Lithium-rich manganese-based layered oxides (LLOs) are considered as next-generation promising cathode materials for lithium-ion batteries due to the high theoretical energy density (exceeding 1000 W·h·kg^-1) and low cost. However, their electrochemical performance is highly sensitive to the initial activation conditions, including initial charge cut off voltage, activation temperature, initial current density, and activation cycle number. The activation process involves the electrochemical transformation of Li₂MnO₃ domains into active phases, which is crucial for achieving high capacity but leads to irreversible oxygen release and structural degradation. Traditional optimization methods rely on single-factor experiments, which are inefficient and fail to address the complex coupling effects of multiple parameters. This study proposes a machine learning driven framework to optimize the activation conditions of LLOs, addressing the limitations of conventional approaches by enabling high-dimensional parameter search and predictive modeling. This work highlights the necessity of artificial intelligent optimization for enhancing the stability and performance of high-energy-density batteries.

The research constructed a dataset comprising nearly 100 samples from laboratory experiments and research articles, featuring key parameters such as Li₂MnO₃ domain ratio (x = 0.1-0.5), activation charge cutoff voltage (4.4-4.8 V), activation temperature (25-55 ℃), activation current density (20-220 mA·g^-1), and activation cycles (1-4). Data preprocessing included unit standardization and mean imputation for missing values. Six supervised learning regression models—Lasso Regression, Ridge Regression, Support Vector Regression (SVR), Decision Tree Regression (DTR), XGBoost, and CatBoost—were trained to predict the 50th-cycle capacity retention. Hyperparameter optimization was performed using grid search with 5-fold cross-validation, evaluated by metrics like R², MAE, MSE, and MAPE. The CatBoost model demonstrated superior prediction performance and was selected for further analysis. Feature importance was interpreted using SHapley Additive exPlanations (SHAP), and Bayesian optimization with Gaussian process regression was applied to identify optimal activation conditions by maximizing capacity retention. Experimental validation involved synthesizing LLOs with different Li₂MnO₃ ratios (e.g., 0.3Li₂MnO₃·0.7LiMn_0.42Ni_0.42Co_0.16O₂ and 0.5Li₂MnO₃·0.5LiMn_2.42Ni_0.42Co_2.16O₂), characterized by XRD and electrochemical performance testing.

The CatBoost model achieved the highest prediction accuracy (R² = 0.777, MSE = 3.00 × 10^-4), significantly outperforming linear models and other nonlinear algorithms. SHAP analysis revealed that Li₂MnO₃ domain ratio and activation charging cutoff voltage were the most influential features, with high voltages (>4.6 V) and high Li₂MnO₃ content negatively impacting capacity retention due to accelerated oxygen loss and structural degradation. Bayesian optimization identified distinct optimal conditions for different LLOs compositions: for a Li₂MnO₃ ratio of 0.3, the optimal parameters were 4.49 V charging cutoff voltage, 25 ℃ activation temperature, and 20 mA·g^-1 activation current density, yielding lowest capacity decay; for a ratio of 0.5, a higher temperature of 43.95 ℃ was required to fully activate the material while maintaining stability. Experimental validation confirmed the model's predictions, with capacity retention errors below 1% compared to experimental result. For instance, under optimized conditions, the 3/7 LLOs sample maintained 100.9% capacity retention after 50 cycles, versus 90.6% with conventional high-voltage activation. The results demonstrate that ML enables precise control of multi-parameter interactions, balancing capacity and stability by suppressing irreversible reactions.

This study successfully integrates machine learning with experimental research to optimize the electrochemical activation of lithium-rich cathodes. The CatBoost-based predictive model accurately captures nonlinear relationships between activation parameters and capacity retention, while Bayesian optimization efficiently identifies global optimal conditions in high-dimensional space. The work provides a data-driven strategy for designing high-performance LLOs, emphasizing the critical roles of voltage and temperature in structural evolution. This approach significantly reduces experimental costs and time, offering a generalizable framework for multi-parameter optimization in complex electrochemical systems. Future applications could extend to other battery materials and processes, advancing the development of intelligent materials design.

In this study, we propose a divide-and-conquer ML modeling strategy embedded with materials domain knowledge, which establishes mappings between different ML models and the distinct physicochemical mechanisms of materials. Future research efforts can focus on the following directions to further advance this strategy: i) Data quality remains the fundamental fuel driving the construction of high-accuracy models. When implementing this strategy, it is necessary to collect sufficient high-quality data for each sub-problem. ii) As material problems become increasingly complex, more and more divide-and-conquer ML modeling strategies can be introduced to comprehensively cover the dimensions of decomposing complex material problems. iii) Currently, divide-and-conquer ML relies on manual model selection and hyperparameter optimization based on expert experience. Automated machine learning (AutoML) can be introduced to eliminating the knowledge barriers to modeling. iv) The divide-and-conquer ML modeling strategy allows researchers to introduce inherently interpretable models for specific sub-problems and incorporate internal interpretation methods for models. In the future, as the paradigm of materials science research undergoes a profound shift towards digitalization and intelligence, this strategy is poised to gain renewed relevance and vitality. Through the deep integration of scientific deconstruction guided by domain expertise, the "divide and conquer" strategy is expected to propel a more thorough and systematic understanding of complex material behaviors. It will facilitate deeper revelation of intrinsic relationships and underlying mechanisms, thereby accelerating the process of precise design and development of high-performance materials.

Inorganic electrides, characterized by localized electrons acting as anions within the cationic lattice framework, represent a unique and emerging class of materials with significant potential for applications in electrode materials, electronics, catalysis, and beyond. Despite their promise, the discovery of new electrides, especially those with complex structures, remains a formidable challenge. Current computational approaches, which predominantly employ "direct" strategies to screen for ideal electrides, often fail to identify promising candidates that could be derived from stable precursor compounds through anion removal. Recognizing that an electride is fundamentally a reduced derivative of its electron-saturated precursor, we introduce an innovative "indirect" screening strategy. This novel approach centers on identifying potential precursor materials that can be transformed into electrides, rather than directly searching for the final electride structures themselves. Consequently, this work endeavors to unlock the vast, yet underexplored, potential of mineral databases as a treasure trove for such precursor systems and to establish a robust, generalizable methodology for their efficient identification and discovery.

We proposed a comprehensive four-stage screening workflow, leveraging the American Mineralogist Crystal Structure Database (AMCSD) to systematically identify potential electride precursors. The initial phase involved the pre-processing of 20 488 mineral structures to standardize the dataset, ensuring uniformity and consistency. Subsequently, a preliminary screening stage was implemented, imposing constraints on compositional complexity, unit cell size, and explicitly excluding specific systems such as carbonates and metal oxides to narrow down the candidate pool. The cornerstone of our approach was the pattern screening stage, which utilized a novel topological descriptor. This descriptor was specifically engineered to identify local coordination environments where a removable anion (X = O, F, Cl, Br, I) is coordinated by 4 to 6 identical metal cations (the XM_n motif). This stage effectively filtered out structures that did not meet the predefined criteria for potential electride formation. In the final stage, the candidate structures identified through pattern screening were subjected to a rigorous fine screening process based on density functional theory (DFT). This involved structural optimization of both the precursor compounds and their corresponding anion-removed derivatives. Following optimization, electronic structure calculations were performed to assess the band gap transition and the spatial localization of electrons using the electron localization function (ELF). Specific thresholds were applied to identify the most promising electride precursors from this refined pool of candidates.

The proposed four-stage screening strategy demonstrated remarkable efficiency, successfully narrowing down from an initial dataset of 20 488 mineral structures to a final selection of 18 high-potential electride precursors. DFT calculations provided conclusive electronic evidence for their electride character: all identified precursors were wide-gap insulators (band gap > 2.0 eV), and upon removal of the central anion (X = O, F, Cl, Br, I), all underwent a characteristic electronic transition. This transition is characterized by the formation of new in-gap states at the Fermi level following anion removal. Specifically, 13 systems transitioned to metallic states, while 5 became narrow-gap semiconductors (< 0.5 eV). ELF analysis unambiguously confirmed the spatial localization of the resulting excess electrons within the anion vacancy sites. The effectiveness of our strategy was further validated by the identification of experimentally known sodalite- and apatite-type electrides among the candidates. Beyond merely validating the method, the discovery of 7 previously unreported structural prototypes underscores the strategy's power for novel discovery. This outcome not only highlights the rich diversity of electride precursors within mineral databases but also demonstrates the generalizability of our topological descriptor for identifying the essential chemical motif required for electride formation.

