While atomically dispersed Fe-N-C catalysts represent a compelling nonplatinum alternative for the oxygen reduction reaction (ORR), their practical deployment in proton-exchange membrane fuel cells (PEMFCs) remains severely constrained by a poorly defined catalyst-ionomer-reactant triple-phase interface, which drastically impedes efficient proton transfer within the cathode catalyst layer. Herein, we report a rational interfacial microenvironment engineering strategy that exploits noncovalent interactions between oxygenated functional groups on carbon nanotubes (CNTs) and ionomer side chains to precisely modulate the catalyst-ionomer interfacial structure. The incorporation of oxygen-containing moieties effectively promotes water enrichment at the catalyst-ionomer interface, strengthens intermolecular interactions among water moieties, and facilitates the establishment of a hydrogen-bonded water network. This interconnected network significantly reduces proton transport resistance, boosting the proton conductivity of the Fe-N-C cathode layer by a factor of 2.3 relative to the conventional architecture. Coarse-grained molecular dynamics simulations substantiate that oxygen-functionalized CNTs facilitate long-range proton hopping, directly contributing to the measured conductivity enhancement. As a result, the optimized PEMFC delivers a remarkable peak power density of 1.63 W cm-2 and an exceptional current density of 53 mA cm-2 at 0.9ViR-free, surpassing the U.S. Department of Energy (DOE) 2025 target of 44 mA cm-2. This work establishes a generalized interfacial microenvironment modulation strategy to overcome proton transport limitations in nonplatinum ORR catalysts, opening a new avenue toward advanced fuel cell electrocatalysts.

With the growing thermal management demands of high-power electronic devices, conventional microchannel heat sinks face inherent limitations in simultaneously achieving efficient heat transfer and low flow resistance. How to significantly enhance heat transfer through innovative structural designs while maintaining reasonable flow resistance remains an urgent challenge. In this study, an asymmetric sinusoidal wavy microchannel heatsink incorporating elliptical microcolumns was proposed to enhance the heat transfer, and an intelligent design framework was developed by, for the first time, integrating a Transformer-based hybrid neural network (THNN) with NSGA-III multi-objective optimization. Effects of the microcolumn geometry, wavy channel parameters, and inlet velocity on flow and heat transfer characteristics were systematically investigated in numerical simulations. The results showed that adding elliptical microcolumns and increasing inlet flow rate can significantly enhance the heat transfer. As wave amplitude increases and period decreases, heat transfer performance also improved. Compared to the baseline structure (linear structure), Nusselt number (Nu) was increased by a factor of 2.2, with a significant 33.7 % improvement in the performance evaluation criterion (PEC). The THNN model achieved highly accurate performance predictions (R-2 > 0.99, RMSE <0.03), and based on the optimal design obtained through multi-objective optimization, PEC was increased by 57.8 % and Nu was enhanced by a factor of 2.98. The proposed structural design strategy and intelligent optimization approach provide valuable theoretical guidance and technical support for the engineering application of high-performance microchannel heatsinks.

Urea oxidation reaction (UOR) attracts considerable attention in the fields of energy and environmental protection; however, its practical application is greatly hindered by sluggish kinetics. Herein, a composite catalyst consisting of Ni-Co phosphate (NiCoPO) coupled with CeO2 (NiCoPO/CeO2) is successfully constructed for UOR. Experimental results show that the specific catalytic activity of NiCoPO/CeO2 reaches 948 mA cm−2 mg−1 (at 1.77 V vs. RHE), which is 3.5 times that of NiCoPO and 135.4 times that of CeO2. In addition to the modulated morphology and structure that provide a potential for exposing more active sites, the well-matched band structures of Ni-Co phosphate and CeO2 facilitates electron transfer from phosphate to CeO2. In situ electrochemical impedance spectroscopy and ex situ Raman spectra reveal that Ni3+/Co3+ serve as actual active sites. Thus, although CeO2 itself exhibits negligible activity, it promotes the formation of Ni3+/Co3+ active sites in NiCoPO during UOR. Furthermore, ex situ FTIR results indicate that UOR proceeds more smoothly on NiCoPO/CeO2 than NiCoPO alone, which is attributed to the enhanced oxidation capacity of the composite towards *CO intermediate during UOR. Contrastively, NiCoPO is highly susceptible to poisoning by *CO intermediate. Therefore, coupling NiCoPO with CeO2 not only promotes active sites generation, but also improves anti-poisoning capacity; consequently, the catalyst UOR performance is enhanced.

