Air conditioning and heat pump systems account for a substantial portion of global energy consumption. Screening for superior and environmentally friendly refrigerants presents a viable solution to mitigate global energy and environmental challenges. Hydrofluoroolefins (HFOs) are considered potential fourth-generation refrigerants due to their environmental friendliness and favorable thermodynamic properties. In this work, we proposed a hybrid physics-data model for HFO compounds to enable accurate thermodynamic properties prediction solely from their molecular structure. The deviations for critical temperature, critical pressure, and critical density are 1.79 %, 2.51 %, and 2.14 %, respectively. For single-phase properties, the deviations are 0.73 % for vapor density, 1.49 % for liquid density, 3.37 % for liquid entropy, and 1.85 % for liquid enthalpy. Using this prediction framework, we performed a detailed screening of potential HFO refrigerants. The reliability of the framework was validated by comparing its result with those calculated through published Helmholtz equation of states, yielding deviations less than 5 % in coefficient of performance. Three new HFO molecules are identified in this work. Among them, (Z)-1,2-difluoroethene demonstrates significantly improved performance compared to existing HFO refrigerants.

Pumped Thermal Electricity Storage is a promising large-scale energy storage technology. However, its roundtrip efficiency when driven by waste heat is fundamentally limited by the heat pump's maximum temperature. While solar integration has been explored, it often fails to substantially surpass this ceiling. This study proposes a novel hybrid pumped thermal electricity storage system that introduces a cascaded energy utilization approach, synergistically coupling industrial waste heat with concentrated solar thermal energy. The system innovatively uses the heat pump for intermediate temperature elevation and then employs high-grade solar heat to boost the storage temperature to a significantly higher level, creating a thermally stratified reservoir that enables a better match between energy quality and power conversion. A dual-pressure organic Rankine cycle is then adopted to effectively convert this stratified energy into electricity through staged expansion. A thorough investigation and multi-objective optimization of working fluids and system parameters were conducted, evaluating performance in a practical factory scenario. Compared to a waste-heat-only system, the hybrid system enhances round-trip efficiency by 42.45%-91.29% and energy density by 18.08%-41.34%. Although solar collectors increase the levelized cost of storage initially, the cost shows diminishing marginal growth with scale. The cyclopentanecyclopentane fluid pair was identified as optimal, achieving a 95.87% round-trip efficiency, 6.36 kWh/m3 energy density, and a 0.2065 $/kWh levelized cost of storage. This integrated design effectively decouples the organic Rankine cycle performance from the heat pump constraint, demonstrating a viable pathway toward highefficiency thermal energy storage.

Hydrofluoroolefins are considered the most promising next-generation refrigerants due to their extremely low global warming potential values, which can effectively mitigate the global warming effect. However, the lack of reliable thermodynamic data hinders the discovery and application of newer and superior hydrofluoroolefin refrigerants. In this work, integrating the strengths of theoretical method and data-driven method, we proposed a neural network extended corresponding state model to predict the residual thermodynamic properties of hydrofluoroolefin refrigerants. The innovation is that the fluids are characterized through their microscopic molecular structures by the inclusion of graph neural network module and the specialized design of model architecture to enhance its generalization ability. The proposed model is trained using the highly accurate data of available known fluids, and evaluated via the leave-one-out cross-validation method. Compared to conventional extended corresponding state models or cubic equation of state, the proposed model shows significantly improved accuracy for density and energy properties in liquid and supercritical regions, with average absolute deviation of 1.49 % (liquid) and 2.42 % (supercritical) for density, 3.37 % and 2.50 % for residual entropy, 1.85 % and 1.34 % for residual enthalpy. These results demonstrate the effectiveness of embedding physics knowledge into the machine learning model. The proposed neural network extended corresponding state model is expected to significantly accelerate the discovery of novel hydrofluoroolefin refrigerants.