In conclusion, we have successfully established a robust and innovative screening strategy that is based on an indirect approach. This strategy has proven to be highly effective in identifying 18 high-potential inorganic electride precursors from an initial dataset of 20 488 mineral structures. The indirect strategy's success is underscored by its remarkable ability to not only reproduce known sodalite- and apatite-type electrides but also, more significantly, to uncover 7 previously unreported structural prototypes. The comprehensive spectrum of electron localization dimensionalities (0D, 1D, 2D) observed across the entire candidate pool further highlights the broad applicability and generalizability of our methodology. This work establishes mineral databases as a rich and valuable resource for the discovery of novel electrides. It also illustrates the power and potential of precursor-targeted screening in uncovering new materials. The generalizable framework presented here offers a versatile and powerful tool that can be extended to the systematic discovery of other functional materials based on specific local coordination patterns. The identified candidates provide a solid foundation for future experimental synthesis and in-depth investigation, paving the way for further advancements in the field of materials science.

Silicon carbide (SiC), as a representative third-generation wide-bandgap semiconductor material, exhibits superior performance over traditional silicon-based devices in high-voltage, high-power, and high-frequency applications. The doping concentration of the SiC epitaxial layer critically determines the performance of power devices. However, current doping control heavily relies on manual experience and offline testing, which incurs high costs and significant time delays. This study aims to address these limitations by proposing a data-driven model for accurate and real-time prediction of doping concentration in both in-situ and next-batch scenarios.

This paper proposes a Multi-scale Feature-enhanced Temporal Transformer Network (MFT-NET) for predicting the core-layer doping concentration during SiC epitaxial growth. The model integrates four key modules:

Multi-scale Convolution Module: Employs parallel convolutional branches with kernel sizes of [3,3], [9,3], and [21,5] to capture parameter dynamics across millisecond-to-hour scales.

Squeeze-and-Excitation (SE) Module: Enhances feature channels correlated with doping concentration and suppresses noise via channel-wise attention.

Transformer Module: Models global coupling relationships among all 75 process parameters using multi-head self-attention.

Gated Recurrent Unit (GRU) Module: Captures cross-batch state dependencies to account for residual dopant and equipment state drift between consecutive epitaxial runs.

The model was trained and evaluated on a dataset comprising 1200 epitaxial runs from a commercial SiC epitaxial reactor. Data preprocessing included Pearson correlation-based feature selection and min-max normalization. A weighted mean squared error loss function was adopted to prioritize mainstream process samples.

Experimental results demonstrate that MFT-NET significantly outperforms traditional models including Ridge Regression, Support Vector Regression (SVR), CNN, CNN+LSTM, Transformer, and CNN+Transformer. In the in-situ prediction scenario, MFT-NET achieved a mean absolute percentage error (MAPE) of 1.35%, a root mean square error (RMSE) of 2.81×10¹⁴ cm^-3, and a coefficient of determination (R²) of 0.89. For next-batch prediction, it attained a MAPE of 1.66%, RMSE of 3.42×10¹⁴cm^-3, and R² of 0.87.

Ablation studies confirmed the contribution of each module: the multi-scale convolution and SE modules improved feature extraction and selection; the Transformer enabled global parameter interaction modeling; and the GRU was crucial for capturing cross-batch state transfer, reducing next-batch prediction RMSE by 20.8% compared to the model without GRU.

Hyperparameter analysis revealed that a 3-layer Transformer, the proposed multi-scale kernel combination, and a Dropout ratio of 0.2 yielded optimal performance.

The MFT-NET model effectively addresses the multi-scale dynamics, global parameter coupling, and cross-batch state transfer challenges in SiC epitaxial growth. It provides highly accurate doping concentration predictions for both in-situ monitoring and next-batch forecasting, with the potential to reduce offline testing costs by 30% and improve process stability by 15%. This work offers a robust data-driven framework for intelligent optimization of SiC epitaxial processes.

Despite the significant progress, the full potential of data-driven and AI methodologies in Sm-Co-based permanent magnet research is yet to be realized. To overcome existing challenges and harness future opportunities, the following prospects are proposed.

1) Enhancing Physical Interpretability of ML Models. Future research should go beyond treating machine learning as a "black-box" predictive tool and place greater emphasis on the physical interpretability of models. On one hand, efforts should be made to actively develop feature descriptors that integrate physical priors and domain knowledge such as magnetism theory and crystal field theory. On the other hand, while continuing to deepen the application of interpretable AI techniques like SISSO and SHAP to quantify the contributions of different features to performance, in-depth research should be conducted to explore the application of new algorithms and optimization strategies such as neural networks. Exploring hybrid models that embed constraints and relationships derived from first-principles calculations and micromagnetic simulations will be crucial for predictions in physical reality.

2) Developing Frameworks for Multi-Source Data and Transfer Learning. The data generated from research on rare-earth permanent magnetic alloys are typical multi-source heterogeneous data, including numerically computed and experimentally measured values, microstructural images, where the microstructure significantly influencing magnetic properties. Future work should leverage deep learning to create unified, machine-readable representations of this diverse data. On this basis, cross-scale transfer learning methods and active learning approaches should be developed to prevent traditional machine learning methods from falling into the traps of overfitting and local optima in small-sample scenarios.

3) Establishing Closed-Loop Inverse Design Systems. The ultimate goal of data-driven approaches is to achieve target-performance-oriented intelligent research and development. Future efforts should focus on constructing an automated intelligent pipeline for inverse design and automated validation. Driven by target performance, this system utilizes conditional generative models to automatically generate candidate compositions and process schemes that meet the requirements. These candidate solutions are then fed into a multi-scale computational chain for simulation validation and optimization. The computational results are fed back as new data into the database and machine learning loops, enabling continuous iteration and optimization of design strategies.

4) Pursuing Data-Assisted Sustainable and Economic Alternatives. By constructing a database incorporating substitution elements, this approach predicts the impact of partially replacing Sm with high-abundance rare-earth elements such as Ce/La on magnetic properties. The goal is to enhance the utilization of high-abundance rare-earth elements while ensuring high performance, thereby developing new cost-effective composition systems. Furthermore, by comprehensively considering factors such as manufacturing processes, raw material costs, and performance merits, novel low-carbon and environmentally friendly rare-earth permanent magnetic alloy systems can be designed.

While the convergence of data-driven methods and material science has yielded breakthrough progress, the field remains in a nascent stage with significant challenges. The primary challenge is the data gap. There is a scarcity of standardized, high-quality experimental data at the device level (e.g., real-time resistance drift statistics under operating conditions), which limits the generalization ability of ML models. Secondly, multi-physics coupling is a major hurdle. Current ML simulations predominantly focus on thermal-structural interactions. However, real-world PCRAM operation involves a complex interplay of thermal, electrical (Joule heating, carrier transport), and chemical fields. Developing a unified model that integrates these multi-domain dynamics is crucial for predictive device design. Thirdly, the "black box" nature of ML models often obscures the underlying physical laws, necessitating the development of interpretable AI to validate findings against established physical rules, such as the 8-N rule in chalcogenide glasses.

Looking forward, the research focus is expected to shift toward Crystalline-Crystalline Phase Transitions (CCPT). Materials like In₂Se₃ and MoTe₂, which switch between different crystalline polymorphs, offer superior energy efficiency and stability compared to traditional amorphous-crystalline transitions. ML will play a vital role in accelerating the discovery of such materials. Additionally, Crystal Structure Prediction (CSP) assisted by ML will become a standard tool for exploring unknown metastable phases. Ultimately, the goal is to establish a closed-loop multi-scale modeling framework that connects microscopic atomic behaviors directly to macroscopic device reliability, providing solid theoretical support for the development of low-power, high-endurance, and high-density storage technologies.

Despite significant progress, the field of AI-driven crystal design faces critical bottlenecks. A primary challenge lies in the absence of a universally accepted representation framework that simultaneously satisfies invertibility, invariance, and periodicity encoding capabilities. Furthermore, current generative models predominantly focus on ideal crystal structures, often neglecting real-world complexities such as defects, impurities, and service environments. To bridge this gap and facilitate the transition from theoretical exploration to practical application, future research should focus on three key directions: 1) Physics-informed representation design: Developing representations that intrinsically embed crystallographic constraints, such as Wyckoff positions and space groups, to ensure symmetry-aware and invertible encodings. 2) High-fidelity modeling of real-world materials: Extending beyond idealized lattice structures to model realistic defects and environmental responses (e.g., temperature, pressure) by integrating symmetry-constrained data augmentation with molecular dynamics simulations. 3) Standardization of benchmarks: Establishing community-wide benchmarks that rigorously evaluate generation stability, novelty, diversity, and computational cost, ensuring objective comparisons across different chemical systems. Addressing these challenges will be pivotal in realizing the automated, intelligent design of functional crystalline materials.

