The catastrophic strength degradation constrains online damage diagnosis of brittle ceramics in the boiling heat transfer process. Here we present a new avenue to capture the onset time of strength degradation with sparse temperature sensors. The Leidenfrost temperature at 357 degrees C captured from surface heat flux marks as a directed percolation of multiple surface cracking. This reminisces a sudden transition from stable vapor layer in I boiling regime to vapor block in II boiling regime. It reverses the classical view that damage initiates from contacting the water at higher temperature similar to 1000 degrees C. The hoop of high tensile stress ascents from the edge of sample bottom, agreeing well with the upswing of quench front. This induces a rapidly growing surface macro-cracking for catastrophic strength degradation in the 1st boiling cycle. The destabilized vapor blanket at higher Leidenfrost temperature is confirmed by the transform of contact angle from 105 degrees to 90 degrees to 85 degrees and changed crack patterns from surface macro-cracking to hierarchical inner network. This work guides us to develop an online prevention for mitigating catastrophic failure of brittle ceramics.

Precise characterization of anisotropic thermal conductivity (k) under dynamic conditions is essential for accurate thermal modeling and safe operation of lithium-ion batteries. Here, we established a transformable platform by combining an optimized localized symmetric heating method with the heat flow method. With only minor adjustments, this platform enables reliable measurement of in-plane thermal conductivity (k//) and through-plane thermal conductivity (k perpendicular to) of pouch cells under varied temperatures, states of charge (SOC), and charge-discharge rates (C-rates). The results show that both k// and k perpendicular to increase with temperature, with the in-plane enhancement being more pronounced. In contrast, their dependence on SOC and C-rates is non-monotonic and strongly coupled, leading to complex variations. These dynamic behaviors likely originate from electrode structural transitions, interfacial contact changes, and products of side reactions, which collectively regulate directional heat transport. Importantly, the anisotropy k ratio consistently remains between 20 and 60 for the 1 Ah NCM613 pouch cell, confirming the persistence of strong anisotropy. Moreover, the variations in k// and k perpendicular to can exceed a factor of two under dynamic operating conditions. These findings provide essential input for next-generation thermal models and highlight the critical role of anisotropic k and its dependence on dynamic operating conditions in accurately capturing directional heat transport during battery operation.

Heat storage and heating technologies based on electricity utilization are crucial for achieving green heating and the low-carbon transition of the heating industry. Previous studies primarily used graphite as thermal conductivity enhancer rather than primary storage material. The practical application and economics of graphite thermal storage in distributed heating remain unexplored. This study evaluates a high-temperature sensible heat storage system that uses graphite as the primary storage material to replace traditional residential heating sources, marking the first application of such a system on the user side as a substitute for oil-fired boilers. Temperature uniformity during charging, discharging characteristics, and the overall system efficiency of the device were investigated. Results showed excellent temperature uniformity with high system efficiency (88.6 %) and thermal efficiency (92.2 %), ensuring stable and reliable thermal energy storage and release capabilities. The study also showed that the heating system effectively used off-peak electricity for heat storage, with electricity consumption patterns correlating with outdoor temperatures. Economic analysis demonstrates that increased heat storage capacity reduces operational costs during the heating season, achieving a 43.8 % cost reduction compared to the previous oil-fired boiler system. The optimization of thermal energy storage capacity needs to be considered to minimize total lifecycle cost and maximize economic benefits. This provides policymakers a pathway for fossil fuel heating replacement through off-peak electricity utilization, enabling urban heating decarbonization with economic viability.

Geminal-site catalysts (GSCs) are prospective candidates for fulfilling the goal of aqueous electrochemical reductive cross-coupling reactions (ERCR) at near-stoichiometric yields. Nevertheless, a problem lies in the lack of a synthetic route for GSCs with few single sites. Here we report a defect-accompanying strategy for synthesizing GSCs containing metal-defect catalytic pairs (M-D GSCs), meaning that Fe-D GSCs can realize the electrochemical synthesis of cyclohexanone oximes (CHOs) from high concentrations (0.5 M) of nitrites (NO2 -) and cyclohexanone (CYC) at near-stoichiometric yields (the Faradic efficiency or yieldC/N: 91.3%). Multiple in-/ex-situ characterizations demonstrated that metal-citrate complexes were converted to metal-defect catalytic pairs via the liberation of gaseous carbon/nitrogen species during pyrolysis. Furthermore, we developed an innovative cathodic oxime-alkali process, where high concentration NaNO2 and CYC can be electrochemically converted to high-purity products including NaOH and CHO. This work showcases the enormous potential of M-D GSCs in achieving near-stoichiometric conversion for ERCR reactions.

