Search Results (1,228)

Plant-derived nanocellulose particles, such as cellulose nanofibrils (CNFs) and cellulose nanocrystals (CNCs), are becoming increasingly popular for a wide range of applications. In particular, when they are employed as rheology modifiers and/or fillers, a choice between CNFs and CNCs is often not obvious. Here, we present the results of a comparative study on the rheological properties of suspensions and gels of carboxymethylated CNFs and CNCs with the same surface chemistry, surface density of charged groups, and thickness. We demonstrate that, at the same weight concentration, CNF suspensions have much higher viscosity and storage modulus, which is due to their longer length providing many entanglements. However, when comparing at the same nanoparticle concentration relative to C*, the situation is reversed: viscosity and storage modulus of CNCs appear to be much higher. This may be due in particular to the higher rigidity and intrinsic strength of highly crystalline CNCs. The gel points for CNF and CNC suspensions (without crosslinker) were compared for the first time. It was found that in the case of CNFs, the gel point occurs at a 3.5-fold lower concentration compared to that of CNCs. Hydrogels were also obtained by crosslinking negatively charged nanocellulose particles of both types by divalent calcium cations. For the first time, the thermodynamic parameters of the crosslinking of carboxymethylated CNFs by calcium ions were determined. Isothermal titration calorimetry data revealed that, for both CNFs and CNCs, crosslinking is endothermic and driven by increasing entropy, which is most likely due to the release of water molecules surrounding the interacting nanoparticles and Ca²⁺ ions. The addition of CaCl₂ to suspensions of nanocellulose particles leads to an increase in the storage modulus; the increase being much more significant for CNCs. Physically crosslinked hydrogels of both CNFs and CNCs can be reversibly destroyed by increasing the shear rate and then quickly recover up to 85% of their original viscosity when the shear rate decreases. The recovery time for CFC networks is only 6 s, which is much shorter than that of CNC networks. This property is promising for various applications, where nanocellulose suspensions are subjected to high shear forces (e.g., mixing, stirring, extrusion, injection, coating) and then need to regain their original properties when at rest. Full article

This paper aims to investigate the rheological behaviour of industrial lubricants at high shear and high pressure. A twin-disk rheometer based on a standard UMT apparatus is used to measure the rheological features and film thickness of three lubricants, namely, 150N, UB-3, and 15W/40, with the shear rate ranging from 0 s⁻¹ to 10⁷ s⁻¹ and the pressure at GPa. A semiempirical rheological model that considers the influence of heat, shear, and fluidic plasticity was proposed to adequately fit the experimental data of three organic lubricants. The rheology of the lubricants has a linear to nonlinear relationship with increasing shear rate, indicating shear thinning, which is then followed by a sharp decrease at approximately 10⁶ s⁻¹ because of thermal effects. At a higher shear rate, the shear stress saturates to a critical value. Moreover, the critical traction coefficients in the saturation region show similar changes in pressure and temperature for the three lubricants. The coefficients are greater at 1 GPa but decrease and saturate above 1.45 GPa, probably because the molecular-free volume is compressed by the constraint. The coefficients change little with varying inlet temperature at 1.45 GPa. This research sheds light on the complex rheological behaviour of three lubricants at high shear rates and high pressures and attempts to explain them theoretically. Full article

To address the challenges of low efficiency and high damage rates in dryland safflower harvesting, a roller-brush type harvesting device was developed. The design was developed following a detailed analysis of the spatial distribution and mechanical characteristics of safflower plants. The pose adjustment process begins with helical grooves clamping and contacting the plant stem. The propulsion action of the helix then forces the stem to undergo a predetermined deflection displacement. The optimal picking pose occurs when the plant’s longitudinal axis is perpendicular to the rotational axis of the picking roller brush. In this position, the picking roller brush shears the filaments at the necking zone through gentle contact with the fruit balls. This mechanism transforms the traditional pull-off separation into a low-damage shear-separation mode. The Box–Behnken test was designed to find the optimal combination of parameters for picking: picking roller brush speed of 282.5 r/min, roller brush spacing of 3.7 mm, and brush bristle diameter of 0.1 mm. Verification tests showed the picking, damage and fruit injury rates were 92.4%, 7.1% and 1.2%, respectively, with standard deviations of 5.42%, 0.51%, and 0.08%. The harvesting efficiency reached 0.053 hm²/h, 8.48 to 12.01 times higher than manual harvesting. Full article