All-perovskite tandem solar cells are constrained by asynchronous crystallization in multicomponent perovskites, which produces vertical compositional gradients, structural inhomogeneity and excessive non-radiative recombination. These effects arise from mismatched coordination and crystallization kinetics among mixed halides and Pb2+/Sn2+ cations. Here we establish a generalizable additive design strategy guided by hard-soft acid-base principles to synchronize nucleation and crystal growth in both wide- and narrow-bandgap perovskites. Borderline-base difluoro(oxalato)borate and hard-base tetrafluoroborate selectively coordinate wide- and narrow-bandgap perovskite precursors, respectively, balancing the crystallization kinetics of PbI2/PbBr2 and PbI2/SnI2 and producing vertically uniform perovskite films with reduced defect densities and suppressed ion migration. In situ optical and structural characterization reveals homogeneous nucleation and direct crystal growth without intermediate halide redistribution. Monolithic two-terminal tandems achieve an efficiency of 30.3% (certified, 30.3%) with improved open-circuit voltage (2.16 V) and fill factor (85.2%), retaining 92% efficiency after 1,000 h of maximum power point tracking. Flexible tandems reach an efficiency of 28.2% (certified, 28.0%). These results establish chemical hardness matching as a universal principle for controlling crystallization in different perovskite systems.

As a thermal interface material that does not impede the normal operation of precision instruments, the development of non-silicone thermally conductive adhesive is of great significance. This paper innovatively leveraged the excellent adsorption properties of graphene and the unique interfacial interaction between graphene and the aluminum dihydrogen phosphate matrix, making spherical aluminum nitride particles uniformly coated with graphene. This process resulted in a novel graphene-coated aluminum nitride structure analogous to silver-coated aluminum fillers, significantly enhancing the overall thermal conductivity. The adhesive achieved a superior thermal conductivity (TC) of up to 14.03 W/(m center dot K), dramatically surpassing existing non-silicone thermally conductive adhesives (the maximum is about 10 W/(m center dot K)) while maintaining electrical insulation and no oil leakage. At the same time, due to the high specific surface area and unique two-dimensional structure of graphene, graphene-reinforced non-silicone thermally conductive adhesive exhibits strong bonding strength (13.39 MPa) and superior viscosity (31.67 Pa center dot s). In addition, owing to the effective vacuum drying and curing process and the introduction of water-based phosphate, graphene-reinforced non-silicone thermally conductive adhesive shows superhydrophilicity with a contact angle (12.3 degrees). Compared to traditional non-silicone thermally conductive adhesives, the heat transfer performance of this thermally conductive adhesive is very remarkable. This study provides a cost-effective solution for preparing superhydrophilic superb thermal conductivity non-silicone thermally conductive adhesive, which is beneficial for their future practical applications and commercialization.