Accurate State of Health estimation for lithium-ion batteries remains challenging due to complex degradation mechanisms and insufficient optimization strategies. This paper proposes an enhanced Whale Optimization Algorithm optimized Convolutional Neural Network-Bidirectional Long Short Term Memory Attention model that advances the field through several methodological contributions. The methodology systematically extracts seven health indicators from incremental capacity curves and validates them through grey relational analysis, demonstrating correlation coefficients of 0.65-0.96 with State of Health. A squeeze and excitation attention mechanism dynamically recalibrates feature weights to emphasize critical degradation information. The research enhances the Whale Optimization Algorithm through dual-strategy population initialization combining lens imaging opposition-based learning and sinusoidal chaos mapping, adaptive parameter adjustment utilizing population improvement rate feedback, and hybrid mutation strategy integrating gradient and fractional-order Levy perturbations. The enhanced optimization algorithm deeply integrates with the neural network architecture to simultaneously optimize hyperparameters and connection weights. Experimental validation on multiple public datasets demonstrates superior performance with mean absolute error of 0.0054, root mean square error of 0.0069, and coefficient of determination of 0.9924. The model maintains robust accuracy even under 50 % incomplete charging scenarios, achieving coefficient of determination above 0.96, which validates its practical applicability.

Pesticide spraying is a primary approach for the chemical management of pests, diseases, and weeds. The efficient design of formulations and their accurate application constitute a systems engineering problem that combines formulation chemistry, application technology, and agronomic practice. The droplet size distribution (DSD), which is determined by the physicochemical properties of the formulation during atomization, has a direct influence on deposition efficiency, drift potential, and control performance. Conventional atomization indicators, such as volume median diameter (VMD), Sauter mean diameter (D32), and relative span (RS), do not adequately provide a quantitative connection between the physicochemical properties of formulations and the droplet size spectrum needed for effective biological control. A comprehensive atomization quality index that incorporates formulation properties and the optimal droplet size is therefore urgently required. To fill this gap, five atomization parameters, relative diffusion ratio (RD), RS, fractal dimension (FD), drift droplet proportion (V150, ≤ 150 μm diameter), and Dv0.5 (also referred to as the VMD), were chosen to construct the atomization bridging index (ABI). The ABI allows a comprehensive quantitative assessment of atomization quality and shows a strong correlation with the physicochemical microstructure of the formulation. The analysis indicates that micelle–polymer complexes generated through polymer–surfactant interactions markedly improve the ABI by jointly lowering dynamic surface tension (DST) and increasing viscosity. The evaluation findings show that the associative polyethylene oxide (PEO)/sodium dodecyl sulfate (SDS) system demonstrates outstanding performance over a broad pressure range. At 250 kPa, the PEO/SDS system at 1× the critical micelle concentration (CMC) reaches the highest ABI value, corresponding to the Class I category, and is therefore recommended as the optimal spraying system. Overall, ABI establishes a robust physicochemical-spray linkage framework and provides new guidance for identifying key formulation parameters in pesticide adjuvant design.

Growing concerns about energy consumption and its connection to global warming highlight the importance of developing sustainable buildings. Shading devices are integral elements of buildings, developed to prevent high-penetrating sunlight. By effectively redirecting solar radiation, dynamic hybrid shadings can significantly lower energy consumption, improve useful daylighting, and increase the visibility of the view to outside scenery. However, the automated shadings based on widely used slat inclination control and the plane profile slats are inadequate for addressing issues for uniformly distributed daylighting. This study introduces an illuminance-driven vertical deployment and retraction strategy for trapezoidal split-facade louvers, integrating daylight uniformity, glare control, and view visibility within a multi-objective optimization framework. Simulations were performed through Ladybug Tools, Radiance, and an evolutionary algorithm (SPEA-2). The viability of proposed hybrid shadings was assessed for deep office spaces by increasing the room depth from 5.0 m to 8.0 m. The optimization of slat parameters, including length, tilt, and reflectance at the upper and lower sections of the split façade, was conducted in different climates. The automated slats based on partial vertical deployment and retraction of trapezoid hybrid shading devices may target above 90% coverage of useful daylight illuminance (focusing on UDI500∼1000 lx) to achieve the recommended level of daylighting as an alternative to artificial lights between 09:00 and 16:00. At the same time, illuminance uniformity (Uo) remains above 0.40, whereas Daylight Glare Probability (DGP) is below 0.40. The visibility percentage increases to 70% in the morning and afternoon, when slats tend to be retracted, while it decreases to 40% in mid-day when slats are deployed. The results highlight the considerable efficacy of advanced trapezoidal‐profile louver shading systems in optimizing daylight distribution and occupants' comfort.

