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Although bistable vibration energy harvesters offer promising broadband characteristics, their efficiency is often hindered by fixed potential barriers that confine the system to small-amplitude intra-well motion. The core innovation of this work is the proposal of a synchronous potential barrier regulation mechanism for multiple subsystems based on a rhombus linkage mechanism. This study introduces a novel multi-subsystem bistable vibration energy harvester (MBEH) integrated with a rhombus linkage mechanism to achieve tunable potential barriers. The mechanism facilitates the coupling of four bistable subsystems, where adjusting the magnet spacing of one subsystem allows for the synchronous regulation of magnetic gaps in others. This architecture ensures a continuous and precise optimization of the potential barrier. Consequently, this mechanism yields remarkable performance advancements, achieving highly efficient coupling among subsystems. Furthermore, potential barrier regulation efficiency is substantially increased, while operating bandwidths of subsystems are complementary and superimposed. Results from numerical investigations indicate that at an excitation acceleration of 0.6 g, MBEH outperforms conventional BEH with a 13.58 Hz increase in summed subsystem bandwidth and a 0.0223 μW gain in output power. The findings validate the efficacy of the proposed MBEH as a high-performance solution for robust broadband vibration energy harvesting. Full article

Fractional derivatives introduce an effective mathematical structure to describe memory effects, long-range interactions, and anomalous transport processes that are not well represented by the traditional integer-order models. This paper presents the unidirectional fractional longitudinal wave equation as a governing equation where a model is proposed to explain the steady wave propagation of solitary waves in a magneto-electro-elastic circular rod. Magneto-electro-elastic substances are a groundbreaking category of advanced functional materials with tremendous nanotechnology and biomedical engineering prospects because of their effective multi-field energy conversion and temperature responsiveness. In order to solve this complicated fractional nonlinear equation, we introduce a new computation-analysis approach: the Riccati subequation neural network method. This hybrid solution is a synergistic combination of an analytical solution structure and a neural network structure consisting of input, hidden, and output layers, with interconnection between neurons through weighted connections and activation functions. It is important to note that every neuron in the first hidden layer is coupled to the solutions of the Riccati equation, and this allows the systematic use of the new trial functions. With the suggested method, analytical solutions are obtained for the spacetime fractional partial differential equations of the unidirectional fractional longitudinal wave equation in the exact form of trigonometric, hyperbolic, and rational functions. This paper is the first attempt to combine the Riccati subequation method with a neural network model, which has given rise to new types of solitary wave solutions. The three-dimensional, two-dimensional, and contour plots are used to visualize the dynamic nature of these solutions and to display the rich nonlinear wave behavior. The effectiveness and the robustness of the implemented technique is not only proven through our findings but also provides more profound information about the nonlinear wave phenomena in the advanced multifunctional materials, which can inform future developments in energy harvesting and the design of biomedical devices. Full article

The increasing importance of photovoltaic (PV) systems in the context of the energy transition, together with the need to improve their efficiency, has driven the adoption and development of intelligent and advanced maximum power point tracking (MPPT) techniques. Among these approaches, the Particle Swarm Optimization (PSO) algorithm stands out due to its simplicity, ease of implementation, low number of control parameters, robustness, and fast convergence capability, making it widely applied in modern MPPT systems. However, the performance of PSO in MPPT applications depends on the appropriate selection of both algorithm control parameters and implementation/configurations parameters. The control parameters include the cognitive (C₁) and social (C₂) learning factors, as well as the inertia factor (w), which directly influence swarm dynamics and the balance between exploration and exploitation mechanisms, that is, between global and local search. On the other hand, configuration parameters such as the number of particles and the initialization strategy affect the initial population diversity, the convergence speed toward the maximum power point, and the computational cost of the algorithm, defining the trade-off between speed and accuracy. Despite the extensive research in this field, there is still no clear consensus regarding the most suitable PSO parameter configuration for MPPT applications. This paper presents a statistical analysis of PSO parameter selection in MPPT applications, identifying the most frequently adopted parameter configurations and trends reported in the literature. The findings provide useful guidelines for researchers to select the PSO parameters according to different operating conditions, particularly under partial shading and irradiance variations. From a sustainability perspective, improving MPPT performance contributes to maximizing PV energy harvesting, reducing energy losses, and enhancing the reliability of PV systems, thereby supporting the transition toward more sustainable energy generation. Full article

