Hydrogen diffusion plays an important role in the sorption kinetics of magnesium hydrides. In this work, a machine-learning-based Deep Potential (DP) model for the Mg-H system was developed using the DP-GEN active learning framework and density functional theory (DFT) calculations. The accuracy of the DP model was validated through comparisons of energies, forces, phonon dispersions, energy-volume relationships, and elastic properties, showing excellent agreement with DFT results. Using the developed DP potential, large-scale molecular dynamics simulations were performed to investigate hydrogen diffusion in tetragonal MgH2 (mp-23710) and orthorhombic MgH2 (mp-23712). The results show that hydrogen diffusivity increases with temperature in both phases, while orthorhombic MgH2 exhibits significantly higher diffusion coefficients than the tetragonal phase. CI-NEB calculations reveal that the enhanced diffusion originates from lower hydrogen migration barriers in the orthorhombic structure. For both polymorphs, vacancy-assisted diffusion is energetically more favorable than interstitial diffusion, and the introduction of hydrogen vacancies markedly promotes hydrogen transport. Radial distribution function analysis further indicates that the weaker local ordering and more flexible lattice environment of orthorhombic MgH2 facilitate hydrogen migration. This work provides an accurate DP potential for Mg-H systems and offers atomistic insights into the phase-dependent hydrogen diffusion behavior of MgH2.

Electrochemical CO2 conversion to methane requires a multi-step hydrogenation and involves a complex cascade reaction. It would be vital to achieve efficient catalytic performance if one could construct tandem active centers towards the multiple intermediates. Herein, we provided a pyrolysis-free synthetic strategy to fabricate monoatomicnanocluster Cu dual active centers for highly selective methanation of CO2. Expectedly, the tandem active centers realized the stepwise electrocatalytic reduction, during which the atomic Cu increased the dissociation of H2O while the Cu nanoclusters with a high electron density promoted the activation of CO2, synergistically accelerating the hydrogenation of *CO into *CHO, suppressing H2 generation and favoring the formation of CH4. The as-prepared catalysts demonstrated a superior Faradaic efficiency of 78.8% with a large partial CH4 current density of 111.5 mA & centerdot;cm-2 at-1.3 V vs. RHE, providing an avenue for the rational design and controllable synthesis of highly selective and active Cu-based CO2 reduction reaction (CO2RR) catalysts.

Hexagonal boron nitride (h-BN), a prototypical two-dimensional ceramic, is promising for electronic and thermal management applications owing to its high thermal conductivity, stability, and wide bandgap. However, the impact of inevitable structural defects on its thermal transport remains insufficiently understood. Here, we develop a machine learning interatomic potential within the Deep Potential framework to accurately describe pristine and defective monolayer h-BN. The model is validated against density functional theory through energyvolume relations, defect formation energies, elastic constants, and phonon spectra. Molecular dynamics simulations predict an in-plane thermal conductivity of 285 +/- 20 W/m center dot K at 300 K, consistent with Boltzmann transport equation results. Furthermore, we reveal distinct phonon scattering mechanisms induced by different defects, with the effect of Stone-Wales defects diminishing at higher concentrations. This work provides a reliable computational tool and insights into defect-property relationships in h-BN for guiding ceramic thermal management design.

The hexagonal perovskite Ba7Nb4MoO20 (BNM) has been considered a promising electrolyte candidate for intermediate-temperature solid oxide fuel cells (IT-SOFC) owing to its excellent oxide-ion transport properties in the intermediate-temperature range. In this study, Zr4+ was introduced at the Nb5+ site to regulate the local crystal structure and coordination environment. All Ba7Nb4-xZrxMoO20-delta (x = 0, 0.1, 0.2, 0.3) compositions retain a single-phase hexagonal perovskite structure, among which the x = 0.2 sample exhibits an ionic conductivity of 5.79 & times; 10-4 S & sdot;cm-1 at 500 degrees C-approximately four times that of the undoped sample-with its migration activation energy reduced to 0.813 eV. Raman analysis reveals that Zr4+ doping modifies the local tetrahedral environment, weakens the Nb/Mo-O bonding, and enhances local structural flexibility, thereby facilitating cooperative oxide-ion migration. Benefiting from this local structural modulation, the Ba7Nb4-xZrxMoO20-delta single cell achieves a peak power density (PPD) of 85.5 mW & sdot;cm-2 at 750 degrees C, demonstrating that Zr4+ doping enhances the overall electrochemical performance mainly by promoting oxide-ion transport through a reduced migration barrier.