Although notable progress has been made in generative crystal models, significant challenges remain in both scientific understanding and practical deployment. Existing datasets are limited in structural diversity, physical fidelity, and multimodal coverage, making it necessary to construct large-scale, high-quality datasets integrating experimental observations, first-principles calculations, and model-generated structures. The physical interpretability and reliability of generated structures, particularly in multicomponent and nonequilibrium systems, require systematic investigation. Establishing closed-loop platforms that integrate model generation, autonomous synthesis, high-throughput characterization, and iterative retraining remains a key step toward practical materials discovery. Physics-aware constraints, uncertainty quantification, and robust generation under sparse data conditions are essential for improving model reliability. Furthermore, industrial applications demand models capable of handling large unit cells, defect chemistry, compositional tunability, and synthesis feasibility. With the development of large materials models, automated laboratories, and data-centric infrastructures, generative crystalline modeling is expected to become a core driver in building an intelligent, automated, and industrialized materials innovation ecosystem.

Lithium metal anodes (LMAs), featuring an extremely high theoretical specific capacity and the lowest redox potential among known anode materials, are widely recognized as a promising foundation for next-generation high-energy rechargeable batteries. Despite their unique advantages, the practical deployment of LMAs remains severely constrained by uncontrolled Li dendrite growth and low Coulombic efficiency. These issues mainly stem from the uneven deposition of lithium ions. Over the past decade, numerous strategies—such as artificial solid-electrolyte interphase (SEI) layers, and solid-state electrolytes—have been developed to address these bottlenecks. Among these methods, electrolyte additives are appealing due to their operational simplicity, low manufacturing cost, and high compatibility with practical battery configurations. Conventional additives typically function either as suppressors that inhibit Li nucleation at protrusions or as promoters that modify SEI composition to enhance interface stability. However, suppressors may lose their selectivity under high current densities because strong local electric fields can drive them toward both protrusions and recesses, weakening their suppressing capability. Meanwhile, selective accelerators that enhance Li⁺ reduction at recessed sites have been scarcely explored for LMAs, even though similar concepts are widely applied in industrial electroplating. In electroplating processes, leveling agents—often sulfur-containing molecules—can adsorb on the metal surface to accelerate bottom-up cation growth by the leveling effect of superfilling. Here, a synergistic dual-additive electrolyte strategy is proposed, combining N,N'-diethylthiourea (DTHU) with dodecyl trimethylammonium cations (DTA⁺). The two additives collaboratively regulate Li⁺ solvation, interfacial adsorption, and deposition kinetics, thus enabling smooth lithium plating even at elevated current densities.

Electrolytes were prepared by dissolving lithium salts in ether- or carbonate-based solvents, followed by the introduction of DTHU and/or DTA⁺ at controlled concentrations. Electrochemical evaluation was conducted using CR2032 coin-type symmetric cells and Li-Cu half cells assembled in an oxygen- and moisture-free glovebox. Long-term cycling, rate capability tests, and Coulombic efficiency measurements were performed under galvanostatic conditions. Full cells employing Li₄Ti₅O₁₂ (LTO) cathodes were assembled to examine the applicability of the additive strategy in practical battery environments.

To probe interfacial chemistry, X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and energy-dispersive X-ray (EDX) mapping were employed. The adsorption behavior of DTHU and DTA⁺ on Li metal was elucidated through density-functional-theory calculations and molecular dynamics simulations. Moreover, the structural evolution of the SEI and ion-transport kinetics were further analyzed through electrochemical impedance spectroscopy and Arrhenius fitting.

A combination of theoretical calculations and experimental characterization revealed distinct yet complementary roles of the two additives. DTHU exhibited a significantly stronger adsorption affinity toward lithium metal compared with solvent molecules, enabling selective accumulation at recessed regions of the metal surface. EDX-mapping and time-dependent molecular simulations confirmed that DTHU molecules migrate toward pits during interfacial equilibration, aligning favorably to promote localized Li⁺ reduction. Conversely, DTA⁺ adsorbs preferentially on surface protrusions, as evidenced by a positive shift in the potential of zero charge obtained from AC voltammetry. This adsorption weakens the local electric field near convex regions and reduces the tip effect, which is responsible for accelerated dendrite growth in conventional electrolytes. When both additives are introduced simultaneously, Li⁺ flux is redistributed more homogeneously across the electrode surface. COMSOL simulations showed that the introduction of DTHU dramatically suppresses the unstable dendritic morphology that appears in the blank ether electrolyte. Instead, Li deposits in a dense and uniform manner.

In addition to altering deposition behavior, the dual-additive system significantly modifies the solvation structure of Li⁺ and the chemical makeup of the SEI. Raman spectroscopy revealed enhanced dissociation of lithium salt due to strong interactions between DTHU and anions. Molecular dynamics simulations further showed that the primary Li⁺ solvation sheath shifts toward a higher proportion of 1,3-dioxolane molecules, known precursors for forming polymeric SEI components. XPS analyses demonstrated that the combined additives promote the formation of a LiF-rich SEI, which possesses high mechanical robustness and ionic conductivity. Arrhenius analysis of charge-transfer resistance indicated a substantial reduction in Li⁺ desolvation energy, confirming accelerated interfacial kinetics.

These structural and interfacial benefits translated directly into superior electrochemical performance. Symmetric Li || Li cells using the dual-additive electrolyte cycled stably than 1500 h at 1.0 mA·cm^-2 with a low and stable overpotential of less than 80 mV. High-rate tests further demonstrated that the dual-additive electrolyte maintained smooth plating behavior even under 4.0 mA·cm^-2. Meanwhile, Cu-Li half cells exhibited higher Coulombic efficiencies and lower nucleation overpotentials, confirming improved initial Li deposition uniformity. In full-cell configurations, Li || LTO batteries employing the dual-additive electrolyte achieved stable cycling 500 cycles at 1.0 C with excellent capacity retention. This performance markedly exceeded that of full cells based on the baseline electrolyte, which suffered accelerated capacity fade due to dendrite-induced side reactions.

This study demonstrates a synergistic electrolyte-additive strategy inspired by industrial electroplating principles. By combining DTHU and DTA⁺, the approach simultaneously equalizes Li⁺ flux distribution, refines the ion-solvation environment, and guides the formation of a robust LiF-rich SEI. Together, these effects prevent dendrite formation even at high current densities and enable long-term cycling stability. The dual-additive electrolyte allows symmetric Li||Li cells to operate stably for over 1500 h and significantly improves the rate capability and cycle life of LTO full cells. The findings highlight the potential of electroplating-derived concepts as a practical and economical route to safe, dendrite-free lithium metal batteries. This strategy may be further extended to other monovalent and multivalent metal anode systems in future studies.

Sodium-ion batteries (SIBs) have garnered significant attention as a promising alternative to lithium-ion batteries (LIBs) due to the abundance and cost-effectiveness of sodium resources. However, the development of high-performance solid-state electrolytes remains a major challenge in the advancement of SIBs. NASICON-type solid electrolytes, specifically Na₃Zr₂Si₂PO₁2 (NZSP), are known for their excellent ionic conductivity and structural stability, making them ideal candidates for use in SIBs. To further enhance their ionic conductivity, one common strategy is to dope low-valence cations into the structure, potentially replacing Zr⁴⁺ ions and increasing the concentration of Na⁺ ions. Despite the widespread use of Mg²⁺ doping in NASICON materials to enhance ionic conductivity, the underlying mechanism remains underexplored. Therefore, the aim of this study is to investigate the effect of Mg²⁺ doping on the microstructure and ionic conductivity of Na_3+2xMg_xZr_2-xSi₂PO₁₂ (NMZSPx) solid-state electrolyte ceramics and elucidate the underlying mechanism of ionic conductivity enhancement.

