This study presents a systematic investigation into the performance optimization of proton exchange membrane electrolyzer cells (PEMEC) for hydrogen production, integrating both experimental analysis and machine learning. Key operational parameters, including temperature and water flow rate on the one hand, and porous transport layer (PTL) materials on the other hand, were evaluated to determine their impact on electrochemical performance. Two PTL variants, titanium felt (Ti-felt) and titanium powder (Ti-powder), were characterized using scanning electron microscopy (SEM), polarization curve, and electrochemical impedance spectroscopy (EIS). Results demonstrated that Ti-powder significantly enhanced PEMEC performance compared to Ti-felt under identical conditions. In contrast, the variation of water flow rate exhibited negligible influence, underscoring the dominance of material properties over fluid dynamics in certain regimes. Additionally, temperature elevation substantially improved the performance. Complementing experiments, machine learning, specifically the AdaBoostRegressor model, applied to PEMEC optimization, enabled a predictive model for performance trends and operational parameter interactions.

Solar desalination systems commonly suffer from intermittent freshwater production due to the transient nature of solar radiation and the absence of effective thermal buffering during low- or off-sunshine periods. This study develops and optimizes a hybrid solar desalination system integrating flat-plate solar collectors, a packed-bed latent heat thermal energy storage (TES) tank filled with encapsulated RT65 phase-change material, and a four-effect solar still. A transient numerical framework is developed to describe the coupled thermal interaction among the collector loop, PCM storage tank, heat exchanger, and multi-effect still. The heat-transfer fluid flow is divided between direct heating of the solar still and TES charging, creating a trade-off between immediate freshwater production and delayed thermal supply. Response surface methodology is employed to optimize the total system flow rate Qsys and the TES flow fraction γ. The optimum operating conditions are obtained at Qsys=0.87 m3/h and γ=11%, yielding a distilled water production of 53.30 kg/day. Compared with the optimized conventional system under the same solar radiation profile, collector area, still geometry, and operating duration, the PCM-assisted configuration increases freshwater productivity by 21.97%. The solar-to-evaporation thermal efficiency increases from 50.68% to 62.20%, corresponding to a 22.73% relative improvement. The results demonstrate that optimized latent heat storage can stabilize thermal delivery, extend desalination operation, and improve freshwater productivity in solar-driven multi-effect desalination systems.

​Against the backdrop of intensifying global energy supply-demand imbalances, enhancing energy utilization efficiency has become a critical challenge. As a phase change material with high energy storage density, ice slurry holds significant application value in HVAC systems. To fully leverage the heat transfer and flow advantages of ice slurry, this research adopts the Euler-Euler two-fluid model to conduct a numerical investigation of the flow and heat transfer characteristics of ice slurry within twisted flat tubes. The analysis focuses on the effects of the straight section length (W) and the twist pitch length (P) of the twisted flat tube cross-section on flow patterns, resistance characteristics, heat transfer performance, and the ice particle phase change process. Results indicated that a helical secondary flow forms within the twisted flat tube, with its intensity increasing as both W and P decrease. The average friction factor (f) decreases with increasing flow velocity (u), increases with rising W and ice slurry volume fraction (α), and decreases with increasing P. The average nusselt number (Nu) increases with rising W and u, decreases with increasing P, and shows a decreasing trend with increasing α. The concentration of ice particulates exhibits a monotonic decline along the streamwise path. Higher W values and lower P values promote the melting of ice particles. The temperature field exhibits an S-shaped distribution across the cross-section, reducing P significantly improves the temperature uniformity. Finally, empirical correlations for f and average Nu are established, with prediction deviations controlled within ±10% and ±5%, respectively. This study provides theoretical support for the structural optimization of twisted flat tube heat exchangers and the efficient application of ice slurry in thermal energy storage configurations.