Epoxy resin (EP) based composite materials, due to their advantages such as light weight, ease of processing, and mechanical properties, have been widely applied across thermal packaging field. However, the overall thermal conductivity is constrained by the interfacial thermal resistance between the filler and the substrate. Existing studies suggest that self-assembled monolayers (SAM) can enhance the interfacial thermal conductance (ITC) by forming covalent bonds. Nevertheless, limited research has focused on using SAM to form bilateral covalent bonds to regulate ITC. Therefore, SAM capable of forming bilateral covalent bonds at the EP/silicon (Si) interface were employed to enhance ITC. In this study, time-domain thermoreflectance (TDTR) experiments and molecular dynamics (MD) simulations were conducted to investigate the EP/SAM/Si system. The results demonstrate that SAM-NH2 modification, which forms bilateral covalent bonds at the EP/Si interface, increased the interfacial adhesion strength and enhanced ITC to 140%, thereby significantly promoting interfacial heat transfer. Conversely, ITC was reduced with SAM-CH3 due to the formation of single covalent bond. Subsequently, the differential effective medium (DEM) model was used to determine that the thermal conductivity of the composite modified with SAM-NH2 was improved by 11%. This study provides new insights into adjusting ITC using SAM.

Thermoelectric materials convert heat directly into electricity and are therefore promising for energy harvesting and environmental applications. Ideal high-performance thermoelectrics combine ultralow lattice thermal conductivity, κ L , with high carrier mobility, a paradigm commonly termed phonon-glass electron-crystal. However, strong coupling between electronic and phononic transport complicates simultaneous optimization of these properties. Because κ L is largely independent of electronic transport, targeted suppression of κ L is an effective route to partially decouple heat and charge transport. This Review summarizes recent advances in reducing κ L via two complementary approaches: phonon engineering of bulk nanostructured systems and phonon engineering of low-dimensional materials. In bulk systems, κ L may be minimized while retaining high electrical conductivity and maximizing the thermoelectric figure of merit ZT by controlling three fundamental phonon parameters: the volumetric specific heat c v , the phonon group velocity v g , and the phonon relaxation time τ . Low-dimensional architectures, including superlattices, nanowires, and nanocomposites, supply additional levers to suppress lattice heat transport and to tailor the electronic structure. Integrating multiscale and multimodal phonon-control strategies enables significant reductions in κ L without sacrificing electronic performance, thereby advancing the phonon-glass electron-crystal paradigm.

Passive radiative cooling technology is realized by increasing solar reflection and infrared emission. Polymer materials demonstrate greater potential in multi‐scenario cooling applications due to their excellent flexibility and manufacturability. Intrinsic characteristic modification is crucial for enhancing the performance of materials. Here, the radiative cooling properties of PVDF and P(VDF‐TrFE) with different C─F content are evaluated. Theoretical studies based on first‐principles calculations are conducted to understand the screening of chemical bonds from phonon dispersions. Then the optical performances are tested, with P(VDF‐TrFE) showing an enhanced net cooling power of 41% and 21% during daytime and nighttime, respectively. On‐site measurements have also been conducted. Compared to PVDF, the average cooling temperature drops of P(VDF‐TrFE) increase from 7.2 to 8.5 °C at noon and from 2.1 to 3.5 °C at night. This work successfully bridges atomic‐scale characteristics with material‐level radiative performance, providing a reference for finding effective radiative cooling materials through phononic properties.

Current marine antifouling materials predominantly utilize external biocides. However, this method is characterized by uncontrolled burst release and short-term efficacy, necessitating frequent reapplication and causing significant environmental pollution. To address these issues, we developed a more sustainable approach by leveraging the controlled release capabilities of microsphere materials. Specifically, temperature-sensitive chitosan molecules were grafted onto microsphere shells using ionic cross-linking, and the resulting microspheres were incorporated into a polyurethane coating. Given the complexity of the marine environment, with varying seawater temperatures and biological activities across different sea areas, this strategy aims to enhance antifouling effectiveness and sustainability. The microspheres achieved an encapsulation efficiency of 97.33