In this study, a series of Mg²⁺ doping Na_3+2xMg_xZr_2-xSi₂PO₁₂ (NMZSPx, 0 ≤ x ≤ 0.20) ceramics were synthesized via a traditional sintering method. The samples were characterized using several techniques, providing insights into the electrical properties and conductivity mechanisms. Electrochemical impedance spectroscopy (EIS) measurements were performed to evaluate the ionic conductivities of the samples across a range of temperatures. X-ray diffraction (XRD) analysis was employed to investigate the phase composition and crystalline structure of the samples. Solid-state nuclear magnetic resonance (SSNMR) spectroscopy, including ³¹P, ²⁹Si, and ²³Na Magic Angle Spinning (MAS) NMR, was used to analyze the local atomic environments and determine the distribution of different elements in the ceramics. Scanning electron microscopy (SEM) was used to examine the microstructure of the ceramics, with individual elemental maps to assess the distribution of Na, Mg, Zr, Si, P, and O elements.

The results of this study reveal that Mg doping significantly affects both the microstructure and the ionic conductivity of Na_3+2xMg_xZr_2-xSi₂PO₁₂ ceramics. As the Mg²⁺ doping concentration increases, the ionic conductivity initially increases, reaching a peak value at x = 0.12, with a conductivity of 1.54 × 10^-3 S·cm^-1 at 25 ℃, which is 3.13 times higher than that of the undoped sample. However, further doping beyond x = 0.12 leads to a decrease in conductivity, indicating an optimal doping concentration for ionic conductivity enhancement. XRD analysis indicates that the samples with doping amount x > 0.12 exhibit a characteristic diffraction peak of rhombohedral crystal at 30.2°. This indicates that as the amount of Mg²⁺ doping increases, the NASICON main phase of NMZSPx samples gradually transitions from monoclinic phase to rhombohedral phase. Mg²⁺ ions do not replace Zr⁴⁺ ions in the NASICON main phase as previously assumed. Instead, a large portion of Mg²⁺ ions preferentially forms sodium magnesium phosphate heterogeneous phases at the grain boundaries. This observation is consistent with the results from SSNMR, where the chemical shifts of those signal peaks in the ³¹P, ²⁹Si, and ²³Na MAS NMR spectra show significant changes in the local environments of these elements, reflecting the influence of Mg²⁺ doping on the phase composition and atomic distribution. The formation of these magnesium phosphate secondary phases indirectly increases the concentration of Na⁺ by altering the Si/P ratio in the NASICON structure. However, the increase in Na⁺ concentration is not the primary reason for the enhanced ionic conductivity. The key factor contributing to the increased ionic conductivity is the improvement in the microstructure of the NMZSPx ceramics. SEM images show that appropriate Mg²⁺ doping significantly reduces the porosity of the ceramic samples and enhances the connectivity at the grain boundaries, facilitating easier Na⁺ transport. Specifically, x = 0.12 sample exhibits the densest microstructure, with good contact between grains and no noticeable defects, resulting in the highest ionic conductivity. However, excessive Mg²+doping (x > 0.12) leads to the formation of more impurity phases and increased porosity, which hinders ion transport across the grain boundaries, resulting in a decrease in ionic conductivity. This suggests that while Mg²⁺ doping can improve the ceramics' microstructure and reduce grain boundary resistance up to a certain point, excessive doping leads to the formation of impurity phases that impede ionic conduction.

This study demonstrates that Mg²⁺ doping in Na_3+2xMg_xZr_2-xSi₂PO₁₂ ceramics enhances ionic conductivity by improving the microstructure, particularly by reducing porosity and enhancing grain boundary connectivity. The optimal doping concentration of Mg²⁺ ions is found to be x = 0.12, which exhibits the highest ionic conductivity. However, excessive Mg²⁺ doping leads to the formation of sodium magnesium phosphate heterogeneous phases and increased porosity, which hinders ion transport and reduces the overall conductivity. The results also suggest that Mg²⁺ ions primarily influence the NMZSPx ceramics' conductivity by modifying the microstructure and inducing the formation of impurity phases at the grain boundaries, rather than directly substituting for Zr⁴⁺ ions in the NASICON structure. These findings provide new insights into the role of Mg²⁺ doping in enhancing the ionic conductivity of NASICON-type solid-state electrolytes and highlight the importance of optimizing doping concentrations to balance the formation of impurity phases and the improvement of microstructural properties.

Li-rich Mn-based cathode materials have become an important candidate for next generation lithium-ion battery cathodes due to their high discharge specific capacity and wide voltage window. The Li-rich Mn-based oxide xLi₂MnO₃·(1-x)LiTMO₂ (TM=Mn、Ni、Co、Fe, etc.) exhibits advantages such as high energy density (~1000 W·h·kg^-1), and low cost. The layered Li-rich material consists of two components: LiTMO₂ and Li₂MnO₃. The Li₂MnO₃ component can be activated during the first charge above 4.5 V, and the oxygen redox reaction provides unique high capacity. However, severe side reactions and irreversible lattice oxygen release can trigger particle cracking, microcracks, and gas generation, leading to significant electrochemical performance degradation. Single-crystallization of particles, by eliminating grain boundaries, helps improve the structural stability of cathode materials and represents an effective strategy for enhancing battery cycling performance.

This study developed a simple and effective synthesis method to obtain micron-sized single-crystal Li-rich Mn-based cathode materials. Specifically, Mn_0.54Co_0.13Ni_0.13(CO₃)_0.8 precursor was synthesized using a carbonate co-precipitation method. The synthesized precursor was then mixed with 5% excess of Li₂CO₃ in a mortar. The mixture was loaded into a cylindrical pellet die with a diameter of 14 mm, and 300 MPa pressure was applied to the powder mixture in the cylindrical die and maintained for 1 min before removal. A two-step calcination process (with a heating rate of 3 ℃·min^-1) was employed, with the sample calcined in air at 500 ℃ for 3 h, and at 950 ℃ for 15 h. Finally, the sample was cooled to room temperature and ground to obtain the lithium-rich single-crystal material Li_1.2Mn_0.54Ni_0.13Co_0.13O₂ (LR-SC).

By employing a precursor densification strategy to reduce interfacial fusion resistance between particles and enhance mass transfer at particle interfaces, it facilitated grain fusion growth and enabled the formation of micron-sized single-crystal particles of LR-SC with particle sizes ranging from 1 μm to 3 μm. The results indicate that the coin cell assembled with the single crystal material delivers an initial discharge capacity of 243.3 mA·h·g^-1 at 0.2 C. Compared with polycrystals, the capacity retention rate after 200 cycles at 0.5 C is increased from 44.9% to 73.1%. The assembled pouch cell (10 mA·h) keeps 78.8% capacity retention rate after 250 cycles at 1 C, displaying remarkable rate capability and cycling stability.

The synthesized single-crystal Li-rich Mn-based cathode material exhibits uniform particle size, superior interfacial stability and cycling stability. By comparing the failure processes of single-crystal particles and polycrystalline secondary spherical particles, its stabilization mechanism was revealed. Compared with typical polycrystalline cathodes, the single-crystal material mitigates the transformation of the layered structure of layer into spinel and rock-salt phases, releasing only minimal gas during the first cycle, significantly enhancing the safety and practicality of material applications. This method provides a simple and feasible way for synthesizing micron-sized single-crystal Li-rich Mn-based cathode materials.

Transition metal phosphides exhibit excellent energy storage characteristics in the field of supercapacitors. However, in practical applications, due to their relatively weak electron conduction ability, these materials lead to the blocking of charge transport inside the material and at the electrode/electrolyte interface, thereby limiting the power density of supercapacitors; more importantly, in the long-term charge-discharge cycle, transition metal phosphides are prone to structural degradation, which will seriously affect the long-term stability and service life of supercapacitors. In this work, MOF was used as a self-sacrificing template to construct a hierarchical NC@MOF@NCP composite (~25.4 mg·cm^-2) with high active material load by hydrothermal method combined with controllable electrodeposition technology. The skeleton structure of the NC@MOF @NCP composite has 3D conductive channel and mesoporous characteristics, which significantly reduces the charge transfer impedance of the material when improving its energy density and stable cycle.