Design and research of an advanced solar-driven CO 2 photothermal–electrocatalytic synergistic reduction system to enhance CO 2 reduction efficiency.

Erythritol, with its high latent heat density and suitable melting point, holds great potential as a phase change material (PCM) in the low-to-medium temperature range. However, its low intrinsic thermal conductivity results in slow charging/discharging rates, restricting its wider application. The incorporation of highly conductive fillers is an effective solution, but the resulting phonon scattering at the newly introduced interfaces often compromises the expected thermal conductivity enhancement. In this study, functional groups (hydroxyl, carboxyl, and amino) were introduced onto the boron nitride nanosheets to enhance phonon matching with the matrix material and subsequently reduce the interfacial thermal resistance (ITR). We compared the ITR reduction efficiency across different functional groups and under varying functional group coverage degrees. The results demonstrated that the strong polarity of the carboxyl group leads to the most effective reduction, attributed to stronger electrostatic interactions and shorter interatomic distances at the interface. An optimal range for the coverage degree of functional groups was also observed. Increasing coverage degree effectively reduces ITR, but exceeding a certain limit leads to agglomeration, which adversely affects the reduction effect. This work provides guidance for the design of erythritol-based composite PCMs with enhanced thermal conductivity by tailoring functional groups to lower ITR.

Temperature non-uniformity in lithium-ion batteries can accelerate degradation, promote heterogeneous aging, and compromise thermal safety, and its characteristics differ markedly among cell formats. In this work, an electrochemical–thermal coupled model is employed for cylindrical and pouch cells to comparatively investigate their temperature non-uniformity under a unified parameter framework and identical boundary conditions. The thermal model explicitly resolves the realistic wound structures and incorporates anisotropic thermal conductivities (λ) and thermal contact resistance (TCR). Temperature non-uniformity is quantified in orthogonal directions using the temperature difference along cut-lines and the corresponding maximum temperature difference (ΔTmax). Under the discharge rates (C-rates) of 2C and the convective heat transfer coefficient of h = 15 W m−2 K−1, neglecting TCR underestimates the radial ΔTmax of the 46,800 cell by about 2.7 °C, and assuming isotropic λ overestimates the in-plane ΔTmax of the pouch cell with comparable capacity from about 2 °C to nearly 6 °C. A direct comparison is conducted between a 46,800 cell and a pouch cell with comparable capacity, and parametric analyses are performed over C-rates, h, and cell sizes. Under 2C and h = 15 W m−2 K−1, the 46,800 cell reaches a remarkable radial ΔTmax of 7.3 °C. The pouch cells exhibit coupled in-plane and through-plane gradients whose dominance shifts from in-plane under air cooling to through-plane under liquid cooling. For both formats, the ΔTmax increases with C-rates and cell sizes. These results can serve as a controlled structural and parametric sensitivity analysis that provides a basis for thermal design of lithium-ion batteries.

Leveraging the close-contact melting (CCM) process promises fast heat charging for latent heat storage systems using energy-intensive phase change materials (PCMs). However, understanding such complex phase-transition systems involving numerous variables entails extensive experimental and simulation efforts. Here, we introduce a data-driven machine learning approach to achieve associations between input variables and output objectives. Following model training, the Extra Tree model shows good reliability in predicting CCM melting times (R2=0.88 and RMSE=0.3031 on the test dataset), outperforming the Decision Tree and Random Forest models. Using SHAP interpretability analysis, the degree of superheat, PCM container size, and initial temperature exert a notable influence on the melting time. According to self-developed erythritol CCM simulations, increasing superheat thickens the bottom liquid film, but reduces melting time by 1/3. Moreover, numerical results reveal that the bottom liquid film is squeezed and flows upwards along the side walls. PCM container size analysis shows that larger containers exhibit stronger natural convection along the side walls, but also take longer to melt. Container size markedly affects specific power, indicating that performance comparisons should consider size effects. A small difference in initial temperature exerts little effect on melting. When the size is 30×30 mm and the superheat is 30°C, the melting time is just 7.56 min. This study combines machine learning and numerical simulation for CCM research and explores the fast-charging erythritol in mid-temperature latent heat storage.