A livestock farm in southern Taiwan produces wastewater with high concentrations of nitrogen and organics, which inhibit anaerobic methanogens and limit the efficiency of its biogas system. To enhance energy recovery, this study developed a liter-scale microbial fuel cell (MFC) system aimed at harvesting electricity from livestock wastewater, serving as a supplementary energy recovery pathway alongside the biogas process. According to the five analyses, the chemical oxygen demand (COD) of raw wastewater ranged from 14 to 21 g L⁻¹, with acetate concentrations ranging between 40 and 112 mM. Propionate and butyrate were consistently below 32 mM and 18 mM, respectively. Ammonium ranged from 1.1 to 1.7 g-N L⁻¹, indicating the wastewater’s high organic load and elevated nitrogen content. Two liter-scale MFCs, ch5 and ch7, were operated for over 70 d. From days 7 to 28, both MFCs employed a fill-and-draw mode, achieving optimal COD removal exceeding 80%. After resolving leakage issues between days 30 and 40, the system was restarted on day 40, yielding 76% (ch5) and 82% (ch7) of COD removal. Continuous operation began on day 59, and both reactors maintained COD removal rates above 80% for most of the subsequent two-week period. The best power outputs for ch5 and ch7 reached 1.11 and 0.82 W m⁻³, respectively. Although both liter-scale reactors achieved COD removal and measurable power output, the most important finding was obtained from the inoculum comparison experiments. After 54 days of acclimating to raw wastewater solids, no significant current was observed. In contrast, digestate solids acclimated with carbon powder for 22 d produced a peak current of 42.5 A m⁻³ at 147 h, with COD removal rates of 67–73% and complete removal of organic acids. The key conclusion of this study is that anaerobic digestate exhibits electroactive microbial potential, whether operated in liter-scale reactors or acclimated with carbon powder. Further investigation into the microbial community structure is warranted to optimize system performance. Full article

This paper presents a numerical investigation into a prototype energy harvesting system utilizing airflow around a bluff-body. The system consists of a flexible cantilever beam in a flag configuration with bonded piezoelectric transducers, integrated with a nonlinear triple-well potential established by auxiliary elastic elements. Three distinct bluff-body geometries—triangular, square, and semi-circular—with characteristic heights of 20 mm and 30 mm were analyzed. Aerodynamic excitation parameters were identified using CFD simulations, comparing exact and simplified mathematical representations of the lift force. The system’s dynamical response was evaluated through bifurcation diagrams, Diagrams of Coexisting Solutions (DS), and 3D Poincaré sections for zero and variable initial conditions. The results indicate that the triangular cross-section provides the widest frequency band for high-amplitude inter-well oscillations, maximizing energy harvesting effectiveness. A key innovation of this study is the demonstration that the simplified excitation model provides sufficient accuracy for rapid engineering design while significantly reducing computational overhead. Furthermore, it highlights the practical applicability of a flag-type system integrated with flexible elements to stabilize the beam’s free end. Full article

This paper presents the design of a batteryless near-field communication (NFC) multi-sensor node with an integrated adaptive power-management system for sensing applications. The work focuses on harvesting energy from a 13.56 MHz NFC field to power an ultra-low power sensing platform. The design consists of the TI RF430FRL152H, an integrated NFC transponder with an embedded MSP430 microcontroller core and ferroelectric random-access memory (FRAM) non-volatile memory. The system combines an ISO/IEC 15693 NFC front end, a tuned loop antenna for optimized power harvesting, and multiple analog and digital sensor interfaces, and a firmware architecture for intermittent harvested energy operation. The aforementioned design performs on-demand data acquisition, logs measurements in the FRAM, and communicates the measured results through an ISO15693 compliant NFC link while powered entirely by the reader’s radio-frequency (RF) field. Since NFC provides only limited harvested power, efficient energy management is critical. The proposed scheme continuously monitors the storage capacitor voltage and activates each sensor only when sufficient energy is available. After every measurement, the system reassesses the stored charge before triggering the next acquisition, ensuring stable multi-sensor operation. A BMP390 temperature and pressure sensor and the on-chip temperature sensor demonstrate the platform’s capability. Experimental results show that the system harvests 1.064 mW (1.85 V, 560 µA), achieves a wireless operating range of up to 40 mm, and delivers a response time of 800 ms, demonstrating its suitability for low-power temperature and pressure sensing applications. Full article

Digital twins are becoming increasingly popular in the built environment, with building users asking for greater levels of data and digitisation, and the volume of research in the field growing. There remains a question as to whether the costs of digital twins are worth the benefits they provide, both in terms of the financial cost and the environmental cost of transferring, storing, analysing, and processing a consistently growing amount of data to feed digital twins. This paper provides a literature review of studies that assess the costs and benefits of digital twins. It considers the value of digital twins and how this value is generated. This review includes an analysis of the different definitions for digital twins given in the literature, the countries of authorship, and categories of sources within the relevant literature. The analysis of digital twin definitions showed that the use of the term varied depending on the application being considered. An assessment of the data harvested and associated benefits showed that environmental conditions, especially temperature, and occupancy data were the most harvested data types in the studies considered. It was found that there is potential for digital twins to provide benefits beyond their costs if used in the correct application. However, the studies relied on simulations to quantify benefits and did not quantify the costs of live data streams in digital twins, which highlights a research gap. For the studies analysed, implementations focusing on occupancy data to provide demand-led services, machine learning to optimise equipment setpoints, and data for predictive maintenance show the greatest potential for cost and energy savings. Full article