Preparation of NiCo-LDH: 0.290 79 g of Ni(NO₃)₂·6H₂O, 0.582 06 g of Co(NO₃)₂·6H₂O, 0.074 08 g of NH₄F and 0.300 30 g of CO(NH₂)₂ were dissolved separately in 50 mL of deionized water. After stirring for 20 min, a 3 cm×4 cm piece of nickel foam (NF) was transferred, together with the precursor solution, into a stainless-steel autoclave lined with polytetrafluoroethylene (PTFE). The mixture was then heated to 120 ℃ and left to react for 5 h, yielding NiCo-LDH nanorods (NC). To prepare NiCo-LDH@Co-MOF: 0.873 1 g of Co(NO₃)₂·6H₂O and 0.210 1 g of 1,3,5-benzenetricarboxylic acid were dissolved in 20 mL of a mixture of N,N-dimethylformamide (DMF) and ethanol (volume ratio 1:1) to form Solution A. Subsequently, 0.5 g of polyvinylpyrrolidone was dispersed in 10 mL of deionized water to yield Solution B, which was then slowly added to Solution A with thorough mixing. The mixture was then transferred, together with the Ni foam bearing the deposited NiCo-LDH, to a stainless-steel reactor lined with polytetrafluoroethylene. The mixture was then maintained at 180 ℃ for 10 h, yielding the purple product, NiCo-LDH@Co-MOF (NC@MOF). To prepare NiCo-LDH@Co-MOF@NiCoP: 5.815 8 g of dissolve Ni(NO₃)₂·6H₂O, 5.820 6 g of Co(NO₃)₂·6H₂O and 2.119 8 g of NaH₂PO₂·H₂O separately in a 100 mL mixture of ethanol and deionized water (volume ratio 1:1). NiCoP nanosheets were then electrodeposited onto the NC@MOF framework via cyclic voltammetry. In a three-electrode system, the NC@MOF served as the working electrode, Pt as the counter electrode and Ag/AgCl as the reference electrode. Within the -1.2 to 0.2　V potential window, 20 cycles were performed at a scan rate of 10 mV·s^-1, yielding the product NiCo-LDH@Co-MOF@NiCoP (NC@MOF@NCP). The loading mass of NC, NC@MOF and NC@MOF@NCP were 2.7, 10.5 mg·cm^-2 and 25.4 mg·cm^-2 respectively.

After 20 cycles of electrochemical deposition, the product NC@MOF@NCP primarily consists of a mixed phase comprising MOF, Ni(OH)₂ and Co_3.5(OH)·0.11H₂O, Ni(HPO₃)H₂O and (Ni_0.65Co_0.35)₃(PO₄). FESEM and TEM images reveal that the NC@MOF nanorods are encapsulated by ultrathin, low-crystallinity NiCoP nanosheets, forming a highly loaded core-shell structure of NC@MOF@NCP. The Co-MOF serves as a sacrificial template that provides skeletal support for the deposition of high-loading NiCoP, and also effectively increases the electrode's specific surface area, offering more active sites for rapid, reversible Faradaic reactions. Electrochemical impedance spectroscopy (EIS) results indicate that the NC@MOF@NCP composite electrode exhibits low R_s (0.74 Ω) and R_ct (0.34 Ω) values. This low electrode-electrolyte interface charge transfer resistance contributes to the electrode's enhanced overall electrochemical performance.

A hierarchical NC@MOF@NCP nanorod electrode loaded with a highly active material has been constructed. This electrode's mesoporous system synergizes with the phosphide's metallic electronic structure, significantly reducing charge transfer impedance to 0.34 Ω. The optimized electrode exhibits a surface capacitance of 21.49 F·cm^-2 and high-capacity retention of 79.65% at 50 mA·cm^-2. Its outstanding rate performance is attributed to rapid charge redistribution mechanisms at the layered heterointerfaces. The assembled asymmetric supercapacitor of NC@MOF@NCP//AC achieved an energy density of 1.55 mW·h·cm^-2 at a power density of 8 mW·cm^-2 and demonstrated excellent cycling stability, retaining 86.8% of its capacity after 8000 cycles.

The 1.68-1.73 eV bandgap inorganic perovskite has excellent photovoltaic and thermal stability, and there is almost no risk of phase separation. It is one of the excellent top cell candidates for tandem solar cells (TSCs). However, the extremely serious non-radiative recombination within inorganic perovskite solar cells (IPSCs) severely restricts the improvement of the PCE of single-junction and TSCs devices. Studies have shown that the defect density on the surface of perovskite solar cells is three orders of magnitude higher than that within the material. Therefore, the rational regulation of the defect density on the surface is indispensable for enhancing the performance of photovoltaic devices.

This paper utilizes the dual (pentafluorobenzene) zinc (B(PFP)Zn) to manage the interface defect density between the photoabsorption layer and the ETL. After the B(PFP)Zn treatment, the device defect density has decreased from 1.63×10¹⁶ cm³ to 1.32×10¹⁶ cm³. Based on this, the PCE of the inverse-type devices fabricated by air was significantly enhanced from 16.07% to 18.72%. Both humidity and thermal stability were improved to a considerable extent.

The diffraction peaks of the inorganic perovskite corresponding to the B(PFP)Zn treatment have been enhanced. This is because B(PFP)Zn interacts with the inorganic perovskite during the secondary annealing process, thereby achieving recrystallization. Observe the surface morphology of the films before and after B(PFP)Zn treatment by means of SEM. SEM images indicate that the surface pores of the films treated with B(PFP)Zn are reduced. The surface morphology of the film was analyzed by using atomic force microscopy (AFM), the surface roughness of the film treated with B(PFP)Zn was reduced. After the B(PFP)Zn interface treatment, the PCE of the device was significantly enhanced from 16.07% to 18.72%. The average open-circuit voltage (V_OC) of the devices increased by 70 mV, and the average FF increased from 77% to 81%.

The films treated by B(PFP)Zn surface treatment have higher PL intensity and the carrier lifetime is nearly twice that of the reference group films, indicating that the defect density at the perovskite/ETL interface has decreased and non-radiative recombination has been suppressed. The devices treated with B(PFP)Zn exhibit lower leakage current. Carry out the space charge limited current (SCLC) tests on the two devices by using the pure hole devices, after the B(PFP)Zn surface treatment, the defect density decreased from 1.63×10¹⁶ cm³ to 1.32×10¹⁶ cm³.

The humidity stability of the two devices was monitored in an environment with 20% to 30% humidity, the PCE of the reference group devices dropped to 80% of the initial value at 115 h, while that of the experimental group dropped to the same level at approximately 300 h.

In this paper, B(PFP)Zn was utilized to perform post-treatment on the surface of CsPbI_2.85Br_0.15 film. The recrystallization process enhanced the crystallization quality of the film, effectively reduced the defect density, to some extent suppressed non-radiative recombination, and decreased the accumulation of charge carriers at the interface. The inverse-phase IPSCs prepared based on air achieved a record PCE of 18.72%, with an average V_OC increase of up to 70 mV. This strategy is simple and highly repeatable, providing a new scientific idea and technical route for the transformation and upgrading of the photovoltaic industry.

A series of La³⁺-doped Ag₁₀Si₄O₁₃ nano-photocatalysts were synthesized via the sol-gel method. The regulation mechanism of La³⁺ doping on the composition, crystal structure, microscopic morphology, and photoelectric properties of the photocatalyst was systematically investigated by characterization techniques including XRD, XPS, TEM, and paramagnetic resonance spectrometer (EPR), combined with density functional theory (DFT) calculations. Using tetracycline hydrochloride (TCH) as the target pollutant, the influence pattern and promotion mechanism of La³⁺ doping on the photocatalytic degradation performance of TCH were investigated. The results show that La³⁺ substitutes Ag⁺ into the Ag₁₀Si₄O₁₃ lattice to trigger lattice distortion (the maximum cell volume change rate is 1.06%), enhance the ferroelectric built-in electric field, and induce the generation of a small amount of Ag monomers on the Ag₁₀Si₄O₁₃ surface to form an Ag/Ag₁₀Si₄O₁₃ Schottky junction. The synergistic effect of these two factors simultaneously controls the carrier transport path from the crystal interior to the surface, driving h⁺ to accumulate on the Ag₁₀Si₄O₁₃ surface and e^- to enrich on the metallic Ag, thereby effectively improving carrier separation efficiency and achieving significant enhancements in degradation rate and photoreduction resistance. The injection of La-5d state electrons into the conduction band forms a donor level, reducing the material's band gap from 1.82 eV to 1.72 eV, lowering the work function by 0.17 eV, significantly broadening the photoresponse range to 683 nm, and increasing carrier density. The 1% (in mass) La³⁺-doped sample achieved a TCH degradation rate of 90% (k = 0.031 04 min^-1), representing a 15% improvement in efficiency and a 20% increase in rate compared to the undoped system. Furthermore, the activity retention rate remained above 90% after five cycles, and the material composition tended to stabilize. Free radical trapping experiments indicated that h⁺ is the primary active species in the photocatalytic reaction, with •O₂- and •OH playing synergistic roles.