With the advancement of wearable electronics toward longer battery life, multifunctionality, and intelligence, traditional rigid energy storage devices and discrete modules for energy harvesting, storage, and sensing are increasingly inadequate in meeting the demands of wearable systems for flexibility, safety, integration, and self-powering capabilities. Aqueous zinc-ion batteries (AZIBs) have emerged as an ideal candidate for constructing wearable energy systems due to their intrinsic safety, low cost, environmental friendliness, and excellent electrochemical performance. This review focuses on integrated systems of wearable AZIBs, systematically elaborating their development pathway from achieving u201Cenergy autonomyu201D to enabling u201Cintelligent sensingu201D. First, the fundamental principles, advantages, and necessity of integrated technologies for wearable AZIBs are analyzed. Next, recent research advancements in this field are comprehensively reviewed. Finally, current key challenges are summarized, and prospects for the future development of truly self-driven, intelligent, and comfortable wearable AZIBs systems are discussed.

The spectral-beam-splitting concentrating photovoltaic-thermal (SBS-CPV/T) system has attracted increasing research interest for its flexibility in adjusting the solar energy distribution among photovoltaic and photothermal units and its high utilization of solar radiation. A novel system integrating the SBS-CPV/T system and the organic flash cycle (OFC) directly through the nanofluid is proposed in this work for higher solar energy utilization efficiency in combined heat and power systems. This configuration converts the indirect heat supply of the heat exchanger between the heat source and OFC into the direct replenishment of heat using nanofluids. The thermodynamic model of the SBS-CPV/T-OFC system is established, and the effects of four different OFC configurations and key parameters are explored. The electrical efficiency of the SBS-CPV/T system can reach 11.79% while the thermal efficiency is 28.19%. The optical loss is the main energy loss in the SBS-CPV/T system. A higher outlet temperature of the heat collection tube and an appropriate flashing pressure after the throttle valve lead to better performance of the OFC systems. The regenerative double flashing OFC (RDOFC) shows the highest exergy efficiency of 53.52% under a solar irradiance of 1000 W/m2, which is 9.6% higher than that of the basic OFC (BOFC). The SBS-CPV/T-RDOFC system with R1336mzz(Z) as the recommended working fluid achieves electrical efficiency and thermal efficiency up to 15.49% and 51.87%, respectively.

The dynamic integration of Solid Oxide Fuel Cell (SOFC) systems with power electronics presents significant challenges due to the disparate time scales of thermo-electrochemical processes and electronic control systems. This manuscript develops a unified standard thermal resistance-impedance-circuit approach for grid-connected SOFC systems. This approach provides a comprehensive cross-scale dynamic model, coupling the standard thermal impedance (STI) method for SOFC modeling with power regulation circuit for converter and inverter, which constructs the overall system topology and characterizes the transmission and coupling characteristics of various physical parameters within different components, integrating the multi-physical processes, cross-timescale dynamics and inter-disciplined areas to facilitate real-time simulation and control. On this basis, we analyze the dynamic response processes of power electronics equipment, and SOFC systems under varying load conditions. The results show that the power electronics respond in sub-second time frames (0.15-0.5 s), Balance of Plant (BOP) components have intermediate response times (7-9 min), and SOFC stack exhibit slow response times (25-39 min) when the load changes. This unified model visualizes the transfer and coupling properties of physical parameters within different components, highlights the interactions between the slow thermal-electrochemical dynamics and the fast-switching power electronics, then emphasizes the topology's capacity to handle transient states and ensure robust performance. The proposed framework provides a pathway for enhancing computational efficiency, improving power quality, and ensuring operational stability in distributed energy systems.

Cascaded phase-change material (PCM) packed-bed thermal energy storage systems improve thermal performance by enhancing temperature matching between PCMs and heat transfer fluids. However, existing optimization strategies based on aggregated indicators cannot explicitly formulate the inherent charging-discharging trade-off. This study develops a multi-objective optimization formulation for charging-discharging trade-offs by incorporating transient thermocline evolution analysis using a dispersion–concentric (D-C) model, PCM configuration selection, and stage-wise filling-ratio optimization. Charging and discharging thermocline thicknesses are formulated as competing objectives to quantify the trade-off and identify balanced PCM configurations and filling-ratio distributions. A representative compromise solution is selected from the Pareto set using the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The comparative optimization of eight configurations involving six candidate PCMs revealed that the optimal configuration consists of PCM-1a (35 wt% Li2CO3–65 wt% K2CO3), PCM-2c (55 wt% MgCl2–45 wt% NaCl), and PCM-3e (59.98 wt% MgCl2–20.42 wt% KCl–19.6 wt% NaCl), with volumetric filling ratios of 0.13, 0.38, and 0.49, respectively. Compared with the reference scheme, the optimized scheme reduces the charging thermocline thickness by 78.5% while increasing the discharging thermocline thickness by 0.07, thereby improving the capacity ratio and utilization rate by 10% and 17.6%, respectively. Correspondingly, the charging, overall energy, and exergy efficiencies are improved by 4.4%, 5.3%, and 3.3%, respectively. This optimized design achieves the highest system benchmarks: a capacity ratio of 0.8, a utilization rate of 0.66, and a total TES capacity of 157.8 MWh.