Erythritol, with a high melting enthalpy of similar to 340 J g(-1), is promising for mid-temperature thermal energy storage, but suffers from poor thermal stability due to oxidative chain reactions on its hydroxyl groups. Here, we tackle this practical challenge by proposing a radical-trapping-based dual-protection strategy that combines nitrogen and an antioxidant. We identify the best antioxidant (AO1010), and show that solely using the antioxidant or nitrogen can only achieve limited improvements, because the unavoidable tiny amount of leaked oxygen molecules from the nitrogen "barrier" can still trigger the chain reactions, and the antioxidant "soldiers" will be constantly depleted upon trapping the intermediate radicals. Using this "barrier + soldier" strategy, we achieve an ultralong lifespan for erythritol with >83% enthalpy retention after heating at 150 degrees C for 10 000 hours and >90% after 1000 cycles. This strategy enables erythritol-based thermal batteries to have comparable capacity and lifespan to commercial lithium batteries, and can be generalizable to the broad sugar alcohol family and other organic PCMs.

In situ thermally enhanced bioremediation (ISTEB) is a promising approach for remediating contaminated soil and groundwater, yet comprehensive quantitative sustainability assessments of its sustainability remain scarce, especially for field-scale applications using hot water injection (TEB-HW) or thermal conductive heating (TEB-TCH). This study addressed this gap by developing the first fully quantitative sustainability framework integrating life cycle assessment (LCA) with best management practices (BMPs), comprising 108 indicators derived from extensive literature review and policy analysis. Using full-scale operational data from ISTEB implementations, we quantified the environmental, economic, and social performance of TEB-HW and TEB-TCH relative to conventional thermal treatment (TCH only). Results show that compared with TCH only, TEB-HW and TEB-TCH reduced carbon emissions by 78% and 31%, and achieved cost savings of 72% and 38%, while also improving community engagement and satisfaction. Normalized multi-criteria sustainability scores indicate overall performance gains of 31% and 13% compared to TCH only. Further optimization of BMPs, such as electric vehicle transport, green injectates, and renewable energy integration, could enhance ISTEB sustainability by up to 45%. These findings provide novel evidence for the practical viability and environmental benefits of ISTEB, offering actionable strategies for low-carbon, cost-effective, and socially acceptable remediation that align with sustainable production principles and contribute toward global net-zero carbon goals in contaminated site management.

Understanding thermal transport within Lithium-ion batteries (LIBs) is critical for accurate temperature prediction toward thermal safety diagnosis. This study systematically investigates the temperature-dependent intrinsic thermal conductivity (k) and interfacial thermal resistance (R-c) of LIB components (namely the anode, cathode, and separator) via an offline, layer-resolved experimental platform over a temperature range of 0-80 degrees C. Our results reveal that the intrinsic k of all components generally increases with temperature, with the anode exhibiting the most pronounced rise, and that R-c exhibits no clear trends. A comparative analysis shows that the interfacial contributions become increasingly dominant with temperature, up to similar to 50 % at 80 degrees C, shifting the limiting mechanism of thermal transport from bulk to interface. The study also differentiates between testing temperature (T-test) and cycling temperature (T-cycle). Measurements on fresh cells under controlled conditions suggest that the thermal behavior is predominantly governed by T-test, with limited influence from prior T-cycle within the studied temperature range. Comparisons with literature data for full-cell k reveal inconsistencies in temperature trends, underscoring the need for structure-resolved and aging-aware thermal characterizations. This work provides a foundational dataset for improving the fidelity of LIB thermal modeling and offers insights into the layered thermal mechanisms governing heat dissipation in LIBs.

The limitations of ion transport kinetics in conventional electrolytes, particularly under extreme operating conditions, arise from suboptimal solvation structures and inefficient charge carrier utilization. Here, we present strategic electrolyte design that reconfigures Li⁺ coordination geometry by modulating intermolecular interactions and solvent molecule volume, fundamentally overcoming these transport constraints. By incorporating an optimized moderator with a low dipole moment and small molecular size, extensive anion aggregation is effectively disrupted into compact ion conduction domains, simultaneously increasing the number of free charge carriers and enhancing ion mobility. Guided by this principle, the designed electrolyte with dichloromethane (85.11 Å, 2.36 Debye) exhibits rapid Li+ hopping between adjacent coordination sites (152.3 ps for acetonitrile and 115.7 ps for FSI-). This electrolyte enables stable cycling of 1.0 Ah 4.5 V graphite (3.13 mAh cm-2)||LiNi0.8Mn0.1Co0.1O2 (2.85 mAh cm-2) pouch cells, delivering 0.87 Ah at -40 °C, surpassing commercial carbonate-based electrolytes, which fail to retain reversible capacity at this temperature. This study establishes fundamental principles for fast ion-transport electrolytes, paving the way for next-generation Li-ion batteries under extreme scenarios.