The understanding of spin-dependent transport in semiconducting polymers is significant in the field of organic spintronics. However, fully elucidating this phenomenon is challenging when relying solely on experimental data or theoretical analysis. Typically, the spin-dependent transport is associated with the magnetoresistance (MR) and charge distributions at N atoms of polyaniline. Herein, by combining density functional theory (DFT) calculations with experimental analysis, we investigate the spin-dependent transport of polyaniline copolymers by altering the charge distribution at nitrogen atoms through introduction of electron withdrawing (nitrile group) and electron donating (methyl group) groups on the benzene ring. The results show that the charge distribution induced by the methyl group on the benzene ring exhibits more pronounced influence on the spin-dependent transport of polyaniline copolymers than that of the nitrile group, which is affirmed by the zero-bias spin-revolved transmission spectra and the triple change of the gradient Delta y/Delta x of MR versus doping degree for copolymers with a methyl group relative to that of copolymers with a nitrile group. The gradient Delta y/Delta x of MR versus doping degree for copolymers with the methyl group and the nitrile group reaches 0.109 and 0.034, respectively. This research provides a novel perspective to figure out the spin-dependent transport of semiconducting polymers.

Electrolyte engineering breakthroughs are crucial to support extremely high-energy battery chemistries. However, the complex interplay between battery performance and electrolyte structure remains poorly understood and difficult to predict. Here we introduce the concept of 'normalized cation/anion-solvent affinity', which describes the critical interactions between solvents and both cations and anions. This innovative approach allows for the simultaneous and quantitative prediction of electrolyte microstructures, transport characteristics, redox behaviours and interphase characteristics. Leveraging this framework, we screened approximately 150 solvent candidates and identified electrolyte formulations that significantly improve Li metal plating/stripping Coulombic efficiency ( >99.5%). Among these, four electrolytes achieved Coulombic efficiency greater than 99.8%, while supporting the durability of aggressive high-voltage cathodes. These formulations enabled the realization of highly reversible Li metal batteries (LMBs) with a record-breaking high energy density of 600 Wh kg(-1) and over 100 cycles, advancing LMBs towards practical applications. The unified affinity paradigm offers valuable insights for designing next-generation electrolytes for high-energy LMBs and other alkali-metal-ion batteries.

某钢厂近期生产的钢材在加工后频繁出现裂纹缺陷,经检测发现罪魁祸首竟是铁水中的"隐形杀手"——砷元素.砷是一种有害残留元素,过量会导致钢材变脆、热加工性能下降,甚至引发产品报废.研究发现,该钢厂铁水中的砷含量在半年内飙升近一倍,源头竟与进口的高砷俄罗斯铁矿密切相关!通过追踪冶金全流程,揭示了砷污染的传递路径:俄罗斯铁矿粉和块矿含砷量高,且在烧结和冶炼过程中难以有效脱除.同时,高炉工艺参数(如温度、碱度)的微小波动也加剧了砷的富集.针对这一问题,提出"源头控制+工艺优化"双管齐下的解决方案:严控高砷原料比例、优化烧结脱砷技术,并建立实时监测机制.为同类企业提供了经济可行的治理范本.

Sodium-ion batteries are gaining traction due to their technical similarities to lithium-ion batteries, as well as the abundance and low cost of raw materials. However, thermal hazards and gas venting of the sodium-ion batteries remain unclear. This study compares the thermal and gas production characteristics of both sodium-ion and lithium-ion batteries at various states of charge. The results indicate that both battery types emit significant amounts of white smoke; however, lithium-ion batteries produce more smoke, exhibit faster jet velocity, and have longer jet duration during thermal runaway. Additionally, sodium-ion batteries activate their safety valves earlier than lithium-ion batteries, with significantly lower safety valve opening temperatures, maximum temperatures, and total mass loss. Moreover, the toxicity of gases emitted by lithium-ion batteries at 100 % state of charge is approximately 2.33 times greater than that from sodium-ion batteries. A thermal hazard assessment model further confirms that the thermal hazards linked to sodium-ion batteries are considerably lower than those associated with lithium-ion batteries. Finally, for early warning of thermal hazard, CO can be used for sodium-ion batteries, while voltage is suitable for lithium-ion batteries. This study provides theoretical guidance for the safety design of the sodium-ion and lithium-ion batteries.