This study proposes a novel variable cross-section upper-converging cathode flow field (CFF) for enhancing proton exchange membrane fuel cell (PEMFC) performance. First, the overall performance of PEMFC with four distinct CFFs is compared. Results demonstrate that the upper-converging CFF delivers the peak power density of 0.630 W/cm2, representing improvements of 3.28%, 3.28% and 21.39% over conventional parallel, wave and converging CFFs, respectively. Furthermore, as current density increases, the performance gap widens. Subsequently, comprehensive heat and mass transfer analysis, including dynamic water removal capability simulated via the volume of fluid method, is conducted to elucidate the performance differences. These analyses reveal that variable cross-section designs promote oxygen transport via enhanced convective diffusion, with the upper-converging CFF exhibiting exceptional heat and mass transfer characteristics. Specifically, it demonstrates superior oxygen concentration, exceptional water removal capability, and enhanced uniformity in temperature distribution. Finally, parametric analysis is performed to investigate key variables identified, particularly the effect of channel-gas diffusion layer contact area on cell performance is quantified for the first time. Results indicate that matching cooling water and reactant gas inlet temperatures enhances performance, while current density initially rises rapidly with increasing Reynolds number before stabilizing. Optimal relative humidity varies non-monotonically with operating voltage, exhibiting lower values at both low and high voltages. Within the tested range, the channel-gas diffusion layer contact area exhibits a nearly linear relationship with current density while inversely correlating with pressure loss.

High-temperature heat pumps can upgrade low-grade industrial waste heat but face multi-level heat sources and large temperature lifts. A two-stage compression heat pump with intermediate cooling (TSHP-IC) is proposed to combine staged heat absorption with two-stage compression, together with an enhanced internal-heat-exchanger configuration (TSHP-IC-IHX). A steady-state thermodynamic model is developed for low-GWP zeotropic mixtures, particularly R1234ze(Z)/R1336mzz(Z). At waste-heat-source temperatures of 85 and 55 °C and heating temperatures of 100–120 °C, the working fluids are independently optimized for the proposed systems, a cascade dual-heat-source heat pump (CHP-DHR), and a parallel single-stage heat pump (PSHP). At 100 °C, TSHP-IC achieves a COP of 4.15, 2.45 % and 4.72 % higher than CHP-DHR and PSHP, respectively. Its performance is comparable to CHP-DHR at 110 °C and 1.67 % lower at 120 °C. After configuration-specific composition optimization, TSHP-IC-IHX reaches a COP of 4.55 at 100 °C and exceeds the correspondingly optimized CHP-DHR-HIHX by 4.94 %–6.31 % throughout the investigated range. Matched diagnostic calculations show that the IHX increases compressor-inlet superheat, reduces pre-throttling enthalpy and flash-vapor fraction, and expands the feasible composition range. At the representative heating temperature of 110 °C, the IHX-assisted configuration at its selected composition exhibits approximately 33 % lower total exergy destruction and an exergy-efficiency increase from 0.66 to 0.76 relative to the selected TSHP-IC case. These results demonstrate that combining two-stage compression with internal heat recovery is effective for large-temperature-lift, multi-level industrial waste heat utilization.