Industrial activities, such as alumina production, generate abundant gaseous waste heat and pollutants, but their utilization efficiency is limited by its temperature grade and NOx. Latent heat storage (LHS) technology, which employs energy-intensive phase-change materials (PCMs) to recover waste heat from flue gases and release it for future use, can improve thermal efficiency via the heat-to-heat mode. Here, machine learning models, including Decision Trees, Random Forests, LightGBM, and Extra Tree, were developed based on 7 system variables to predict heat charging performance, with the Extra Tree model performing the best, as verified by experiments. The interpretive results indicate that the PCM volume, heat-transfer area, and degree of superheat primarily determine the heat charging time. Inspired by the lantern structure, a novel LHS system was proposed and analyzed for the Nusselt number and pressure drop through steady-state simulations. After analyzing various parameters including the fin count, PCM type, gas velocity, and fin angle, transient PCM melting simulations were then conducted by connecting the thermal boundaries to evaluate the optimal design. Compared to traditional designs, the proposed design reduces melting time by 43%, reduces gas-side thermal resistance by 49%, and maintains total thermal resistance at 5 °C/W. The state of charge (SOC) increases proportionally with time (SOC ∝ t), and reaches a high specific power of 139 W/kg and high latent heat storage capacity of 333.7 kJ/kg. Upon integration of machine learning, decoupled numerical simulations, thermal energy storage design, and system economic analysis, this work further unlocks the potential of using thermal storage to improve the effectiveness of industrial waste heat recovery.

Waste heat recovery and utilization of low-grade flue gases, e.g., from metallurgical industry, enable improvement of energy efficiency toward decarbonization of various industrial sectors. However, the thermal capacity and efficiency of existing waste heat recovery techniques remain low, primarily due to the poor thermal design and the absence of energy-intensive materials for heat storage. Here, we propose an innovative latent heat thermal energy storage (LHTES) system with annular externally finned tubes, and simulate the heat transfer and flow dynamics of the flue gas cross-flow under various actual flow velocities, tube diameters, tube spacings, and fin spacings through three-dimensional modeling. Using response surface method, we reveal that flow velocity apparently affects heat transfer, and that tube diameter greatly impacts flue gas pressure drop and average temperature, followed by establishment of the intricate relationship between responses and design parameters. Using nondominated sorting genetic algorithm II, we obtain the Pareto front for three objectives and determine the optimal point by entropy weight TOPSIS decision-making, simultaneously optimizing the heat transfer coefficient of 32.33 W/(m2 & sdot;K), pressure drop of 152.66 Pa, and mean flue gas temperature of 147.23 degrees C. The noticeable heat transfer difference between the tube's upper and lower regions is considered in transient modeling, which induces stronger natural convection and a higher melting rate in the upper region. The state of charging (SOC) in the finned tubes represents two stages (SOC proportional to t and SOC proportional to t0.7), and the thermal resistance is reduced more than 60-fold compared to that of unfinned tubes. The presented methodology and results can serve as guidelines for the design and implementation of high-performance LHTES systems for waste heat recovery of industrial flue gases.

Solar heating in high-irradiance, cold regions like the Tibetan Plateau and Iberian Peninsula often struggles with severe seasonal supply-demand mismatches. To address this, we propose a solar PV/T system integrated with seasonal latent heat storage using highly-supercooled phase change materials. Unlike sensible heat storage, this solution offers superior energy density and greater flexibility, leveraging stable supercooling to store heat with minimal insulation. Optimizations based on the Hangzhou indicated the system achieved a competitive levelized cost of electricity of 0.68 CNY/kWh, while a demonstration setup has been in continuous operation. Crucially, applying this system to the target region of Lhasa yields a global warming potential nearly 30% lower than in Hangzhou. Given the strong climatic parallels between Lhasa and Madrid, this study demonstrates the technology’s promising scalable potential for decarbonized heating in Iberia.