The uniform dispersion and loading of phthalocyanine molecular catalysts on conductive carbon substrates are crucial for exposing their active sites. The significant amount of solvent needed to achieve appropriate dispersion of phthalocyanine leads to the risk of reaggregation during solvent evaporation. Hence, a solventless strategy is adopted by many to bypass the use of a solvent. In this study, we showcase the deposition of transition metal phthalocyanine (TMPc) molecules onto a self-supporting conductive carbon cloth electrode using an environmentally friendly sublimation technique for efficient electrocatalytic CO2 reduction. We meticulously investigated the preparation conditions, including the heating temperature and TMPc type, to assess their impact on the CO2 reduction activity. The as-prepared CC-CoPc-450 electrode demonstrated an outstanding comprehensive performance, showcasing a remarkable maximum CO Faradaic efficiency (FECO) of 97.1% at -0.86 V with a current density of 8.3 mA cm-2. The electrode exhibited excellent stability during the 16 h long-term eCO2RR process. Density functional theory (DFT) calculations demonstrated the role of d-orbitals in TM-N4 and the synergy with π-conjugation electrons in facilitating the efficient electron transfer process in eCO2RR. This study offers a fresh perspective on the eco-friendly dispersion of TMPcs on conductive substrates and provides insights into the design of π-species macrocyclic electrocatalyst electrodes.

In this study, we constructed a three-layer cylindrical periodic structure based on metamaterials.This structure is obtained by coupling the periodic cylindrical structure and the MIM (metal/insulator/metal) three-layer structure.The finite difference time domain method is used to calculate the reflection curve of the structure, and then the color coordinates of the structure under the D65 light source are calculated.We obtain the relationship between the color presented by the structure and the variation of structural size parameters.Then the random forest algorithm is used for machine learning, and a more accurate learning model is obtained.The coefficient of determination R 2 is above 0.98.This result ensures that the random forest algorithm can be used in the calculation of superstructure.The article presents a novel light filter design with tunable color properties and machine learning framework for accurate color predictions based on structural parameters.

With the trend toward miniaturization of functional devices, material preparation and thermal management processes are also limited to small spaces. Microchannels have emerged as an optimal solution for these challenges. Microchannel-based reactors can generate hybrid materials, and the integration of microchannel heat sinks and substrates can control the temperature of high-power devices. The microstructure within microchannels significantly influences fluid flow and heat transfer, impacting the efficiency of both reaction and heat dissipation processes. Pin-fins are widely used microstructures due to their ability to increase heat transfer area and enhance fluid mixing. In order to find the optimal structure of the fins, it is essential to explore a vast parameter space. In this paper, artificial neural network and genetic algorithm are combined to optimize the copper irregular pin–fin microchannels. Initially, a large number of numerical simulations are performed, focusing on adjustable parameters such as fin radii in various directions, while monitoring the heating surface temperature and the pressure drop of the fin section. Then, nearly 2000 sets of accumulated data are used to train the neural network, establishing the relationship between structural and performance parameters. Finally, a genetic algorithm is employed for multi-objective optimization, yielding a Pareto front. The findings reveal that the newly obtained optimized microchannels exhibit superior thermal–hydraulic performance compared to traditional microchannels. The mechanism of heat transfer enhancement in the optimized microchannel has been revealed: the arrangement of asymmetric fins allows for more thorough contact between the fluid and the fins. Based on this rule, the newly designed multi-fin microchannels exhibit better performance under both fixed heat flux and fixed temperature conditions. In addition, doping high thermal conductivity materials into the substrate to form composite materials can significantly improve the heat transfer performance of microchannels, and using materials with different doping ratios in different parts of the microchannel can effectively improve the temperature uniformity of the heating surface. Thus, uniform-temperature microchannels are designed by combining metal materials (such as copper and aluminum) with non-metal materials (like diamond and graphite).