Electrolyte additives, owing to their simplicity and high efficiency, have been widely employed to enhance the performance of aqueous zinc-ion batteries (AZIBs). To achieve rapid screening of highly effective electrolyte additives, this study integrates theoretical calculations with machine learning (ML) methods, using the sum of binding energy and adsorption energy (Eadd) of 2025 ionic liquids (ILs) ion pairs as the prediction target for model training and ranking. Through systematic model performance comparison and experimental validation, the Gradient Boosting Regressor (GBR) model demonstrated exceptionally high predictive accuracy (test set R2 = 0.9982) and excellent practical feasibility. Additives screened by the GBR model, namely n-Propylammonium tetrafluoroborate (PrBF4) and 1-Butyl-1-methylpyrrolidinium tetrafluoroborate (BMPyrrBF4), enabled zinc (Zn) symmetric cells to achieve cycling lifetimes of 130 h and 550 h, respectively, both superior to the 100 h observed with the ZnSO4 electrolyte and consistent with the model's predicted ranking. Further analysis revealed that these electrolyte additives disrupted the intrinsic hydrogen-bond network of the electrolyte, reduced the content of free water, and induced preferential Zn2+ deposition along the Zn (002) crystal plane. In addition, they increased the nucleation overpotential, promoting uniform Zn nucleation. Consequently, these effects effectively suppressed dendrite growth and the accumulation of detrimental by-products, thereby extending battery lifespan. The ML framework developed in this study provides a feasible and efficient pathway for large-scale screening of electrolyte additives and offers valuable guidance for the optimization and development of nextgeneration aqueous batteries.

In order to address the limitations of the oxygen reduction reaction (ORR) activity of cobalt-free Bi0.5Sr0.5FeO3-delta (BSFO) cathodes in intermediate-temperature solid oxide fuel cells (IT-SOFCs), a novel Bi0.5Sr0.5FeO3-delta-Sm0.2Ce0.8O2-delta (BSFO-SDC) composite cathode was developed. XRD, TEM, and EDS confirmed that BSFO and SDC do not chemically react within the operating temperature range of IT-SOFCs. Moreover, the hetero-interfaces increase the active sites for the oxygen reduction reaction (ORR). The optimized BSFO-20SDC (20 wt% SDC) exhibits a polarization resistance of 0.07 Omega & centerdot;cm2 at 750 degrees C, 53% of pure BSFO (0.13 Omega & centerdot;cm2). First-principles simulation based on density functional theory (DFT) reveals that the enhanced electrochemical performance is mainly attributed to the low oxygen vacancy formation energy of the BSFO-SDC heterostructure (1.07 eV), which is significantly lower than that of BSFO (1.47 eV). The anode-supported single cell (NiO-SDC/SDC/BSFO-20SDC) delivers a peak power density of 642 mW cm-2 at 750 degrees C with humidified H2 (similar to 3 vol% H2O) as fuel. Additionally, the composite has a thermal expansion coefficient (TEC) of 13.35 & times;10-6 K-1 matching SDC electrolyte, and the single cell maintains stable open-circuit voltage (similar to 0.7 V) for 80 h at 750 degrees C and 296 mA cm-2. These results demonstrate that BSFO-SDC is a promising cobalt-free cathode for IT-SOFCs.

Fabrication of metal-organic frameworks (MOFs) or carbon-based materials with unique morphologies, such as one-dimensional (1D) nanofibers, is critical for energy storage and conversion applications because of their high surface area and efficient electron transport. This study presents a thermodynamically driven reconstruction strategy for the synthesis of sea-urchin-like MOF superstructures. Through this method, MOF block crystals are transformed into a pure-phase, sea-urchin-like superstructure comprising long, ultrathin, uniform MOF nanofibers. This evolution process involves reorganization of the coordination mode between ligands and metal centers, leading to reconstruction of the crystal structure. Detailed investigation into the evolution process demonstrate that the addition of urea can substantially expedite the reconstruction process. The free energy difference serves as the driving force of evolution from the initial kinetic intermediate state to the final thermodynamically stable state. Owing to the special nanofiber morphology, the derived Co- and N-codoped carbon nanofibers (Co-N-CNFs) offer exceptional advantages in boosting the oxygen reduction reaction (ORR) performance and are considerably superior to block-like CoNC electrocatalysts in terms of half-wave potential, stability, and durability. Zn-air battery test results confirm the remarkable ORR performance in practical applications, demonstrating the application potential of this new electrocatalyst for ORR. The proposed MOF reconstruction strategy offers a new pathway for synthesizing functional MOFs or their derivatives with 1D or other types of morphologies.