Understanding dynamic wetting behavior under extreme temperatures and pressures is critical for applications such as enhanced oil recovery and nuclear power systems. This study systematically investigates the effects of temperature and pressure on the dynamic advancing and receding contact angles (DACA and DRCA) of water on roughened 304 stainless steel surfaces under low capillary number conditions (Ca < 10-5). Six surfaces with varying roughness (0.017 μm ≤ Sa ≤ 0.453 μm) were characterized, and experiments were conducted at temperatures up to 100 °C and pressures up to 10 MPa. The results show that the DACA generally increases with both temperature and pressure. Notably, a distinct roughness-pressure coupling effect was identified: while the DACA on smooth surfaces increased linearly with pressure, rough surfaces exhibited nonlinear responses. This nonlinearity is attributed to pressure-induced transitions in the wetting state within surface textures. In contrast, the DRCA on rough surfaces remained low and independent of thermodynamic conditions due to dominant pinning by macroscopic defects. However, on the ultrasmooth surface, elevated temperature activated a pinning mechanism, sharply reducing the DRCA and shifting the receding mode from constant contact angle to a mixed mode. These findings offer fundamental insights into dynamic wetting under extreme conditions, aiding the design of functional surfaces for high-pressure and high-temperature environments.

System-level application of phase-change cooling (PCC) to production-scale automotive permanent magnet synchronous motors (PMSMs) remains insufficiently understood, especially when the compact production geometry and original cooling-flow-path constraints must be retained. This study addresses this gap by numerically evaluating an electronic-fluorinated-fluid PCC system for a mass-produced 240 kW PMSM under peak-power operation. For the investigated motor, the conventional oil-cooling method reaches a maximum winding temperature of 169 degrees C after 50 s, indicating that the peak-power duration is limited by the end-winding hotspot. An oil-cooling conjugate heat-transfer model was first established in STAR-CCM+ using production operating data and a mesh-independence study; the model was then extended to a volume-fraction-based liquid-vapor PCC framework with wall boiling. The effects of coolant boiling point and system flow rate on vapor migration, component-level temperature rise, and peak-power duration were analyzed. For the copper-winding motor, PCC reduces the maximum motor temperature by 9-32 degrees C compared with oil cooling and extends the peak-power duration by 7.6%-63.6%. For an aluminum-winding motor under the same 240 kW condition, PCC lowers the maximum winding temperature from 219 degrees C to 154 degrees C and increases the peak-power duration by 233%. The results reveal that phase change is beneficial in the spacious end-winding region where vapor can be discharged, but vapor retention in narrow stator back-side passages can deteriorate local heat transfer. These findings demonstrate the system-level feasibility and limitations of PCC for production-scale high-performance automotive PMSMs and provide design guidance for coolant boiling point, flow rate, vapor-discharge paths, and aluminum-winding applications.

Sodium (Na)-ion batteries (NIBs) are emerging as a promising solution for large scale energy storage applications. Among various cathode chemistries, O3-phase layered transition-metal oxides stand out for their high energy density, yet their practical deployment is restricted by intricate phase transitions that induce lattice distortion, stress accumulation, and particle cracking, leading to rapid performance degradation. Here, we propose a temperature-mediated strain-management strategy to improve the phase reversibility and structural stability of O3-phase oxide cathodes. Comprehensive structural and dynamic analyses reveal that optimal thermal regulation facilitates lattice strain release, mitigates detrimental stress accumulation that drives irreversible phase transitions, and accelerates Na+ diffusion kinetics. As a result, structural degradation, transition-metal dissolution, and capacity fading are effectively suppressed. This work provides a new perspective on employing external fields to overcome the intrinsic structural instability of layered oxides, offering fundamental insights for rational cathode design and reliable operation of practical NIBs for energy storage.

This paper investigates the close-contact melting (CCM) of phase change materials on effective slip surfaces enabled by superhydrophobic microgroove structures. The CCM of ice cubes on hydrophobic grooved surfaces with different parameters is measured, and a modified theoretical framework is developed to account for the spatial variation of the liquid-gas meniscus induced by the pressure gradient along the flow direction. The modified model predicts lower melting rates, attributed to the smaller equivalent average meniscus curvature (i.e., a flatter meniscus), which reduces the slip length and slows the drainage of the melt film. The experimental results validate that the heat transfer of CCM can be further enhanced under specific groove geometry conditions for the first time and confirm the predictions of the modified model. A detailed test of varying superheat conditions was conducted to verify the applicability of the model. These findings provide experimental support and application potential for using slippery surfaces to enhance CCM under specific conditions, which is of great significance for scientific exploration and engineering applications, including thermal management and thermal energy storage.