A temporally periodic model is presented to describe the vertical profile of internal gravity waves in the F region of the Earth’s ionosphere where the waves are subject to a magnetic force due to the high concentration of ions. The configuration studied is representative of the situation where the geomagnetic field is approximately constant and is so strong that the angular gyrofrequency of the ions is very large compared with the ion-neutral collision frequency, which is in turn larger than the angular frequency of the gravity waves. We examine the situation where the gravity wave amplitude is small enough that the equations for the neutral fluid flow can be linearized. This allows for the description of wave propagation in terms of a system of coupled equations that include the effects of ion drag on waves for any orientation of the magnetic field. It is assumed that the background neutral fluid flow is nonzero and horizontal, but there is no vertical shear, and that the wave amplitude depends on altitude only, and an exact analytical solution is readily found. This dynamical model captures some essential features of ionospheric gravity waves that are consistent with observational measurements. In particular, the ion drag acts to damp the waves in the direction of vertical propagation and increase their vertical wavelength relative to the corresponding wavelength in the neutral atmosphere. The vertical damping rate and the vertical wavelength both depend on the dip angle of the magnetic field. When the magnetic field acts in the direction of the gravity lines of constant phase, there is no damping, and the vertical wavelength is the same as that of the corresponding waves in the neutral atmosphere. The dip angles that produce stronger damping also result in waves with greater wavelengths. Full article

This study explores the potential of a bio-based thermosetting adhesive system incorporating recycled fillers to enhance structural bonding applications while promoting sustainability. Diglycidylether of vanillyl alcohol (DGEVA) was selected as the resin matrix due to its favorable thermomechanical properties and low moisture absorption. To improve mechanical performance and support circular economy principles, recycled carbon fibers (RCFs) and mineral wool (MW) were integrated into the adhesive formulation in varying proportions (10, 30, and 50 phr). A cationic thermal initiator, ytterbium (III) trifluoromethanesulfonate (YTT), was used to permit polymerization. Comprehensive characterization was performed to assess the curing behavior, thermal stability, and mechanical performance of the adhesive. FTIR spectroscopy monitored the polymerization process, while DSC and dynamic DSC provided insights into reaction kinetics, including activation energy, and curing rates. The mechanical and thermomechanical properties were evaluated using dynamic mechanical thermal analysis (DMTA) and shear lap testing on bonded joints. Additionally, SEM imaging was employed to examine fillers’ morphology and joint interfaces. The results indicated that increasing filler content slowed polymerization and raised activation energy but still permitted high conversion rates. Both RCF- and MW-containing formulations exhibited improved stiffness and adhesion strength, particularly in CMC joints. These findings suggest that DGEVA-based adhesives reinforced with recycled fillers offer a viable and sustainable alternative for structural bonding, contributing to waste valorization and green material development in engineering applications. Full article

In a previous experimental study, a high-frequency reciprocating rig tribotester was used to test several base oils, including a mineral oil and a vegetable oil, as well as a blend of the two, with and without the addition of carbon-based nanoparticles. The results showed synergy between certain nanoparticles and the oil blend. As such, in this study, molecular dynamics simulations are conducted on three systems to find the model that most accurately represents the experimental setup. These systems consist of lubricant molecules sandwiched between two iron oxide surfaces. The lubricant molecules represent the three types of lubricant used in the experimental study: hexadecane for the mineral base oil, a mixture of fatty acids for the rapeseed oil, and a mixture of both hexadecane and fatty acids for the oil blend. Three system sizes were considered: the first with 100 molecules, the second with 200 molecules, and the third with 300 molecules. The density, velocity, and temperature profiles, as well as the shear rate and coefficient of friction, are analyzed. The results show that the 300-molecule systems show a similar trend to that observed in the experimental study, with the vegetable oil model having the lowest coefficient of friction, followed by the blend model and finally the hexadecane model. The different analyzed profiles provide valuable insights into the interactions within the lubricant film. Full article