Cu-Sn alloy materials are widely used in electronic industry, aerospace and 3D printing. When studying the structure and properties of materials, a contradiction between arithmetic and accuracy is encountered by Molecular dynamics (MD). Molecular dynamics is a general theoretical calculation method for studying the mechanical properties of alloy materials. However, molecular dynamics simulations of alloy materials are limited to simple systems because the construction of traditional interatomic potentials is replicative and inefficient. In this study, the Cu-Sn material machine learning interatomic potential was constructed by using a deep neural network model, and the first-principles calculation results were used as the training data set to ensure the accuracy of the quantum mechanical interatomic potential. This process features an "active learning" process, data generation and model training methods with minimal human intervention. Molecular dynamics using machine learning interatomic potentials (MLIP) and first-principles calculations show good consistency. It was concluded that MLIP can accurately predict energy, force and mechanical properties. The root mean square error (RMSEs) of the energy and force per atom is approximately 10 meV/atom and 100 meV/& Aring;. It shows good advantages in energy-volume curve, phase transition temperature and elastic modulus, laying the foundation for the wide application of the MD method in the design and development of Cu-Sn alloy materials.

A rapid non-equilibrium sintering strategy based on high-temperature shock (HTS) treatment is proposed to engineer defect-rich double perovskite Sr2FeTaO6_s (SFT) anode materials for enhanced electrochemical performance in solid oxide fuel cells (SOFC). The HTS process induces the in-situ formation of metastable SrFeO3 (SFO) and Sr5Ta4O15 (STO) phases, leading to a nanoscale polycrystalline microstructure that significantly promotes interfacial catalytic activity. Comprehensive characterizations reveal that the HTS-SFT anode exhibits enriched oxygen vacancies at the 0D scale, abundant dislocations and localized compressive-tensile strain fields at the 1D scale, and a dense network of nanoscale grain boundaries at the 2D scale. These multiscale defects synergistically enhance gas adsorption/dissociation, charge transfer, and interfacial reaction kinetics. As a result, the HTS-SFT achieves a peak power density (PPD) of 0.578 W cm_ 2 at 850 degrees C, which was 2.77 times higher than that of conventionally sintered SFT. Moreover, the polarization resistance (Rp) is significantly reduced, and the apparent activation energy (Ea) decreases from 1.306 eV to 1.214 eV, evidencing markedly enhanced catalytic activity. This work demonstrates the great potential of HTS in tailoring defect structures in double perovskites and offers new insights into the design of high-performance SOFC anode materials.

A Gaussian approximation potential (GAP) for TiO2 was constructed by adjusting the size and composition of the dataset, as well as the hyperparameters in the smooth overlap of atomic positions (SOAP) descriptors. Using these trained machine learning interatomic potentials, we conducted molecular dynamics simulations to determine the lattice constants, thermal conductivity, and thermal expansion coefficient of titanium oxide ceramics. The calculated root mean square errors for these properties were 0.01 angstrom, 1.2 W K-1 m-1, and 0.005 K-1, respectively. Our molecular dynamics simulation results exhibit strong consistency with first-principles calculations. This indicates that the Gaussian approximation potential (GAP) developed for titanium oxide achieves both firstprinciples accuracy and computational efficiency.

Supercapacitors,also known as electrical double-layer capaci-tors(EDLCs),store and release electrical charge through the adsorption and desorption of ions on the surface of highly porous carbon materials[1].To meet the increasing demands from electric vehicles,rail traffic,military and space applications,EDLCs are usu-ally required to operate within a broad temperature range(subzero to 60 ℃ or more)[2].The operating temperatures of current EDLC technologies are strongly related to the electrolyte[3].However,conventional aqueous electrolytes suffer from the issues of freez-ing below zero and rapid evaporation of water at high tempera-tures,limiting their safe operating temperature range.