It is widely recognized that grain variability affects the physical and engineering properties of cowpea and maize varieties. Understanding the effects is vital for designing a dehulling machine that can yield better performance. The physical and engineering properties of nine cowpea varieties and a local maize variety were determined to provide essential data for the design of dehulling and processing equipment. Standard laboratory methods reported in the literature were used to analyze the grains. The study reveals that the physical and engineering properties of nine cowpea and maize varieties varied considerably (p < 0.05). The mean values of moisture content % ranged from 10.06 to 13.81%, length ranged from 7.11 to 11.44 mm, width ranged from 5.65 to 10.28 mm, thickness ranged from 4.60 to 6.73 mm, and thousand-grain weight ranged from 100 to 364 g. Da ranged from 5.79 to 8.89 mm, Dg ranged from 5.66 to 8.59 mm, sphericity ranged from 0.73 to 0.86, surface area ranged from 101.38 to 233.75 mm², and volume ranged from 97.05 to 339.82 mm³. Furthermore, the COF on stainless steel ranged from 0.30 to 0.37, the angle of repose ranged from 20.03 to 30.33°, the bulk density ranged from 688.00 to 814.67 kg/m³, the true density ranged from 1079.91 to 1282.61 kg/m³, and the porosity % ranged from 60.53 to 67.46%. Lastly, grain hardness ranged from 56.27 to 267.91 N, grain compressive energy ranged from 80.91 to 664 mJ, grain stiffness ranged from 6.48 to 26.13 N/mm, seed coat–cotyledon/pericarp–endosperm stickiness force ranged from 0.04 to 0.10 N, Adhesiveness (force to overcome stickiness) ranged from 0.08 to 93.42 N · mm, and fracturability ranged from 56.27 to 267.91 N. These results offer a comprehensive engineering database for the design and optimization of dehulling and post-harvest processing equipment. Full article

The potato chip processing (PCP) industry generates huge amounts of wastewater heavily polluted with organic matter and nutrients. The current treatment technology of PCP wastewater uses dissolved air flotation (DAF) and an activated sludge sequential batch reactor (SBR); both consume large amounts of chemicals and represent energy-intensive systems. This study explores the utilization of algae for the sustainable treatment of PCP wastewater, nutrient recovery, and algal biomass production. Conical flasks (1-L) and 6-L transparent plastic bottles were used as lab-scale algae photobioreactors (APBRs). Raw wastewater, an anaerobically pre-treated effluent and a DAF–SBR or shortly SBR effluent were used in the first, second, and third APBR. Three feed volumes from each source (150 mL, 300 mL, and 500 mL for first and second APBR and 400 mL, 600 mL, and 800 mL for third APBR) to a fixed volume of algal seed (200 mL) were tested to select the optimal feed volume and harvest time using a 1-L APBR. System performance and impact of water characteristics on quantity and quality of algal biomass were explored at pre-selected feed volume and harvest time in 6-L APBRs. All experiments were carried out in a growth chamber with continuous light (148.75 μmol.m⁻².S⁻¹). The results showed that 150 mL is the optimal feed volume for the first and second APBR at 10 days and 9 days growth cycles. An amount of 500 mL and 6 days were selected as the optimal feed volume and growth cycle for the third APBR. The average dry biomass yields at the pre-selected optimal conditions were 65.3 ± 11.4, 69.9 ± 12.0, and 100.6 ± 11.7 mg/L.d in the first, second, and third APBR, respectively. The first APBR achieved removals of 99.2 ± 0.4%, 98.7 ± 0.8%, 89.1 ± 4.3%, and 97.5 ± 1.4% for turbidity, COD, TKN, and TP, respectively, on average. Corresponding removal in the second APBR is 97.6 ± 2.6%, 91.6 ± 7.5%, 93.6 ± 4.5%, and 96.1 ± 1.4%, respectively, while the third APBR achieved 98.5%, 76.2%, and 97.0%, respectively. Additionally, the results of protein content and amino acids profiles indicate significant impacts of feed water quality on both parameters. The protein content was 30.64%, 32.53%, and 35.65% in the first, second, and third APBR, respectively. Similarly, the amino acids profile indicated a significant higher percentage of the amino acids in the third reactor compared with the first and second reactor. Full article