AbstractPhotoacoustic tomography offers a powerful tool to visualize biologically relevant molecules and understand processes within living systems at high resolution in deep tissue, facilitated by the conversion of incident photons into low-scattering acoustic waves through non-radiative relaxation. Although current endogenous and exogenous photoacoustic contrast agents effectively enable molecular imaging within deep tissues, their broad absorption spectra in the visible to near-infrared (NIR) range limit photoacoustic multiplexed imaging. Here, we exploit the distinct ultrasharp NIR absorption peaks of lanthanides to engineer a series of NIR photoacoustic nanocrystals. This engineering involves precise host and dopant material composition, yielding nanocrystals with sharply peaked photoacoustic absorption spectra (~3.2 nm width) and a ~10-fold enhancement in NIR optical absorption for efficient deep tissue imaging. By combining photoacoustic tomography with these engineered nanocrystals, we demonstrate photoacoustic multiplexed differential imaging with substantially decreased background signals and enhanced precision and contrast.

Glass exhibits high transmittance in the solar radiation band but high absorbance in the mid-far infrared (MIR) band, which causes a poor energy-saving effect. Thermal insulation coatings offer the most effective solution to address this. Among these, nano-cesium tungsten bronze (CsxWO3) had a strong blocking effect in the solar radiation band due to its intrinsic absorption, local surface plasmon resonance, and small polaron absorption, but its reflectivity in the MIR band was very low. Conversely, silver nanowires (AgNWs) formed a dense network structure with low transmittance and high reflectance in the MIR band; however, when mixed into Cs0.32WO3 slurries, the solar radiation-blocking ability was weakened. In order to assess the impact of AgNWs on the properties of Cs0.32WO3 films, this study collected experimental data from different Cs0.32WO3 films doped with AgNWs for multilayer perceptron (MLP) neural network machine learning. The trained models exhibited efficient and accurate prediction abilities. A large number of extrapolated independent variables were input to the trained MLP models using the grid search method, and then the predicted results of dependent variables were displayed in three-dimensional (3D) models to more intuitively show the influence of doping AgNWs on the optical performance of different Cs0.32WO3 films. Through an optimization analysis of two 3D models of T-550 nm (transmittance at 550 nm) and SC (shading coefficient), two transition values of T-550 nm were found: 69.5 and 64.2%. When T-550 nm surpassed 69.5%, the SC value of nondoped Cs0.32WO3 films was the lowest. Conversely, when T-550 (nm) was below 69.5%, doping with AgNWs decreased the SC value of Cs0.32WO3 films. Using the optimal mixture of Cs0.32WO3 slurries and AgNW slurry at a ratio of 1:3, the SC value of nondoped Cs0.32WO3 films was lower when T-550 (nm) exceeded 64.2%. Conversely, when T(550 nm)was below 64.2%, the same mixture resulted in a lower SC value. These predicted results and their accuracy were verified by experiments and provided important technical guidance and method support for future research and the application of high-performance Cs0.32WO3 films.

Graphene membranes of excellent solar absorption and photothermal conversion efficiency have been used in solar-driven water evaporation (SDWE) systems as light-harvesting material. The interfacial evaporation property between graphene membranes and seawater is an important issue to further promote the development of SDWE. In this work, manipulation strategies are presented based on porous structures for tailoring the evaporation performance of graphene membranes. The non-equilibrium molecular dynamic (NEMD) simulation results show that the pore size, pore concentration, and distribution pattern are all key factors in enhancing the evaporation rate. The evaporation performance can achieve the best optimisation when the pore size is 3.1 & Aring; and the pore concentration is the lowest. Moreover, the periodic distribution of porous structures can greatly increase the evaporation rate (about 100 water molecules per nanosecond) due to the improvement of adsorption and desorption balance compared with the random structure. The optimised configuration of the graphene porous used in SDWE systems is proposed, which could increase the evaporation rate to 357.1%. This study could provide some theoretical guidance on graphene membranes for application in both photothermal conversion and solar-driven water purification.