The development of large-scale proton exchange membrane water electrolyzer cell (PEMEC) models is pivotal for advancing the industrialization of green hydrogen production, addressing critical challenges in computational efficiency and operational fidelity during system upscaling. In this study, five progressively simplified PEMEC models are developed and evaluated to reconcile computational efficiency with predictive accuracy, focusing on their resolution of key physical fields: current density, temperature, pressure, and liquid saturation. The fully resolved Model 1 serves as the accuracy benchmark, while subsequent models omit geometric domains (e.g., cathode components, bipolar plate and catalyst layer). Results demonstrate a clear trade-off: excessive structural simplification accelerates computation but may amplify prediction errors, with Model 5 achieving the fastest runtime (1.1 h) at the cost of the highest deviation (3.06%). Model 4 emerges as the optimal compromise, reducing computational time by 56% versus Model 1 while maintaining minimal errors (1.02%) through targeted retention of electrochemical coupling. Crucially, bipolar plate geometry plays an important role in temperature distribution prediction, while electrochemical heterogeneity governs fluid-phase transport accuracy. Validation on a commercial-scale electrolyzer (400 cm2 active area) confirms the adaptability of the proposed model to complex flow field architectures, highlighting its utility for large-scale design optimization. This work delivers a practical modeling framework for industrial-scale PEMEC design, enabling fast and reliable virtual prototyping of large systems while preserving accuracy in multi-physics simulations.

A NiFeCoMnMo high-entropy catalyst shows enhanced OER activity. Mo tuning optimizes the electronic structure and induces surface reconstruction to an active oxyhydroxide, promoting kinetics and stability with possible lattice oxygen involvement.

The efficient separation of photogenerated charge carriers persists as a principal constraint on achievable hydrogen evolution efficiency in cadmium sulfide (CdS)-based photocatalysts. Surface-engineering approaches, including carbon-coating strategies and heterojunction fabrication, provide viable pathways to mitigate this limitation. In this work, the facile hydrothermal synthesis of CdS/CuMoO4@C composite photocatalysts has been reported. The concurrent implementation of a conductive carbon overlayer and the establishment of an S-scheme heterojunction architecture synergistically enhance interfacial charge separation kinetics, resulting in superior photocatalytic hydrogen generation performance. Notably, the optimized CdS/CuMoO4@C composite achieved an exceptional hydrogen evolution rate of 361.73 mu mol, representing a 6.20-fold enhancement relative to pristine CdS. Mechanistic analyses reveal that the carbonaceous coating facilitates directional electron transfer pathways and induces thermal field intensification at the heterointerface, thereby promoting the spatial segregation of photoelectrons and holes. Concurrently, the encapsulating carbon matrix confers enhanced dispersion stability and preserves structural integrity under sustained illumination. This work furnishes fundamental insights into the electron-thermal coupling phenomena engendered by interfacial carbon species, elucidating their critical role in modulating interfacial charge transfer dynamics within heterostructured photocatalysts.