BACKGROUND:Carbendazim (CBZ), is a benzimidazole fungicide and widely used for controlling fruit and vegetable diseases, which poses significant risks to human health due to its neurotoxicity, endocrine disruption, and reproductive toxicity. Sensitive and rapid monitoring of carbendazim residues in food is essential for ensuring food safety. Among the numerous developed methods, electrochemical sensing stands out due to its simplicity of operation, low cost, and capability for on-site detection. Its key point is to construct a high-performance sensing interface. Nevertheless, these interfaces still face some limitations, such as inadequate conductivity, relatively low sensitivity, and narrow linear range. RESULTS:Herein, graphene supported iron nanoparticles encapsulated nitrogen-doped carbon nanotubes (Fe@N-CNTs) were constructed. The MOF-derived "tube-bridge" CNTs architecture, enhanced by N-doping, ensures high conductivity and optimized electron transfer pathways. Encapsulated iron nanoparticles act as shielded yet accessible redox-active centers, enhancing catalytic specificity. Graphene prevents CNTs stacking, maximizing active site exposure and interfacial charge transfer. This synergistic design significantly boosts the electrochemical active surface area, electron transfer kinetics, and electrocatalytic activity. As a result, a highly sensitive electrochemical sensing platform for CBZ has been successfully constructed. An irreversible two-electron and two-proton process takes place on the surface of Fe@N-CNTs/Graphene/GCE. The composite demonstrated exceptional performance for CBZ detection, achieving a broad linear range (0.001-7.0 μM), and an ultralow detection limit (0.56 nM). Furthermore, the sensor exhibited superior repeatability, stability, and selectivity. Its practical applicability was successfully validated through the accurate quantification of CBZ residues in medicinal herbs and vegetables (recoveries of 98.58 %-101.7 %). SIGNIFICANCE:This work offering a robust solution for monitoring ultra-low concentrations CBZ residues in complex food matrices. This innovative technology provides essential support for combating pesticide misuse while safeguarding public health and preserving ecological integrity related to CBZ contamination.

The basic thermophysical properties and cycle performances of refrigerant mixtures are compared and analyzed in automotive heat pumps.The following mixtures are analyzed:R134a,R1234yf,R290,R410A,and eight mixtures containing flame retardant R1216,including five binary mixtures comprising R1234ze(E),R152a,R1234yf,R290,and R127 with R1216 and three ternary mixtures,R1234yf/R161/R1216,R134a/R161/R1216,and R1123/R32/R1216.The results show that all the mixtures are environmentally friendly and stable in operation,with Global Warming Potential(GWP)values lower than 150 and temperature glide lower than 3℃.R152a/R1216(60/40)has similar thermophysical properties and cycle performance when compared to R134a and exhibits an approximately 11％increase in the heating coefficient of performance(COP).R290/R1216(60/40),R1270/R1216(60/40),R1234yf/R161/R1216(40/40/20),and R134a/R161/R1216(10/50/40)exhibit higher volumetric cooling/heating capacities,ranging from 113％to 180％that of R134a.R1123/R32/R1216(60/20/20)has a lower cooling COP than R134a and R410A by 84％ and 93％,respectively.However,it has the highest volumetric performance,outperforming R134a and R410A by approximately 104％and 109％,respectively.These refrigerant mixtures may be applied to small mobile cooling systems such as electric-vehicle heat pumps;however,further experimental validation is necessary for their application and promotion.

Tunnel fires pose significant energy safety risks due to the narrow and restricted spaces and complex ventilation conditions. A typical scenario is a train roof fire triggered by a pantograph malfunction, which not only releases substantial thermal energy but also results in the wastage of electrical and fuel energy. This study focuses on the impact of the coupled lateral smoke exhaust system, which combines longitudinal ventilation and lateral exhaust, on fire heat release rate and flow field evolution during train fires, while also exploring an AI-based approach for predicting train fire dynamics. Compared with traditional ground fires in tunnels, the burning rate of train roof fires in interval tunnels shows non-monotonic changes, and the evolution characteristics of the flow field also differ significantly. To reveal the prediction process of the full-period changes in tunnel fires over time and overcome the temporal limitations of traditional fire physical models, this paper proposes a full-period, real-time prediction framework and the novel algorithm for heat release rate (HRR) and ceiling heat flux profile of tunnel fires using deep learning. The framework integrates ResNet-18 and ViT-Small for flame image feature extraction, with physical prior information incorporated as auxiliary input features to enhance the model's predictive performance and physical interpretability. This enables rapid and accurate full-period prediction of the HRR and the heat flux profile beneath the tunnel ceiling under the coupled conditions of longitudinal ventilation and lateral extraction in a tunnel.