The photocatalysts were prepared by the sol-gel method. 0.9 g of citric acid was dissolved in anhydrous ethanol, after which 9.5 mL of tetraethyl orthosilicate was added dropwise and stirred for 1 h, followed by the dropwise addition of 3 mL of distilled water and continued stirring for another hour; the mixture was then sealed and aged for one week to obtain a colorless and transparent silicic acid sol. Subsequently, 6.39 mL of a 0.38 g/mL AgNO₃ solution and a specified amount of lanthanum (III) nitrate hexahydrate were added to this silicic acid sol, stirred for 1 h, and aged for 24 h to yield the precursor sol. The precursor sol was dried, ground, and heat-treated in a muffle furnace at 400 ℃ for 5 h to produce La³⁺-doped Ag₁₀Si₄O₁₃. By varying the amount of lanthanum(III) nitrate hexahydrate added to achieve La³⁺ doping levels of x%(in mass fraction) (x = 0, 0.50, 1.00, 1.25, 1.50, 2.00) relative to the mass of Ag₁₀Si₄O₁₃, a series of La³⁺-doped Ag₁₀Si₄O₁₃ photocatalysts were prepared, labeled as ASO (for x = 0) and x L-ASO (where x represents the specific doping level).

The crystal structures of the photocatalysts were analyzed by a D8/axs type ray diffractometer (XRD), and the lattice parameters of the samples were determined by Rietveld refinement using GSAS software. The surface composition and electronic states of the samples were analyzed by X-ray photoelectron spectroscopy (XPS) using AXISSUPRA model. A JEM-2010 transmission electron microscope (TEM) was used to observe the microscopic morphology of the samples, and the elemental distributions were analyzed by an accompanying energy spectrometer (EDS). The JW-BK100 A Specific Surface Area and Pore Size Analyzer was used to test the specific surface area and the maximum pore size of the photocatalysts.The light absorption properties of the samples were tested using a UV-Vis DRS (model U-3900H). The fluorescence intensity of the photocatalysts was tested by Fluorescence Spectrometer (PL) (model F-97). An electrochemical impedance test and Mott-Schottky curve test were performed using a CHI660D electrochemical workstation. An electron EPR (model EPR) 200M was used to detect active substances.

Weigh 0.1 g of photocatalyst in 100 mL of TCH solution (pH 6) with a concentration of 10 mg/L, dark adsorption for 30 min to reach the adsorption equilibrium and then turn on the 300 W xenon lamp for the photocatalytic reaction, and sample every 10 min, centrifuged to take the supernatant in the cuvette, and calculated the degradation rate by using UV-Vis DRS to test the concentration of TCH. The test samples were recovered and the above steps were repeated for five cycles of testing. Simulations were carried out using Materials Studio 2020 software developed by Accelrys, based on the generalized gradient approximation (GGA) plane-wave ultrasoft pseudopotential method in the DFT framework to describe the interactions between the ionic potentials and the valence electrons, and the exchange-correlation energies between electrons were described by the Perdew-Burke-Ernzerhof (PBE) generalized function. Geometry optimization and energy calculations were performed for all cell models using the GGA+U method without considering spin-polarization effects, with U_Ag-p = 6 eV, U_O-p = 4 eV, and U_Si-p = 4 eV. The valence electron groupings used to construct the pseudopotentials are Ag 4d¹⁰5s¹, O 2s²2p⁴, Si 3s²3P², and La 5p⁶6s²5d¹. The plane-wave truncation energy (E_cut) is set to 480 eV and a 2 × 2 × 2 K-point grid is used to sum the Brillouin zone.

The XRD diffraction patterns show that the characteristic diffraction peaks of Ag₁₀Si₄O₁₃ appeared in all the samples, and the doping of La³⁺ did not change the crystal structure type of ASO. The XPS test results showed that there is metallic Ag in the 1.0 L-ASO, and the La element stably exists in the ASO cell as La³⁺. The TEM photographs show that La³⁺occupies some Ag⁺ sites in the ASO lattice through substitutional doping, and the corresponding metallic Ag are polarised on the surface of the material, forming a metal-semiconductor contact interface with the L-ASO and constituting a Schottky junction. La³⁺doping showed an inverted 'V'-shaped dependence on the degradation rate of TCH, in which the 1.0 L-ASO sample showed the best degradation performance, and the degradation rate of TCH by the 1.0 L-ASO sample remained more than 90% of the initial efficiency after five cycles of testing. DFT calculation analysis of ASO before and after doping revealed that: After La³⁺ doping, the band gap is reduced; the work function decreases from 4.22 eV to 4.05 eV and the Fermi level shifts towards the conduction band, significantly enhancing the strength of the ferroelectric built-in electric field.

La³⁺-doped Ag₁₀Si₄O₁₃ nano-photocatalytic materials were successfully prepared by sol-gel method. The optimal doping site of La³⁺ was determined by combining with DFT calculations. It was confirmed that La³⁺ substitutional doping triggered lattice distortion, with a unit cell volume distortion up to 1.06%. La³⁺ doping significantly enhanced the intensity of ferroelectric built-in electric field and induced the in-situ generation of metallic Ag on the surface, forming an Ag/Ag₁₀Si₄O₁₃ Schottky heterojunctions. The injection of La 5d state electrons into the conduction band forms new electronic states near the conduction band minimum, which reduces the band gap and effectively broadens the photoresponse range to 683 nm. The synergistic effect between the optimized ferroelectric built-in electric field within the crystal and the surface Schottky junction simultaneously controls the carrier transport path from the crystal interior to the surface. This drives the accumulation of h⁺ on the Ag₁₀Si₄O₁₃ (ASO) surface and the enrichment of e- on the metallic Ag, significantly inhibiting carrier recombination, enhancing separation efficiency, and ultimately achieving a significant improvement in the degradation rate and the photoreduction resistance. h⁺ plays a dominant role in the degradation process, and La³⁺ doping can significantly enhance the h⁺ yield. When the doping amount is 1% (in mass fraction), the degradation rate of TCH reaches 90%, which represents a 15% improvement compared to the undoped system. Furthermore, after five cycles, the degradation rate remained above 90% of its initial value, demonstrating excellent service stability. This work reveals a dual-effect mechanism where the triple synergistic effects of rare-earth doping-induced band narrowing, enhanced polarization electric field, and surface Schottky junction improve both photocatalytic efficiency and photostability. It provides a new strategy for developing highly efficient and stable silver-based photocatalysts.

The photocatalytic CO₂ reduction technology has become a research hotspot in the field of carbon neutrality because it can simultaneously achieve "carbon fixation + solar energy conversion". CeO₂ has been widely applied in the field of photocatalysis due to the advantages of CO₂ adsorption by oxygen vacancies (Ce³⁺-O^-) and the carrier buffering capacity of the Ce³⁺/Ce⁴⁺redox couple. Bi₂S₃, due to its narrow bandgap (1.3–1.7 eV), unique layered structure, and broad light absorption range, has become an ideal candidate for broadening the spectral response. When constructing a heterojunction between Bi₂S₃ and CeO₂, the oxygen vacancies of CeO₂ can serve as CO₂ adsorption anchors, and the built-in electric field at the interface between the two can promote the directional migration of electrons and holes. In-situ introduction of metallic Bi nanoparticles can enhance the visible light absorption through the Surface Plasmon Resonance (SPR) effect and further inhibit the recombination of photogenerated carriers as electron traps. Meanwhile, one-dimensional nanofibers, because of their high aspect ratio, continuous pore structure, and mechanical stability, not only provide a three-dimensional template for the in-situ growth of Bi@Bi₂S₃, but also form microchannels through the interweaving of fibers, promoting the diffusion of CO₂ and the desorption of products, making them an ideal choice for photocatalytic carriers.

Experiment In this study, CeO₂ fibers prepared by the electrospinning technique were used as the substrate, ascorbic acid was used as the reducing agent, and deionized water, ethylene glycol, ethanol, and ethylenediamine were used as solvents respectively. Combined with the hydrothermal synthesis method, Bi@Bi₂S₃ composite CeO₂ nanofibers in the shapes of nanosheets, nanospheres, nanorods, and nanocubes were prepared. Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) revealed that Bi₂S₃ was constructed on the surface of CeO₂ fibers in different morphologies, and the in-situ generated Bi nanoparticles were uniformly anchored at the interface of Bi₂S₃, forming a unique three-dimensional structure. X-ray Photoelectron Spectroscopy (XPS) and Electron Paramagnetic Resonance (EPR) confirmed that Bi₂S₃ and CeO₂ achieved directional separation of carriers through a type-S heterojunction. Highly active electrons were retained in the conduction band of Bi₂S₃ for CO₂ reduction, and strongly oxidizing holes were retained in the valence band of CeO₂ to drive water oxidation. The SPR effect of Bi nanoparticles enhanced the visible light absorption ability, and at the same time, they served as electron bridges to shorten the charge migration path.