BaCeO3 is a widely recognized protonic ceramic cell (PCC) electrolyte material for its exceptional proton conductivity and excellent sinterability. However, it suffers from poor stability and is highly vulnerable to CO2 attack during operation, limiting its practical application in PCCs. To address this gap, this study introduces the Sc doping into the B-site of BaCeO3 to improve its CO2 tolerance and further enhance its proton conductivity. The results reveal that Sc doping significantly improves both the CO2 tolerance and proton conductivity. Among the Sc-doped BaCeO3 compositions, BaCe0.6Sc0.4O3-delta (BCSc0.4) demonstrates superior CO2 tolerance, high proton conductivity, and low electronic conductivity. At 600 degrees C, PCC with the BCSc0.4 electrolyte achieves a peak power density of 0.831 W cm- 2 in fuel cell mode and a current density of -1.321 A cm- 2 at 1.3 V in electrolysis mode. Moreover, the BCSc0.4 electrolyte demonstrates excellent durability. It maintaining stable operation under PCC conditions for 200 h without any observable degradation. This study successfully develops a novel PCC electrolyte that combines enhanced CO2 tolerance, high proton conductivity, and long-term durability. These attributes highlight its strong potential to advance the development of high-performance PCCs.

Ba7Nb4MoO20 exhibits excellent oxygen ion transport properties and is a promising electrolyte material for solid oxide fuel cell (SOFC). To further enhance its oxygen ionic conductivity, element doping is an effective strategy. However, few studies have delved into the impact mechanism of doping strategies on the electrolyte's conductivity properties from the perspective of electronic structure. Here, the enhancement mechanism of oxygen ionic conductivity in Ba7Nb4MoO20 was analyzed using the the methods of density of states (DOS) and Crystal Orbital Hamilton Populations (COHP). Since the electronic conductivities of the electrolytes are negligible, their total conductivies can essentially be regarded as the conductivies of oxygen ions. As the Sr doping amount increases, the oxygen ionic conductivities of the electrolytes also increase. The bulk conductivity shows a negative correlation with the Sr doping amount, which is due to the higher bond energy of Sr-O compared to Ba-O. On the other hand, Sr promotes grain growth and reduces the number of grain boundaries, thereby decreasing the resistance to oxygen diffusion at the grain boundaries and thus enhancing the grain boundary conductivity. In the Ba7-xSrxNb4MoO20-s (x=0, 0.1, 0.2, 0.3, and 0.4) perovskite oxides, Ba 6.6 Sr 0.4 Nb 4 MoO 20-s has the highest conductivity, reaching 1.12 x 10-4S cm-1 at 500 degrees C. This work not only develops a SOFC electrolyte material with promising application prospects, but also provides theoretical guidance for its doping modification.

To improve ion transport kinetics and electronic conductivity between the different phases in sodium/lithium-ion battery (LIB/SIB) anodes, heterointerface engineering is considered as a promising strategy due to the strong built-in electric field. However, the lattice mismatch and defects in the interphase structure can lead to large grain boundary resistance, reducing the ion transport kinetics and electronic conductivity. Herein, monometallic selenide Fe3Se4-Fe7Se8 semi-coherent heterointerface embedded in 3D connected Nitrogen-doped carbon yolk-shell matrix (Fe3Se4-Fe7Se8@NC) is obtained via an in situ phase transition process. Such semi-coherent heterointerface between Fe3Se4 and Fe7Se8 shows the matched interfacial lattice and strong built-in electric field, resulting in the low interface impedance and fast reaction kinetics. Moreover, the yolk-shell structure is designed to confine all monometallic selenide Fe3Se4-Fe7Se8 semi-coherent heterointerface nanoparticles, improving the structural stability and inhibiting the volume expansion effect. In particular, the 3D carbon bridge between multi-yolks shell structure improves the electronic conductivity and shortens the ion transport path. Therefore, the efficient reversible pseudocapacitance and electrochemical conversion reaction are enabled by the Fe3Se4-Fe7Se8@NC, leading to the high specific capacity of 439 mAh g-1 for SIB and 1010 mAh g-1 for LIB. This work provides a new strategy for constructing heterointerface of the anode for secondary batteries. Monometallic selenide Fe3Se4-Fe7Se8 semi-coherent heterointerface embedded in 3D connected Nitrogen-doped carbon yolk-shell matrix (Fe3Se4-Fe7Se8@NC) is obtained via a phase transition process, inhibiting the lattice mismatch, and improving the built-in electric field. Benefitting from the unique 3D carbon bridged multi-yolks shell structure and heterointerface engineering, Fe3Se4-Fe7Se8@NC anode for lithium/sodium-ion battery exhibits low interface impedance, fast reaction kinetics, and excellent structural stability. image