This study systematically investigates the complex nonlinear rheological behavior of magnetorheological fluids (MRFs) and greases (MRGs) through comparative experiments under two shear modes (steady-state shear and large-amplitude oscillatory shear) at room temperature. Results demonstrate that during steady-state shear tests, the apparent viscosity of both materials decreases with the increasing shear rate, exhibiting shear-thinning behavior at high shear rates that aligns with the Herschel–Bulkley constitutive model. Throughout the logarithmically increasing shear rate range, the viscosity and shear stress of MRF consistently exceed those of MRG. Under low-frequency, large-amplitude oscillatory shear (LAOS) conditions, both materials display pronounced viscoelasticity and hysteresis. At higher current levels, the maximum shear stress of MRF surpasses MRG, but its hysteresis loops exhibit reduced smoothness. The Bouc–Wen model accurately characterizes the nonlinear hysteresis of both materials, with model parameters successfully identified via a genetic algorithm. This work establishes a universal framework for the dynamic mechanical response mechanisms of magnetorheological materials, providing theoretical guidance for designing and predicting the performance of smart damping devices. Full article

Bulk metallic glasses (BMGs), classified as metastable materials, necessitate melt quenching at critical cooling rates higher than 10² K/s to kinetically bypass crystalline phase formation during solidification. Owing to this rapid quenching, the microstructure of BMGs can be regarded as melt quenched. This study examines how their melt state governs the thermal stability, structural characteristics, and plasticity behavior of Zr₅₀Cu₄₀Al₁₀ BMG. Rod samples were prepared via injection casting at controlled melt temperatures and suction casting. Experimental observations demonstrated a positive correlation between elevated melt temperatures and enhanced glass forming ability (GFA) along with improved thermal stability (T-A) in BMGs during processing. Structural analyses confirmed the glassy nature of the prepared BMGs with different melt states and revealed their temperature-dependent atomic-scale heterogeneity: the samples quenched at low melt temperatures exhibited significant Cu-rich clustering as determined via energy-dispersive X-ray spectroscopy (EDS) mapping, and those at high melt temperatures formed homogeneous structures. This structure heterogeneity was directly correlated with good plastic deformation behavior, i.e., the rod sample prepared at the lowest melt temperature achieved 9.7% plastic strain. The transition is attributed to liquid-liquid phase transition (LLPT): below the LLPT threshold, metastable Cu-rich clusters persist in the melt and are retained upon quenching, creating structural defects that facilitate shear band multiplication. These findings highlight melt temperature as a crucial factor in tailoring the structure characteristic and mechanical behavior of Zr₅₀Cu₄₀Al₁₀ BMGs. Full article

To investigate the long-term water stability of graphene-modified permeable asphalt mixtures, in this study, we analysed the effects of single factors and multi-factor coupling. The single-factor water stability was investigated through the free thawing splitting test, standard Cantabro test, and immersion Cantabro test; the experimental indicators were the freeze–thaw cracking ratio (TSR), mass loss rate, and immersion mass loss rate, respectively. The multi-factor water stability was studied through immersion operation tests of mixtures with different degrees of ageing. The dispersion of graphene was examined through Raman mapping, the formation of three-dimensional network structures of graphene and SBS was evaluated via the dynamic shear rheometer test (DSR), and the elemental distribution was quantitatively analysed using energy-dispersive spectroscopy (EDS) and an image pixel algorithm (RGB). The results indicate that an unaged graphene-composite- and SBS-modified permeable asphalt mixture with an optimal graphene content of 0.05% demonstrated a 4.5% improvement in the TSR, alongside reductions in the mass loss rate and water immersion mass loss rate of 25.64% and 23.52%, respectively. Even after prolonged thermal oxygen ageing, its TSR, mass loss rate, and water immersion mass loss rate improved by 5.1%, 23.04%, and 20.70%, respectively. Multi-factor coupling tests confirmed that the water stability met requirements under severe conditions, with better performance at high temperatures. Graphene was uniformly dispersed in the modified asphalt. The appearance of a plateau region at low frequencies in graphene-composite- and SBS-modified asphalt verified the formation of a three-dimensional network structure, and the oxygen content was positively correlated with deepening thermal oxidative ageing. Full article