The photocatalytic CO₂ reduction reaction was carried out using a self-made airtight reaction device, with a 300 W Xe lamp (AM 1.5G filter, 100 mW·cm^-2) as the light source to simulate sunlight. After 3 hours of light irradiation, the Bi@Bi₂S₃/CeO₂ ternary composite fiber system showed excellent photocatalytic CO₂ activity. Among them, the nanosheet structure, with its high specific surface area and large pore volume, could form more active sites, resulting in the best photocatalytic CO₂ reduction effect. The yields of CO and CH₄ reached 14.58 μmol·g^-1·h^-1and 5.68 μmol·g^-1·h^-1respectively. Different structural characteristics such as the high light absorption efficiency of the cavity in the pompon structure, the strong local electric field at the edges of the cube structure, and the rapid separation of products in the rod-like structure all effectively improved the CO₂ reduction efficiency. The generation rates of CO were 12.26, 11.71, and 10.55 μmol·g^-1·h^-1 respectively, and the generation rates of CH₄ also reached 4.34, 4.12, and 3.38 μmol·g^-1·h^-1respectively. Meanwhile, the Bi@Bi₂S₃/CeO₂ ternary composite fibers showed good photocatalytic stability. Under the above reaction conditions, after 5 consecutive cycles (accumulated 15 hours), the yields of CO and CH₄ still remained above 90% of the initial values.

In this study, a Bi@Bi₂S₃/CeO₂ composite photocatalyst was successfully prepared using CeO₂ nanofibers as the substrate and combining the hydrothermal method. Material characterization showed that Bi₂S₃ and CeO₂ constructed a S-scheme heterojunction through interfacial interaction, achieving efficient separation of photogenerated carriers. Highly active electrons were retained in the conduction band of Bi₂S₃ for CO₂ reduction, and holes were retained in the valence band of CeO₂ to drive water oxidation. The Bi nanoparticles deposited on the surface enhanced the visible light absorption through the SPR effect, and served as electron bridges to accelerate charge migration and prolong the lifetime of photogenerated carriers. Bi@Bi₂S₃/CeO₂ showed excellent photocatalytic CO₂ reduction performance. This study provides a new idea for the design of efficient CeO₂-based photocatalysts: retaining highly active carriers through a S-scheme heterojunction and optimizing light absorption and charge transfer by combining the SPR effect of non-noble metal nanoparticles. This strategy has important reference value for the development of low-cost and highly stable CO₂ reduction catalysts and is expected to promote the practical application of photocatalytic technology in the field of carbon cycle.

Wide-bandgap oxide semiconductors Ga₂O₃ and ZnO have garnered significant attention due to their exceptional optoelectronic properties and thermo-chemical stability. This study innovatively integrates a ZnO quaternary alloy (BeZnOS) with Ga₂O₃ to construct a novel BeZnOS/Ga₂O₃ heterojunction ultraviolet photodetector. By leveraging the synergistic band modulation via isovalent ion (Be²⁺/S^2-) co-doping in ZnO, we aim to enhance the photogenerated carrier separation and transport efficiency through optimized heterojunction band alignment, ultimately developing a high-performance self-driven deep-UV photodetector. This work provides new insights into ZnO bandgap engineering and establishes a materials foundation for developing high-performance, all-oxide-based deep-ultraviolet photodetectors.

The heterostructure thin films were synthesized via pulsed laser deposition (PLD) using KrF excimer laser ablation (λ=248 nm) on c-plane sapphire substrates. Ceramic targets of BeZnOS and Ga₂O₃ were prepared by solid-state sintering at 1200 ℃ under argon atmosphere. Prior to deposition, substrates underwent rigorous cleaning in acetone, ethanol, and deionized water (15 min each) followed by N₂ drying. BeZnOS films were grown at 700 ℃ with 2 Pa O₂ partial pressure and 350 mJ laser energy, while Ga₂O₃ layers were selectively deposited through a shadow mask at 650 ℃ (2 Pa O₂, 250 mJ). Post-growth in situ annealing was performed at 550 ℃ (20 Pa O₂, 20 min) to optimize crystallinity. Device fabrication was completed by depositing Pt (high-work-function) and Al (low-work-function) electrodes through magnetron sputtering (100 W, 1.5 Pa Ar) to form Pt/BeZnOS/Ga₂O₃/Al architectures with 200 μm×200 μm contacts.

Comprehensive structural and optoelectronic characterizations were conducted using high-resolution X-ray diffraction (XRD), UV-Vis-NIR transmission spectroscopy, field-emission scanning electron microscopy with energy-dispersive spectroscopy (FESEM/EDS), and X-ray/ultraviolet photoelectron spectroscopy (XPS/UPS). These techniques systematically analyzed crystalline phase purity, optical bandgaps, elemental distribution profiles, and energy band configurations. A Omni-λ 3027 setup consisting of Keithley 2635 digital source meter, probe station, electromagnetic shielding dark box, monochromator, 150 W xenon lamp and phase-locked amplifier, was utilized to measure the optoelectronic performances of the photodetector.

Structural characterization via high-resolution XRD confirmed phase-pure hexagonal wurtzite BeZnOS and monoclinic β-Ga₂O₃ film. Optical transmission spectrum revealed dual absorption edges, corresponding to direct bandgaps of 3.30 (BeZnOS) and 4.50 eV (Ga₂O₃) via Tauc analysis. Cross-sectional FE-SEM demonstrated layer thicknesses of 212 nm (BeZnOS) and 165 nm (Ga₂O₃), while EDS mapping confirmed elemental stratification with well-defined heterointerfaces. The fabricated Pt/BeZnOS/Ga₂O₃/Al photodetector exhibits pronounced rectifying behavior (rectification ratio: 1.72×10²) and achieved self-powered operation at zero bias. Notably, dual spectral response peaks emerged in the UVC and UVA regions, with a peak responsivity of 23.5 mA/W at 240 nm and a corresponding specific detectivity of 2.3×10¹¹ Jones. The device further demonstrated rapid response kinetics (rise time τ_r = 0.09 s; decay time τ_d = 0.10 s). These exceptional characteristics originate from the synergistic coupling of built-in electric fields: 1) the type-II band alignment at the BeZnOS/Ga₂O₃ heterojunction (ΔE_C = 1.9 eV, ΔE_V = 0.7 eV), and 2) the Schottky barrier at the Pt/BeZnOS interface. This dual-field configuration drives efficient spatial separation of electrons and holes, reducing recombination and enhancing photocurrent generation. Additionally, the photoresponse characteristics of the device exhibit significant intensity dependence: under weak illumination, it demonstrates higher responsivity but slower response speed, whereas under strong illumination, it shows lower responsivity yet faster response speed. This phenomenon primarily originates from the carrier saturation effect in deep-level trap states, whereby high light intensity saturates the trap centers, thereby suppressing the persistent photoconductivity (PPC) relaxation process.

This work successfully demonstrates a high-performance self-driven deep-UV photodetector based on an engineered BeZnOS/Ga₂O₃ heterojunction, achieving high sensitivity (R_{240 nm} = 23.5 mA/W, D* = 2.3×10¹¹ Jones) and fast response (τ_r/τ_d=0.09 s/0.10 s) at zero bias. The fabricated heterojunction forms a type-II band alignment, which directionally couples with the built-in electric field of the Pt/BeZnOS Schottky junction to generate an enhanced composite field. This synergistic configuration significantly promotes the separation and transport of photogenerated carriers, ultimately enabling high-sensitivity and rapid-response self-powered operation. The innovative dual-junction synergistic modulation strategy demonstrates significant potential for advancing self-driven optoelectronic devices.