In this paper, Ti3C2Tx MXene/Cu-Bi bimetallic sulfide (Ti3C2Tx/BiCuS2.5) composites were prepared by a simple in situ deposition method for electrocatalytic nitrogen reduction reaction (eNRR). Compared to Ti3C2Tx/Bi2S3 and Ti3C2Tx/CuS, the eNRR performance of Ti3C2Tx/BiCuS2.5 is significantly improved. The results show that Ti3C2Tx/BiCuS2.5 exhibits a NH3 yield of 62.57 mu g h(-1) mg(cat.)(-1) in 0.1 M Na2SO4 at -0.6 V vs reversible hydrogen electrode, and the Faradaic efficiency (FE) reaches 67.69%, which is better than that of Ti3C2Tx/CuS (NH3 yield: 52.26 mu g h(-1) mg(cat.)(-1), FE: 34.15%) and Ti3C2Tx/Bi2S3 (NH3 yield: 54.04 mu g h(-1) mg(cat.)(-1), FE: 37.38%). According to density functional theory calculations, the eNRR at the Ti3C2Tx/BiCuS2.5 surface is the alternating pathway. The H-1 NMR experiment of N-15 proves that the N of NH3 generated in the experiment originates from N-2 passed during the experiment.

Despite aqueous zinc ion batteries (AZIBs) holding promising prospects owing to their affordability, cornucopian resources and intrinsic security, the poor reversibility and low coulomb efficiency of Zinc (Zn) anodes significantly shorten the lifespan of AZIBs, thus promoting the continuous exploration of novel high performance electrolyte additives that can stabilize Zn anodes. Herein, a commonly used pyrrolidine-based ionic liquid, N, Ndimethylpyrrolidinium tetrafluoroborate ([DMP]BF4), was introduced into a typical ZnSO4 aqueous electrolyte as an additive to strengthen the Zn anode stability. By a comprehensive series of electrochemical tests, structural characterizations, and theoretical calculations, the mechanism by which the [DMP]BF4 additive enhances the stability of Zn anode was elucidated: can modulate the solvation structure of Zn2+, facilitate its transfer, desolvation and deposition kinetics; can be preferentially adsorbed onto Zn anode surface, inducing Zn2+ epitaxial deposition along (002) crystal plane, regulating uniform nucleation, thereby mitigating Zn dendrite growth; can construct a self-healing zincophilic hydrophobic in-situ solid electrolyte interface (SEI) layer onto the Zn electrode surface, effectively isolating the direct contact between H2O and Zn anode, thus inhibiting parasitic side reactions. Consequently, Zn-Zn symmetrical cells assembled using [DMP]BF4 showed a long and stable cycle life under diverse current densities and deposition areal capacities (approximately 2900 h under 1 mA cm- 2, 1 mAh cm-2 as well as over 1400 h under 5 mA cm- 2, 2.5 mAh cm- 2). Furthermore, the full battery, utilizing Na2V6O16 & sdot;1.63H2O (NVO-H) nanowires as the cathode material, exhibited an extended cycle life of 500 cycles under 1 A/g and 2800 cycles under 3 A/g. This study establishes a reliable experimental foundation for the advancement of other high-performance ionic liquid additives.

The cathodic catalytic activity for the oxygen reduction reaction (ORR) plays a critical role in determining the performance of proton-conducting solid oxide fuel cells (P-SOFCs). BaCo 0.4 Fe 0.4 Zr 0.2 O 3-s (BCFZ) has emerged as a promising cathode for P-SOFCs due to its triple-phase conductivity. Nevertheless, its suboptimal proton conductivity and hydration ability at intermediate temperatures prevent it from achieving the anticipated ORR catalytic activity. To address these limitations, this study explores the enhancement of electrocatalytic activity in BCFZ through alkali metal doping and A-site defect construction. The effects of such modifications on oxygen surface exchange kinetics and ORR catalytic activity are systematically investigated. The findings reveal that BCFZ exhibits relatively low parameters in terms of electronic conductivity, oxygen ion conductivity, oxygen vacancy concentration, k chem , and D chem . Conversely, these parameters are markedly improved in A-site deficient BCFZ (D-BCFZ) and Na/K-doped BCFZ. Consequently, the enhancement of these properties yields a significant increase in ORR catalytic activity, with D-BCFZ demonstrating the best electrochemical performance. Specifically, P-SOFC with D-BCFZ cathode achieves an R p value of just 0.073 S2 cm2 2 and a P max value of 0.928 W cm- 2 at 650 degrees C. This study provides theoretical insight into the mechanisms by how alkali metal doping and defect construction enhance the ORR catalytic activity of BCFZ. These findings offer valuable guidance for the development and optimization of high-performance P-SOFC cathodes.