Phase change material slurries offer immense potential for efficient cold thermal energy storage, but enhancing their heat transfer typically incurs a severe flow resistance penalty. To address this thermo-hydraulic trade-off, this study proposes a comprehensive data-driven framework integrating Computational Fluid Dynamics (CFD), interpretable machine learning, and multi-objective optimization to investigate the thermo-hydraulic characteristics of ice slurry inside a twisted tape-enhanced tube (TTET). CFD results indicate that the twisted tape breaks the radial symmetry of the flow and induces intense secondary helical flows that propel ice particles toward the wall. Decreasing the twist ratio (TR) and clearance ratio (CR) significantly enhances the average Nusselt number (Nuave) but simultaneously increases the friction factor (fave). Subsequently, six mainstream machine learning models were evaluated for predicting Nuave and fave. The Multi-Layer Perceptron (MLP) exhibited superior predictive robustness, achieving test R2 values of 0.996 and 0.989 respectively. Furthermore, SHAP feature attribution revealed that the Reynolds number (Re) dominates heat transfer with a 56.8% contribution, whereas TR primarily governs the flow resistance penalty with a 33.4% contribution. Finally, coupling the MLP model with the Multi-Objective Grey Wolf Optimizer (MOGWO) and TOPSIS decision criteria captured the Pareto optimal frontier. The identified optimal configuration (TR = 2.406, CR = 0.386, Re = 15,171.424, αin = 10%, ds = 0.250 mm) achieves a 42.9% heat transfer enhancement and a 52.3% flow resistance reduction compared to the baseline. This paradigm provides an efficient and physically interpretable pathway for optimizing complex thermal management systems.

The scarcity of freshwater in arid regions necessitates reliable and sustainable desalination methods. While traditional solar-powered stills offer a viable solution, their performance is inherently limited by daily solar intensity, leading to inconsistent freshwater production. This study introduces an innovative integrated system that couples a solar still with a latent/sensible heat packed bed thermal energy storage unit. This novel design aims to achieve stable, continuous freshwater production throughout both day and night. This research addresses a research gap in the existing literature by providing a comprehensive analysis of this integrated system under realistic solar conditions. A numerical model has been developed, coupling differential equations for a solar still and solar collector with a dispersion concentric model for a packed bed storage system. The system's performance has been assessed under Sinai Desert solar conditions and validated against existing literature. Various phase change materials (PCMs), sensible heat storage materials, and geometric parameters were analyzed. Results showed that RT65, as a PCM, delivered the best performance with 40.94 % thermal efficiency and 26.17 kg/day freshwater output. Among sensible heat materials, quartzite rock performed optimally, achieving 34.31 % efficiency and 21.90 kg/day water production. Further analysis revealed that smaller storage capsules (20 mm diameter) and lower bed porosity (0.22) enhanced distilled water yield to 27.04 kg/day with 42.29 % system efficiency. The geometric optimization of the solar still resulted in maximum freshwater production of 29.51 kg per day when using a length of 6.75 m with a first effect water depth of 0.04 m and subsequent effect depths of 0.06 m, demonstrating how staged water depth variations significantly improve system performance. Additionally, various correlations have been developed to predict accumulated distillate output and system efficiency, aiding in system performance estimation. These findings provide critical insights for designing efficient integrated thermal storage and desalination systems in arid regions.

In the design process of space gas-cooled microreactors, it is essential to investigate the flow and heat transfer characteristics of fuel rod bundles to ensure the rationality and feasibility. Helium-xenon gas mixtures are commonly employed as coolants in such reactors. However, existing studies about helium-xenon gas mixture flow and heat transfer characteristics were mainly performed with circular, annular, or rectangular crosssectional channels, while few with rod bundle regions. Furthermore, current studies predominantly rely on numerical simulations, while few on experiments due to the high cost of helium-xenon gas mixture. In order to obtain the experimental data, an experiment is designed using air instead of helium-xenon gas mixture based on similarity analysis between air and helium-xenon gas mixture. Consequently, in this paper, a similarity analysis method by differential equation analysis method for the flow and heat transfer of air and helium-xenon gas mixture is established. According to the boundary conditions obtained from the similarity analysis theory, the flow and heat transfer experiment is conducted under different operating conditions to obtain the temperature distribution and the pressure drop variations within the core. Through analyzing the experimental results of helium-xenon gas mixture converted from air by similarity theory criteria, a set of semi-empirical correlations for helium-xenon gas mixture flow and heat transfer is proposed by using a six-rod average methodology, demonstrating errors within 10 %. The derived correlations exhibit conservatism, ensuring reliability in engineering applications. This study can validate the reactor core structural design and provide critical experimental references for the design of space gas-cooled microreactors.

