a particular focus on the impact of water velocity on GHE performance. Their analysis showed that when the water velocity slowed sufficiently, the outlet temperature of the GHE gradually aligned with the ground temperature, indicating a more complete thermal exchange. Figure 6, Figure 7, Figure 8, Figure 9, Figure 10 and Figure 11 show temperature profiles at various velocities and depths under both heating and cooling modes. At lower velocities, the water temperature approaches the ground temperature before exiting the pipe, indicating sufficient residence time. At higher velocities, thermal equilibrium is not reached, confirming incomplete exchange.

Figure 6 illustrates the water temperature behavior in a single vertical U-tube pipe during heating mode at a depth of 98 m. The water temperature increased exponentially along the pipe, starting from the inlet and rising toward the ground temperature. At flow velocities of 0.35 m/s and 0.45 m/s, the fluid temperature approached the ground temperature at approximately 91 m and 96 m, respectively. This indicates that sufficient residence time at lower velocities allows the water to absorb enough heat from the surrounding soil. In contrast, at higher velocities of 0.9 m/s and 1.2 m/s, the water did not reach the ground temperature even at the pipe exit, indicating incomplete heat exchange and increased energy demand due to higher pumping power. Figure 7 shows the water temperature behavior under the cooling mode at the same depth of 98 m. The water temperature decreased exponentially, starting at a higher inlet temperature and approaching the ground temperature as it flowed downward. When the water velocity was 0.35 m/s or 0.45 m/s, thermal equilibrium with the surrounding ground was nearly achieved by the pipe outlet. However, for velocities of 0.9 m/s and 1.2 m/s, the water exited the pipe without reaching the ground temperature, confirming insufficient thermal contact time at higher flow speeds.

Figure 8 illustrates the water temperature behavior in a vertical U-tube pipe during the heating mode at a depth of 50 m. The water temperature increased exponentially from an inlet temperature of 8 °C toward the ground temperature of 18.5 °C near the pipe exit at flow velocities of 0.28 m/s and 0.38 m/s. However, at higher velocities of 0.7 m/s and 1 m/s, the outlet water did not fully match the ground temperature, as the water exited the pipe too quickly, limiting heat exchange with the surrounding soil. Figure 9 shows the temperature profile under cooling mode for the same 50 m depth. The water temperature decreased exponentially from an initial value of 26 °C, approaching the ground temperature of 18.5 °C at the outlet when flowing at 0.28 m/s or 0.38 m/s. In contrast, higher flow velocities of 0.7 m/s and 1 m/s prevented complete thermal equilibrium, since the water passed through the pipe before fully exchanging heat with the ground.

Figure 10 illustrates the water temperature behavior in a vertical U-tube at 20 m depth within a geothermal heat pump system (GHPS). The water temperature rises steadily from the inlet along the pipe, reaching the ground temperature at about 18.5 m and 20 m when the applied velocities were 0.17 m/s and 0.22 m/s, respectively. In this case, since the ground is warmer than the inlet water, thermal energy is transferred from the soil into the water, making it available for use in the system. At higher velocities of 0.4 m/s and 0.6 m/s, however, the outlet water failed to reach the ground temperature, indicating insufficient residence time for full heat transfer. Figure 11 shows the cooling mode profile at the same 20 m depth. Here, the water temperature is initially above the surrounding ground, causing heat to flow from the water to the soil. As the water moves along the pipe, its temperature gradually decreases, approaching the ground temperature of 22.1 °C near 18.5 m and 20 m when the flow was 0.17 m/s and 0.22 m/s. At higher velocities of 0.4 m/s and 0.6 m/s, the outlet water temperature stayed above the ground temperature, confirming incomplete heat exchange due to an insufficient contact time.

According to the findings of these studies, the water velocity should fall within an optimal range—neither too high nor too low—to ensure efficient heat transfer and achieve the desired outlet temperature. If the water velocity is excessively high, it consumes more pumping energy, and the temperature difference between the inlet and outlet decreases, reducing the effectiveness of heat exchange. Conversely, if the water velocity is too low, the outlet water reaches the ground temperature too quickly, leaving a significant portion of the loop underutilized. Therefore, the velocity should be managed so that the outlet water temperature aligns with the ground temperature, ensuring full utilization of the loop.

Table 4. Recommended water velocity ranges for various GHE configurations.