Accounting for geotechnical property variability is crucial in seismic site response analysis. Traditionally, the influence of each geotechnical property on response parameters is assessed independently. However, this approach limits our understanding of the combined effects of multiple properties on ground response parameters. This study presents a novel, explainable machine learning (ML)-based approach to assess the influence of multiple geotechnical property variations on response parameters. Four ML models, namely AdaBoost, Extreme Gradient Boosting (XGBoost), Random Forest Regressor (RFR) and Gradient Boosting Machine (GBM), were developed for predictive models. The input factors were shear-wave velocity, plasticity index, soil thickness, input motion intensity and unit weight of the soils. The response parameters were peak ground acceleration (PGA) and peak ground displacement (PGD). Multiple statistical performance metrics were computed to evaluate the performance of the models. The results show the superior prediction performance of the GBM model with low error rates and high agreement index (AI), Kling–Gupta efficiency (KGE) and coefficient of determination ${(R}^2)$. The output of the GBM model was further analyzed using Shapley Additive exPlanation (SHAP) technique to explain and identify the most significant factors contributing to the predictions. Finally, the model was used to develop user-friendly web-based software to facilitate rapid predictions of PGA and PGD. Full article

The growing demand from the automotive industry for lightweight, high-performance, and advanced manufacturing techniques for efficient and cost-effective production has accelerated the adoption of fiber-reinforced polymer composites. However, considering the manufacturing complexity of these materials, design remains challenging due to the intricate and interdependent relationships between the process conditions, the part geometry, and the resulting microstructure and quality. This research utilized the Autodesk Moldflow Insight software to design an injection molding process for the manufacturing of discontinuous glass fiber-reinforced polymer parts through computer modeling. A geometrically complex car fender was used as a case study. The effects of various process parameters, particularly gate locations, on the injection-molded parts’ properties (such as the fiber orientation, volumetric shrinkage, and shear rate) were investigated. Multiple injection molding process configurations were designed and simulated, including three, four, and five gates at varying locations. Based on the optimal performance (i.e., low shrinkage, a consistent fiber orientation, and a controllable shear rate), an optimal configuration with four gates at appropriate locations (corresponding to the second gate location set) was identified based on multicriteria decision-making analysis, i.e., volumetric shrinkage of ${8.5}_{-2.2}^{+1.4}\%$, a fiber orientation tensor of 0.927 ± 0.011, and a stable shear rate < 74,324 (1/s). A reduced strain closure model (modified Folgar–Tucker model) was used to predict the glass fiber orientation. A multicriteria decision-making technique, based on similarity ranking with an ideal solution, was employed to optimize the gate location. The simulation results clearly demonstrate that the gate placement is crucial for material behavior during molding and for reducing common defects. The simulation-based injection molding process design for the manufacturing of discontinuous fiber-reinforced polymer parts proposed in this paper can improve the production efficiency, reduce trial-and-error rates, and improve part quality. Full article

The shell liner is a core component of Semi-Autogenous Grinding (SAG) mills, suffering severe wear from ore impact and friction, and its shape directly affects grinding efficiency and maintenance costs. In this study, the Finnie wear model in EDEM2022 software was improved to predict the wear morphology evolution of shell liners. A Python-based coupled simulation of the Discrete Element Method (DEM, EDEM) and Finite Element Method (FEM, ABAQUS) was established to analyze liner wear mechanisms, stress states, and mill service performance (wear resistance, grinding efficiency, and stress distribution). The simulated wear profile showed high consistency with laser three-dimensional scanning (LTDS) results, confirming the improved Finnie-DEM model’s effectiveness in reproducing liner wear evolution. Shearing in crushing/grinding zones was the main wear cause, with additional contributions from relative sliding among ore, grinding balls, and liners in grinding/discharge zones. DEM-FEM coupling revealed two circumferential instantaneous wear extremes (Max^a > Max^b) and two lifter wear rate peaks (M^a > M^b). In the grinding zone, liner stress distribution matched wear distribution, with maximum instantaneous stress at characteristic points A and B—stress at A reflects liner impact degree, while stress at B indicates mill ore-crushing capacity. Optimizing flat liner shape adjusted wear rate peaks (M^a, M^b), improving overall liner wear. This optimization significantly affected stresses at A/B and ore normal collision but had little impact on mill energy efficiency. Full article