The battery thermal management system (BTMS) is essential for lithium-ion battery applications. However, wide-temperature-range BTMS remains insufficiently explored. This study proposes a novel temperature-adaptive BTMS based on a phase change material (PCM) thermal regulator, which can dynamically adjust cooling performance through changes in PCM volume. An experimental prototype and a three-dimensional transient model of the proposed BTMS were established to evaluate its thermal performance under constant-current charge-discharge cycles, dynamic stress test (DST) driving cycles, various ambient temperatures, and different PCM physical properties. Results indicate that the PCM thermal regulator can simultaneously satisfy the requirements of high-temperature heat dissipation and low-temperature insulation. At an ambient temperature of 25 degrees C, the average battery temperature remains below 51 degrees C during a discharge-charge cycle at 3C discharge and 1.5C charge rates. Effective thermal control is also achieved under dynamic DST driving cycles within an ambient temperature range of 25-40 degrees C. At low ambient temperatures from-20 degrees C to 0 degrees C, the PCM thermal regulator module exhibits longer heat retention above 0 degrees C and lower capacity loss than conventional PCM/ cooling plate hybrid BTMS. Furthermore, comparative analysis of five PCMs reveals that thermal conductivity is the most decisive factor influencing the performance of the PCM thermal regulator. This work offers a promising pathway for wide-temperature BTMS design.

Proton exchange membrane water electrolysis (PEMWE) is considered a promising technology for integrating with renewable energy owing to its high current density, hydrogen purity, operating pressure, and responsiveness. In practice, non-uniformity in PEMWE stacks adversely affects overall performance and durability. In this study, the temperature and voltage distributions of the PEMWE stack under different operating conditions were analyzed. Furthermore, a method for evaluating uniformity was introduced, and the effects of key operational parameters on stack uniformity were analyzed. The results indicated that the temperature of the inlet water was the decisive factor for the uniformity of the stack temperature. In contrast, the influence of voltage uniformity was more complex, with temperature and current density coupling as the main factors. Dynamic analysis demonstrated that water flow rate had a significant impact on response time, while it had a negligible impact on the overall performance of the stack. During transient processes, temperature non-uniformity induced voltage non-uniformity. Reducing the instantaneous step amplitude of the current can reduce transient voltage non-uniformity. These investigations contributed to elucidating the uniformity variations during stack operation, thereby guiding the optimization of operating strategies.

In this study， a new method for passive thermal management of lithium-ion batteries based on paraffin/expanded graphite/bamboo charcoal composite bilayer phase-change materials is proposed. To solve the problem of the limited temperature-control range of existing phase-change materials， a dual phase-change temperature （30 ℃/50 ℃） gradient structure is constructed， and a composite phase-change system with dual phase-change temperature regulation is developed by combining the high thermal conductivity of expanded graphite with the porous adsorption properties of bamboo charcoal. Based on these the results， at 40℃ ambient temperature and under 5C large multiplication rate working conditions， the temperature increase of the battery constructed using the double-layer phase-change material was 37.8% lower than that of the battery constructed using the non-phase-change material group （43.3 ℃ vs. 69.6 ℃， respectively）； at low temperatures （-10 ℃ and 0 ℃）， the double-layer phase-change material extended the battery’s effective working temperature range through the synergistic effects of the latent heat release of the phase change and heat storage in the pores. The composite phase-change system realized intelligent thermal management across a broad temperature spectrum （–10 –40 ℃） via the dual-phase-change mechanism， providing an innovative solution for the thermal safety regulation of batteries， which has significant engineering application value.

The non-uniform settlement of foundation caused by uneven temperature distribution greatly affects the safety characteristic of the high-temperature molten salt tank. Therefore, quantitatively investigating the temperature and settlement distribution is an effective way to improve the foundation safety performance. First, a commercial scale tank foundation applied in 100 MWe tower plant is designed. Second, a novel analytical formula for assessing the temperature distribution uniformity (TDU) of foundation is derived, by which the spatial characteristics of temperature field is described. Finally, the effects of different layouts and inlet air velocity of ventilation pipes are discussed. The results are concluded as follows. (1) The AIO-SS layout could lead to overheating of soil. Moreover, due to the significant offset and poor symmetry of temperature field relative to foundation geometric center in AIO-SS method, the TDU of AIO-SS is 5.589, which is lower than that 7.845 in AIO-AP layout where better uniformity of temperature and settlement performances can be obtained. (2) The elliptical temperature distribution of foundation still exists when the constant inlet velocities of all pipes are equal. The temperature uniformity of lower velocity of pipes is worse than that of higher parameter, whereas smaller settlement could be obtained when lower velocity is considered. (3) The variable inlet velocity of all pipes could improve uniformity of temperature and settlement distribution, and the maximum settlement is 11.8 mm which is 21 % lower than that of constant velocity strategy. The work provides insights on optimization design of salt tank foundation for better thermal and settlement performances.