Design and synthesis of novel magnetic lanthanide-based frameworks for low-temperature magnetic refrigerants with high entropy change is still attractive and challenging. In this work, two isostructural Ln-MOFs with 3D network, namely, [NH2(CH3)2Ln(C2O4)2(H2O)]n & sdot;3H2O (Ln = Gd for 1, Dy for 2) based on oxalate ligand have been solvothermally synthesized and structurally characterized. Structural analysis indicates that the Ln-MOFs are a 3D anionic framework featuring interconnected 1D channels composed of [Ln(H2O)]3+ nodes bridged by C2O42-linkers. DC magnetic behavior revealed the presence of weak intramolecular antiferromagnetic interactions between the metal ions in 1 and 2. Significantly, the GdIII-MOF displayed a high magnetocaloric effect with the value of maximum entropy change of -Delta Sm = 40.16 J kg-1 K-1 at 2 K and Delta H = 7 T. Despite operating at 2 K and 3 T, the -Delta Sm value of 27.87 J kg-1 K-1 exceeds that of commercial Gd3Ga5O12 (GGG) materials, indicating its potential as a low-temperature magnetic refrigerant. The ac susceptibility measurements demonstrated a field-induced single-molecule magnet (SMM) behavior of DyIII analogue.

Reusing shipping containers for residential purposes offers a promising approach to address global energy consumption challenges from economic and environmental perspectives. This study parametrically designed hybrid louver shadings by combining fixed vertical triangular slats with variable-depth horizontal rectangular slats, offering a novel approach to shading prefabricated buildings. The energy consumption, daylighting performance, and visual comfort were assessed for various shading configurations. Results indicated that implementing the proposed hybrid louvers, featuring fixed vertical triangular slats and variable-depth horizontal rectangular slats, significantly reduced Energy Use Intensity (EUI) to 133.95 kWh/m2. Moreover, Useful daylight illuminance (UDI), Daylight Autonomy (DA), and Glare Autonomy (GA) values improved to 95.38%, 89.97%, and 91.16%, respectively. The study highlighted the potential of the proposed shading system to significantly reduce overall energy consumption across various ASHRAE climate zones, including Miami (1A), Guangzhou (2A), Melbourne (3C), Esperance (3C), San Diego (3A), and Milan (4A). Notably, energy reductions of up to 50.2% were projected for climates such as Miami (1A) and San Diego (3A). Furthermore, container buildings in warm climate zones exhibited a significantly lower EUI range of 76.58 to 91.95 kWh/m². This study underscores the transformative potential of hybrid louver systems in promoting the widespread adoption of sustainable residential architecture, contributing to global sustainability efforts.

Herein, a novel pH-responsive adsorbent with selective adsorption effect on cationic and anionic dyes was further designed and prepared via radiation grafting in situ growth technique. The cheap, modifiable and benign natural renewable biomass loofah (LFs) was selected as the substrate, and then acrylic acid (AAc) was grafted onto the loofah substrate through electron beam (EB) radiation (grafting rate of 30.5 %). The introduction of -COOH effectively captured and fixed cobalt ions (Co2+), and zeolitic imidazolate framework-67 (ZIF-67) was grown in situ on the loofah surface with Co2+ as a metal center and 2-methylimidazole as the ligand, so a functional loofah-based adsorbent ZIF-67@LFs-AAc was obtained. The introduction of ZIF-67 significantly enhanced the adsorption efficiency and capability of biomass materials, and successfully combined the advantages of biomass and inorganic nanomaterials. The biosorbent is pH-responsive and can specifically adsorb anionic dyes in acidic setting. The equilibrium uptake capacity of Congo red (CR) is 433.9 mg/g at pH = 3. Cationic dyes can be selectively adsorbed under neutral and basic conditions, and the equilibrium uptake capacity of methylene blue (MB) is as high as 554.0 mg/g at pH = 7. When the addition of the ZIF-67@LFs-AAc was 1.0 g/L, the removed rates of MB and CR were 95.9 % and 91.8 %, respectively. With ZIF-67@LFs-AAc, the adsorption of dyes is promoted by electrostatic interaction, pore adsorption, 7C-7C interaction and hydrogen bond. In summary, the integration of MOFs with loofah can lead to the development of a highly efficient biosorbent for treating dyecontaining wastewater, thereby offering promising prospects for its application in water treatment.