This study aimed to investigate the effects of Levilactobacillus brevis, Lacticaseibacillus paracasei, and Lacticaseibacillus rhamnosus strains isolated from Mihalic cheese, also known as “weeping cheese”, on fermentation kinetics, microbial viability, and textural and aromatic properties of the butter matrix. The effects of the isolates were determined on acidification kinetics (V_max, T_vmax, pH_vmax), viability proportion index (VPI), textural parameters (firmness, work of shear, stickiness, work of adhesion), and volatile aroma compounds (GC-MS) formation. This study found that the BLR sample containing Lacticaseibacillus rhamnosus maintained its limited viability under acidic stress conditions despite its high fermentation rate and low pH_vmax values. The BLP sample containing Lacticaseibacillus paracasei exhibited high viability due to its low acidification rate and limited pH change. Determining the chemical classes to which the aroma compounds in the BLP sample belonged revealed a composition rich in fatty acids. The BLB sample containing Levilactobacillus brevis produced a high ΔpH value and an aroma profile rich in aldehyde compounds. Examination of the macro-structural properties of the butter samples revealed that the sample containing Lacticaseibacillus rhamnosus, similar to the control sample (BMC), was more compact and rigid during storage. In contrast, samples containing Lacticaseibacillus paracasei and Levilactobacillus brevis had a softer/spreadable texture. These findings demonstrate the potential of lactic acid bacteria isolates from the traditional Mihalic cheese microbiota as biological catalysts for the development/improvement of texture, aroma, and sensory quality in high-fat dairy products and for the industrial production of products modified to meet consumer preferences. Full article

Aligned with Saudi Arabia’s Vision 2030 and its corresponding global direction, this study aimed to identify and evaluate an environmentally friendly and alternative material to replace conventional synthetic polymers for polymer flooding. Extracting biopolymer solution, characterizing rheological properties, and conducting core-flooding experiments (seawater flood (SWF), secondary polymer flood (PF), and tertiary polymer flood) were experimentally investigated under simulated reservoir conditions (75 °C, 165,000 ppm TDS brine, and 2000 psi pore pressure). Biopolymer solutions were successfully generated from powdered pomegranate peels, and rheological characterizations of solutions with different shear rates, temperatures, and pomegranate-peel concentrations were investigated. Results revealed that significant shear-thinning behavior was pronounced in the biopolymer solutions, where 7% solution was selected for core-flooding tests. 7% solution exhibited 14.4 cP apparent viscosity at 13.2 s⁻¹ shear rate and 75 °C, indicating good thermal stability. Interfacial tension (IFT) results demonstrated high IFTs compared to the required IFT to reduce capillary forces, indicating that improved mobility control through viscosity enhancement serves as dominant EOR mechanism. The results indicated that PF yielded a higher ultimate oil recovery (62.2%) compared to SWF (47.6%) and tertiary polymer flood (58.0%). Results demonstrated that significant pressure fluctuations during polymer injection were observed, highlighting injectivity challenges. From all results, pomegranate peels would be potentially used to generate a biopolymer solution and replace environmentally hazardous materials. Full article

Additive manufacturing enables the fabrication of lightweight structures with complex geometries, offering significant potential in aerospace and biomedical applications. Triply periodic minimal surface (TPMS) lattice structures are of particular interest due to their geometry. However, their intricate geometries pose challenges for both experimental characterization and numerical simulation. This study numerically investigates the effective mechanical properties and dynamic response of AlSi10Mg TPMS structures produced by laser powder bed fusion (PBF-LB/M). Using a micro–mesoscale approach with periodic boundary conditions, Young’s modulus, shear modulus, and Poisson’s ratio in the elastic region using the Johnson–Cook plasticity model are analyzed. Finite element simulations of the representative volume element (RVE) are employed to assess energy absorption and damage evolution under high strain rates, incorporating a ductile damage model. The performance of sheet-based TPMS lattices, namely, Schwarz–Primitive, Gyroid, Schwarz–Diamond, and IWP, is compared with strut-based lattices, namely, BCC and FCC, across volume fractions of 20–40%. Results demonstrate the superior stiffness and energy absorption of TPMS lattices, where Schwarz–Diamond and IWP outperformed the other structures, highlighting their advantages over conventional strut-based designs. This comprehensive numerical framework provides new insights into the high strain-rate behavior of TPMS structures and supports their design for demanding engineering applications. Full article