To deliver freshwater for drip irrigation, our study presents an optimal techno-economic based on a Water Pumping Photovoltaic System (WPPVS) that integrates a Hydrogen Energy Storage System (HySS) to ensure reliable freshwater for agricultural irrigation in remote arid regions. A critical operational challenge in WPPVS is mechanical vibration at low flow rates, which degrades the pump efficiency and lifespan. Our methodology directly addresses this issue by incorporating a vibration-avoidance strategy that ensures that the pump operates only within its stable and, efficient range. To reduce the loss of water supply probability and overall annual costs of the drip irrigation system, a multi-objective optimization framework using Multi-Objective Particle Swarm Optimization (MOPSO) and Gaussian Mixture Model (GMM) clustering to simultaneously minimize the Loss of Water Supply Probability (LWSP), and the system’s total life-cycle cost. The model’s practical applicability is demonstrated through a detailed techno-economic feasibility analysis for a tomato crop drip irrigation project in Sakaka, Saudi Arabia. Sensitivity analysis is performed on dynamic head, crop prices, and interest and inflation rates, confirming the robustness of the system against variable economic indicators. In comparison to 1071 h without HySS, the results revealed that the seasonal irradiation harvest hours are 1863, which represents 21% of the seasonal hours employing the developed hybrid energy storage coordination. This integrated approach provides a holistic and economically viable solution for designing reliable solar irrigation systems with long-term mechanical integrity. Full article

Energy-harvesting (EH) AIoT systems enable long-term autonomous operation but suffer from time-varying energy availability, which makes stable learning difficult. In such environments, federated learning (FL) is prone to energy depletion (blackout), while continual learning is required to handle evolving data distributions, leading to a trade-off between energy stability and catastrophic forgetting. In this paper, we propose a stability-controlled continual federated learning framework that jointly regulates local training intensity and rehearsal usage based on the residual energy state. The proposed method is derived from a Lyapunov drift-plus-penalty formulation and implemented as a lightweight mode-based control policy. Simulation results using real solar energy traces show that the proposed method significantly reduces blackout while improving accuracy and mitigating forgetting compared to existing approaches. These results demonstrate the effectiveness of energy-aware joint control for stable continual federated learning in EH-AIoT systems. Full article

The utilization of unconventional feed resources offers a sustainable strategy to mitigate feed shortages particularly in tropical and subtropical regions where access to conventional feeds is often limited. Among these, water hyacinth (Eichhornia crassipes) is one of the world’s most aggressive aquatic weeds, which has drawn attention due to its dual role as a problematic invasive species and a potential livestock feed. This plant reduces water quality, contributes to biodiversity loss and causes economic damage in farming systems. At the same time, its high capacity for nutrient absorption makes it a viable source of protein and energy for ruminants when properly harvested and processed into forms such as hay, dried leaves, and silage. However, its utilization requires caution, as the plant can accumulate toxins and heavy metals from polluted water, which may harm animal health if unprocessed. This review focuses on the potential of water hyacinth to improve ruminant growth performance, nutrient digestibility and rumen fermentation. Including water hyacinth in ruminant diet safely can possibly improve animal productivity, contribute to sustainable weed management and also provide a practical strategy to alleviate feed shortage in dry seasons, thereby encouraging resilience and sustainable ruminant production. Full article

Polymer–ceramic piezoelectric composites are widely investigated to combine the high piezoelectric performance of ferroelectric ceramics with the flexibility and processability of electroactive polymers. However, achieving enhanced dielectric properties while preserving the intrinsic piezoelectric response of the polymer matrix remains challenging, particularly due to dielectric mismatch between the constituent phases and interfacial effects. In this work, barium titanate (BaTiO₃) loaded poly(vinylidene fluoride-trifluoroethylene) (PVDF-TrFE) nanocomposites were fabricated by solvent casting using polyvinylpyrrolidone (PVP) and polysorbate 80 (PS80) as dispersing agents, aiming to obtain polarizable materials capable of retaining high piezoelectric strain coefficient (d₃₃) values and potentially exploiting the opposite polarity of matrix and filler through tailored poling strategies. Morphological, crystallographic, structural, thermal, thermomechanical, dielectric, and piezoelectric characterizations were performed by SEM/EDXS, XRD, FTIR, DSC, TGA, DMTA, dielectric spectroscopy, and d₃₃ measurements. Both dispersants improved filler dispersion and film densification, increasing the crystalline fraction of the matrix, without altering the relative fraction of β-phase (up to 93%). PVP enabled moderate and stable permittivity enhancement with weak frequency dependence, whereas PS80 introduced an electrically active interfacial contribution that amplified low-frequency permittivity at high filler loadings but made the permittivity more frequency-dependent. The piezoelectric response (between −20 pC/N and −25 pC/N) remained predominantly governed by the polymer phase, suggesting limited polarization played by BaTiO₃. These results underlined the critical role of interfacial electrical properties in designing stable high-performance flexible PVDF-TrFE/BaTiO₃ composites. Full article