Researchers	GHE Configuration	Borehole Depth (m)	Pipe Diameter (mm)	Recommended Flow Velocity (m/s)
Hong et al. [17]	Single U-tube arrangement	80–110	32, 25	0.3–0.6
Li et al. [228]	Single U-tube arrangement	—	—	0.4–0.7
Zhou et al. [17]	Single U-tube arrangement	100	25	≤0.8 (pressure loss increases sharply above this limit)
Salhein [1]	Single U-tube arrangement	50, 20	32	0.28–0.38 (50 m); 0.17–0.22 (20 m)
Salhein et al. [1,7,16]	Single U-tube arrangement	98	25, 32, 40	0.33–0.43 (25 mm); 0.35–0.45 (32 mm); 0.38–0.48 (40 mm)
Han and Yu [230]	Single U-tube arrangement	30	—	0.3–0.4
Benamar et al. [231]	Single U-tube arrangement	—	32	0.3–0.4
You et al. [235]	Single U-tube arrangement	—	—	0.5–0.6
Li et al. [236]	Single U-tube arrangement	—	—	0.4–1.0
Wang et al. [238]	Deep Borehole Heat Exchanger	2000	—	0.3–0.7
Akio et al. [229]	Double-tube	—	—	4–6 L/min (~0.34–0.51 m/s)
Yuanlong and Jie [242]	Single U-tube arrangement	—	32	0.57–0.76 m3/h (~0.3–0.4 m/s)
Li et al. [243]	Double U-tube arrangement	—	—	0.3
Paolo Maria et al. [232]	Horizontal GHE	—	—	Significant gains from 0.25 to 1 m/s; optimal depends on geometry
Ranjeet et al. [233]	Single U-tube arrangement	—	—	Helical: +46% heat transfer from 0.25 to 1 m/s; slinky: +32%; inear: minimal improvement
Kong et al. [237].	Single U-tube arrangement	—	—	0.2–1.2 m/s; smooth U-tubes preferred for lower pressure loss

summarizes recommended velocity ranges for different GHE configurations, diameters, and depths.

5. Conclusions

We conducted an extensive review of heat transfer fluids (HTFs) and their influence on ground heat exchanger (GHE) performance in geothermal heat-pump systems (GHPSs), integrating analyses of fluid classification, thermophysical behavior, nanofluid enhancement approaches, and operational optimization methods. From this work, we highlighted the following conclusions:

• Scope and baseline HTFs. Conventional HTFs (water and water–glycol mixtures) were widely used but constrained by low thermal conductivity, freezing risk (necessitating antifreeze), and higher pumping energy due to increased viscosity—tradeoffs that motivated the search for enhanced fluids.
• Performance trends. Carbon-based nanofluids (e.g., MWCNT/Oil ~200%, Graphene/EG ~86%) exhibited the largest thermal-conductivity gains but saw limited GHE use due to cost, stability, and compatibility constraints. In contrast, Al₂O₃/Water (~30%) had the highest field adoption (~71.43%) because it balanced enhancement with stability, chemical compatibility, and cost.
• Dominant influencing factors. Synergistic optimization of multiple parameters (~41.5%) delivered the greatest gains, followed by nanoparticle material (~36.4%) and concentration (~33.1%). Particle size (~31%) and shape (~25.4%) also mattered, whereas clustering/agglomeration (~10.2%) was most detrimental because it reduced the effective heat-transfer area and promoted sedimentation.
• Dispersion stability. Sustained gains depended on stable, well-dispersed suspensions (appropriate functionalization, surfactants, and pH control) to prevent agglomeration and viscosity penalties.
• GHE operational optimization. Water velocity was a primary control knob: maintaining moderate flows (~0.3–0.7 m/s for single U-tubes) typically maximized convective benefit while limiting pressure drop and pump power. Geometry, borehole depth, and pipe diameter needed to be matched to fluid properties and the selected velocity range for long-term efficiency.
• Integration pathway. Combining optimized nanofluid formulation (composition, stability, and concentration) with engineered operating conditions (flow velocity and exchanger geometry) provided a robust route to higher geothermal system efficiency.
• Future directions. Priorities included hybrid nanofluid development, real-time monitoring of dispersion stability, and adaptive velocity control to sustain performance under seasonal and load variations.