To address the growing thermal loads of scramjet engines, a Coupled Transpiration Cooling Thermal Protection System (CTCTPS) integrated with self-driven cooling pipes is proposed. This system combines an S-shaped cooling pipe and a transpiration cooling structure to achieve self-driven and adaptive cooling. It harnesses the heat flux differences on the pipe wall to drive coolant flow inside the pipe for internal structure cooling, while the liquid water in the pipe evaporates or changes phase to provide coolant for transpiration cooling. In this research, different heat flux differences (0-500 W/m2) are used to explore their impacts on fluid flow, phase change, and heat transfer characteristics within the system. The study reveals that the system can remarkably enhance the overall cooling capacity. During the phase change stage, the cooling efficiency of the transpiration cooling structure surface is about 2.7 times that of the local circulation flow stage, and the heat transfer coefficient peaks at 88. By adjusting the heat flux difference, the system can optimize cooling time and coolant consumption. The system eliminates the need for external driving devices by leveraging natural convection induced by heat flux differences and effectively circumvents the instability issues caused by direct phase transitions in porous structures. This work paves a new pathway for comprehensive thermal management system of scramjet engine via the rational design of the CTCTPS with self-driven cooling pipes.

Compared with traditional electric heating dryers, heat pump dryers are more energy efficient and environmentally friendly. In this work, a novel heat pump dryer with zeotropic mixtures as working fluids and recuperators is studied and compared with the cycle using the corresponding pure working fluid. The effects of the evaporation temperature, and the components and mass fractions of the zeotropic mixtures on the performance of the system are investigated. After comprehensively considering various performance coefficients, this work selects a CO2/R290 (mass fraction of 20/80) mixture as the optimal working fluid of the heat pump dryer system. Compared with R134a, it significantly improves the coefficient of performance (COP), specific moisture extraction rate (SMER), volumetric heating capacity (VHC), and pressure ratio (PR), with maximum performance improvements of 33.66 %, 41.50 %, 181.44 %, and 46.55 %, respectively. The zeotropic mixture also has significant performance advantages in terms of less charge and exergy destruction. Moreover, the addition of CO2 as a nonflammable refrigerant to the components reduces the flammability of the working fluid compared with that of pure R290, which improves safety in practical applications.

Office buildings present significant potential for energy savings using innovative shading systems, particularly given their extensive daytime usage. However, comprehensive studies that integrate automated shading systems with multi-objective optimization (MOO) to balance visual comfort, energy savings, and daylight distribution are still needed. This research aims to enhance daylighting performance and reduce dependence on artificial lighting by employing MOO techniques. It focuses on automated and split-controlled louvers that adjust slat positions horizontally across the top, middle, and bottom sections of the facade to optimize work plane illuminance under varying conditions. Different illuminance ranges were reviewed for visual comfort in relation to Useful Daylight Illuminance (UDI), with a focus on UDI500 similar to 1000 lx for improved daylighting. The study parametrically modeled automatic trapezoid-profile louver shading devices applied to the climates of Miami, Guangzhou, and Amman. Ladybug Tools, integrated with Grasshopper and Rhinoceros 3D, were used to connect Radiance and Octopus to identify optimal shading solutions. The optimal slat length and angle were determined using MOO based on SPEA2 with hyper-mutation. The fixed exterior trapezoid shadings achieve at least 70 % of the optimal illuminance between 10:00 and 15:00 on typical dates. The newly introduced dynamic louvers, based on hourly openness level for the top, middle, and bottom sections of the facade, achieved at least 98 % coverage within the UDI500 similar to 1000 lx range. Monthly variations suggest that an illuminance uniformity above 0.6 can be achieved, along with 90 % coverage of UDI500 similar to 1000 lx. The Daylight Glare Probability (DGP) index remained below 0.35 for the camera positioned at the back and below 0.4 at the center of the office space, indicating imperceptible and perceptible glare, respectively.