Addressing global freshwater scarcity necessitates sustainable desalination technologies. Solar-driven interfacial evaporation presents a promising alternative to energy-intensive conventional methods. This study reports a high-performance, bio-based solar evaporator (CB-NWPF) fabricated from noodle wheat protein foam. Through a process involving starch removal, borate cross-linking, and surface carbonization, the evaporator features longrange vertical channels and hierarchical pores. This unique architecture synergistically promotes rapid capillary water transport, efficient salt reflux. Under one-sun illumination, the CB-NWPF evaporator achieves a high evaporation rate of 3.62 f 0.04 kg center dot m- 2 center dot h- 1 and an exceptional energy efficiency of 95.6 f 1.1%. It demonstrates remarkable long-term stability, outstanding salt resistance, and antibacterial efficacy. This work provides a novel strategy for developing high-performance solar evaporators from biomass resources.

To tackle the challenges associated with temporal scale decoupling, the lack of closed-loop feedback, and weak coupling between physical and data-driven models in integrated energy systems, this study proposes a comprehensive three-stage optimization framework characterized by multi-timescale coordination, combined with a hybrid physics-informed data-driven approach. First, the limitations of mainstream methods are summarized, including the disconnection between long-term planning and short-term operation, temporal scale disparities, and insufficient dynamic coordination between prediction and optimization. Based on this, a closed-loop analytical framework that smoothly integrates capacity planning, day-ahead scheduling, and intraday rolling optimization is established, thus enabling a bidirectional linkage between decision transmission and effect feedback. Additionally, a physics-based optimization model based on bi-level programming and intelligent algorithms with a data-driven forecasting model that utilizes a backpropagation neural network is tightly coupled, thus establishing an integrated dynamic coordination mechanism. Scenario validation results show that, by using the proposed approach, the prediction accuracy (R²) for wind power and photovoltaic power reaches 0.99305 and 0.9975, respectively, the system’s annualized investment cost is reduced by 22.6%, and the annual operating cost further decreases by approximately 2.1%. What’s more, the intraday rolling optimization ensures that the dispatch schedules of most equipment units maintain a fluctuation rate below 20% during more than 55% of operating time, effectively mitigating the risk of abrupt output fluctuations. This enables the coordinated optimization of economic performance and operational security/stability for the system throughout its entire lifecycle, thereby providing a viable solution for the system to efficiently tackle uncertainties.

The melting process of a phase change material (PCM) inside a capsule can be promising in the thermal management of spacecraft. Such spacecraft operate under various gravity conditions, but previous studies have mostly considered the influence of gravity conditions on the constrained melting process of a PCM and not on its unconstrained melting process. In this study, a numerical model was constructed to comprehensively analyze the constrained and unconstrained melting processes of a PCM inside a spherical capsule under low-gravity conditions. After validation, the model was then applied to investigating the effects of low-gravity conditions on the evolution of velocity, temperature, melt layer thickness, heat transfer, liquid fraction, and total melting time. For the unconstrained melting process, low-gravity conditions weaken buoyancy-driven natural convection and slow down the solid PCM downward trend, thereby limiting the melting rate. In addition, the melt layer thickness does not increase linearly with decreasing gravity. Specifically, the increase in melt layer thickness is smaller by about 1.06 mm when the gravity drops from 0.4g to 0.2g compared to when it drops from 0.2g to 0.1g. The local heat flux in the contact melting area gradually decreases with the reduction of gravity during the unconstrained melting process. During the constrained melting process, notable oscillations in the local heat flux were observed. Decreasing the gravity from g to 0g increased the total melting times of the constrained and unconstrained melting processes by 417