CO2-based binary mixtures offer superior thermodynamic advantages and environmental benefits compared to alternative working fluids. Enthalpy and entropy are essential in thermodynamic analysis, necessitating the availability of vapor–liquid equilibrium data. The static thermostatic analysis system accurately measures the mixtures’ temperature, pressure, and molar fractions. We carry out five temperatures at 283.15 K to 323.15 K while maintaining a pressure of approximately 6.38 MPa. Two electromagnetic capillary samplers effectively extract working fluids from the equilibrium cell, facilitating precise analysis using a gas chromatograph. The standard measurement uncertainties of experimental temperature, mole fractions, and pressure are determined at 0.06 K, 0.004, and 0.002 MPa, ensuring precise and reliable data for our analysis. The experimental data we gathered has undergone extensive analysis and modeling using the PR + WS + NRTL model to offer a comprehensive insight into the system's behavior. The AARDp value is 0.81

Multifunctional metamaterials have emerged as a transformative platform for controlling multi-physical fields, promising applications in intelligent manufacturing, flexible electronics, thermal management, and energy conversion. However, conventional metamaterial designs typically prioritize optimizing single-field responses, constraining their adaptability and functional integration potential in complex multi-physics scenarios where coordinated regulation of multiple fields is required. Here, a V-shaped 3D electrothermal dual-function metamaterial (V-ETDFM) architecture is proposed, enabling efficient and reconfigurable control of both electric and thermal transport. By expanding conduction pathways into 3D space, the proposed V-shaped structure introduces additional degrees of freedom, enhancing its functional integration and adaptability. Through theoretical and numerical analysis, the feasibility of dynamically controlling cloak parameters, including size, shape, and spatial positioning, is demonstrated by reversibly stretching and compressing the V-shaped framework based on transformation principles that maintain effective parameter invariance. Experimentally, a series of electrothermal cloaks with varying cloaked regions are fabricated to validate key design principles, confirming the static properties of the theoretical framework, while the implementation of real-time dynamic tuning presents an avenue for future exploration. The work establishes a novel design strategy for electrothermal multifunctional metamaterials and provides a foundational theoretical framework for flexible and reconfigurable multi-physics materials.

As a new type of energy storage technology using thermal energy, the Carnot battery (CB) is one of the most promising large-scale energy storage technologies due to its unlimited geographical conditions, simple structure, and high energy storage density. Previous research has mainly focused on the individual analysis of the working fluid or the conventional CB system, and the comprehensive thermal economy analysis of the system is lacking. In this work, a novel CB system with segmented energy storage using zeotropic working fluids is proposed, and the effects of the working fluid mass fraction, waste heat temperature and heat storage temperature on system performance are investigated. The multi-objective optimization problem of maximizing the power recovery efficiency and minimizing the initial investment cost is studied, and systematic Pareto-optimal solutions are obtained. The novelty of this work is the use of segmented condensation at the saturated liquid phase point of the working fluids. The temperature matching of the heat exchanger is modified by adjusting the mass flow rate of the heat storage water to reduce heat transfer exergy losses and improve the system performance. Compared with the conventional CB system, the novel system improves the power recovery efficiency by 3.31-24.07 % and the economic index, the levelized cost of storage (LCOS) by 2.87-17.25 %. The zeotropic working fluid R245fa/ pentane (mass fraction of 40/60) shows the best thermal performance, with a power recovery efficiency of 74.13 %, which is 23.51 % greater than that of pure R245fa and 18.97 % greater than that of pure pentane. The zeotropic working fluid R245fa/pentane (40/60) achieves the minimum LCOS of 0.213 $/kWh at a waste heat temperature of 80.0 degrees C and a storage temperature of 94.2 degrees C, which is 8.06 % higher than the LCOS of 0.232 $/kWh for pure pentane, and 10.83 % higher than the LCOS of 0.239 $/kWh for pure R245fa. The selection of a zeotropic working fluid with an appropriate temperature glide can effectively improve the thermal and economic performance of the system.