Ultra-hard materials, characterized by a hardness exceeding 40 GPa, showcase remarkable mechanical properties such as superior wear resistance and compressive strength, outperforming traditional hard materials. The mid-20th-century breakthroughs in techniques like powder metallurgy and high-pressure synthesis have established ultra-hard materials as a distinct and advancing field within materials science. Among these materials, diamond and cubic boron nitride (cBN) stand out as prime examples, finding extensive application across various industries including resource extraction, precision processing, electronics, aerospace, and scientific research. Despite their exceptional properties, diamonds are limited by their low oxidation temperature and reactivity with iron, while cBN, although chemically stable and effective for processing ferrous metals, has a lower hardness compared to diamond. These limitations highlight the need for the development of new ultra-hard materials that can combine the strengths of both diamond and cBN. B-C-N compounds, composed of boron, carbon, and nitrogen, benefit from the strong covalent bonds formed due to their close proximity in the periodic table, endowing them with exceptional chemical stability and mechanical strength. Their robust lattice structures contribute to their durability and toughness, making them highly suitable for applications that demand high stability and strength. Recent research has delved into various B-C-N materials: Nakano et al. (1994) synthesized cubic BCN phases under high-pressure and high-temperature conditions, Komatsu et al. (1996) produced cBC_2.5N with notable nano-scale characteristics and a bulk modulus greater than that of cBN, and Solozhenko et al. (2001) synthesized cubic BC₂N blocks with a remarkable hardness of 76 GPa, surpassing cBN. The advent of advanced computer technology has seen first-principles calculations based on density functional theory play a significant role in materials design. Researchers have proposed various BCN structures, such as orthogonal BC₂N (Mattesini et al., 2001) and zinc blende BC₂N (Sun et al.), which have shown potential as ultra-hard materials. Gao et al. (2018) introduced BC₆N structures with mixed hybridization, demonstrating one-dimensional conductive properties.This study presents two novel BCN structures that are stable under ambient pressure and possess both ultra-hard properties and excellent conductivity. This represents a significant advancement in the research of metallic ultra-hard materials and provides essential theoretical foundations for their future practical applications in materials science.

The structural models were constructed in the Materials Visualizer module of Materials Studio. The property calculations for the two different structures were performed using the CASTEP software package on the basis of density functional theory. The calculations employed ultrasoft pseudopotentials, and the exchange-correlation functional (GGA) was chosen to be the Perdew-Burke-Ernzerhof (PBE) form of the generalized gradient approximation. After a series of convergence tests, the plane wave cutoff energy was set to 630 eV; the first Brillouin zones of all structures were meshed using the Monkhorst-Pack method, with the spacing of the K-point grid set to 2π × 0.04 Å⁻¹. The convergence criteria for the structural relaxation process were for the total energy of the structure, the maximum ionic displacement, the maximum internal stress, and the change in the Hellmann-Feynman force for the ions to be less than 5.0 × 10⁻⁶ eV/atom, 5.0 × 10⁻⁴ Å, 0.02 GPa, and 0.01 eV/Å, respectively. The elastic constants and electronic band structures of the structures were calculated using the primitive cell. The phonon spectra of the two structures were calculated using the finite displacement method.

The results show that both P2/m-BCN and Pm-BCN structures are elastic and dynamically stable. Their thermodynamic stability was assessed by calculating formation enthalpies at various pressures. Both structures have positive formation enthalpies, indicating higher energy than graphite and hBN, necessitating external forces like high pressure or catalysts for formation. Beyond a critical pressure, the enthalpy becomes negative, suggesting these BCN structures can be synthesized from graphite and hBN.

Using the HSE06 mixed functional method, we studied their electronic properties under atmospheric pressure, revealing a certain degree of conductivity. Projected density of states (PDOS) calculations indicate that the conductivity is primarily due to the 2p orbitals of carbon and boron atoms, highlighting the role of orbital hybridization.

Mechanical property analysis shows that P2/m-BCN and Pm-BCN have bulk and shear moduli slightly lower than cBN, indicating high incompressibility and shear resistance. Vickers hardness calculations yield 43.7 GPa and 49.9 GPa for P2/m-BCN and Pm-BCN, respectively, confirming their potential as superhard materials.

Stress-strain studies reveal a high tendency for cleavage on the (001) plane, suggesting brittle fracture along this direction. Notably, P2/m-BCN exhibits a unique bimodal stress-strain curve along the [100] direction, indicating a staged fracture process: initial selective bond breaking, partial stress release, and subsequent network failure under higher strain. This provides insights into the mechanical stability and fracture toughness of these structures.

This study successfully designs two novel BCN structures, P2/m-BCN and Pm-BCN, via first-principles calculations. These structures exhibit exceptional elastic and dynamical stability as metastable phases at ambient pressure, establishing a theoretical basis for potential applications. Structural analysis indicates that P2/m-BCN has sp²-hybridized carbon atoms, while Pm-BCN contains boron-nitrogen units, endowing them with unique electronic structures and metallic properties. Mechanical assessments reveal high strength and rigidity, with the lowest tensile strengths along the [001] direction (39.7 GPa for P2/m-BCN and 42.4 GPa for Pm-BCN), suggesting a strong cleavage tendency on the (001) plane. Notably, P2/m-BCN exhibits a distinctive double-peak stress-strain behavior along the [100] direction. Electron localization function (ELF) analysis reveals a stepwise fracture mechanism: initial B-N bond rupture leads to partial stress release, followed by load transfer to the C-C network, which fails at higher strain. This highlights the transient load-bearing capacity of heterogeneous bonding networks. Overall, these metastable metallic BCN phases enhance the structural diversity of superhard materials, combining high mechanical strength, metallicity, and tunable anisotropic fracture behavior. These findings offer new theoretical insights for designing superhard multifunctional materials, with promising applications in cutting, wear resistance, and extreme environments.

06Ni9DR alloy steel has become a core material for LNG storage and transportation equipment due to its excellent low-temperature toughness (down to -196 ℃) and low thermal expansion properties. The 06Ni9DR alloy steel is heated at 1100-1250 ℃ before hot rolling. However, there are severe oxidation and difficulties in removing the oxide skin, which leads to increased processing costs. The protective coating method has become one of the main means of high-temperature oxidation protection for alloy steels due to its simple preparation process, wide applicability and freedom from shape and size limitations. In the previous stage, a reaction-sintered Al₂O₃-glass composite coating with 73.6% protection after oxidization at 1200 ℃ for 3 h was prepared by our team. The addition of SiC to deplete the oxygen inside the coating is expected to improve oxidation protection. It is worth noting that when there is liquid phase in the coating at high temperature, the SiC will act as foaming and leave pores in it, which will become the oxygen diffusion channel. Therefore, in this work, SiC-Al₂O₃-glass composite coatings with different silicon carbide contents were prepared, and the effect of silicon carbide content on the oxidation protection and its mechanism were revealed.

The crystal structure of the coating samples after heat treatment was by power X-ray diffraction using a diffractometer (10°-90°, X' pert pro, PHILIPS, Netherlands). The XRD spectra were recorded at 40 mA and 40 kV using Cu K_α radiation (λ=0.1542 nm). The apparent porosity (AP) and bulk density (BD) of the coating samples were measured by Archimedes drainage method. The microstructure and element analysis of the coating samples and steels with coatings were evaluated by using field emission scanning electron microscopy (SEM, EVO-10, ZEISS, Germany), equipped with an X-ray energy dispersive spectrometer (EDS, Xplose30, Oxford, Britain) at 16 kV. The average pore size inside the coating was counted by Image Pro Plus 6.0. The mass loss rate (β) of GC steels with coatings after oxidation test was referred to the Chinese industry standard for the determination and calculation method for oxidation burning loss of slab (YB/T 4773-2019). The pore size distributions and average pore diameter of coatings samples after heat treatment for 3 h were measured by mercury piezometer (5 nm-800 μm, AUTOPORE V9620, Micromeritics Instruments, America).

The composition of the physical phase showed that the SiC in the composite coatings could continuously oxidize to generate the square quartz phase, and the amount of generation increased with the content of SiC and the heat treatment duration. The average pore size of all coating samples after 10 min of oxidation was only about 2.5 μm. The number of macropores in the composite coatings with low SiC content increased significantly, and the average pore size also increased to 30.6 μm with the oxidation duration. The average pore size decreased with the SiC content in the composite coatings after heat treatment for 180 min. The excellent oxidation protection was observed for all steels with coatings after oxidation for 10 min, which was more than 96%. The oxidation protection ratio of the composite coating with the low SiC content decreased to 40.9% for 180 min, and the oxidation protection ratio of the composite coating with the high SiC content remained almost unchanged, up to 96.1%.

The main conclusions of this paper are summarized as following. The mechanism of "foaming attenuation" in composite coatings with low SiC content was revealed. There was a high content of liquid phase in it. During the oxidation process, the oxidation products of SiC, such as CO and CO₂, will be wrapped by the liquid phase. The amounts of gases wrapped inside the coating increased with the oxidation duration, resulting in a significant "foaming" phenomenon in the coating and the formation of large-size pore channels, which significantly reduced the oxidation protection. The mechanism of "oxygen depletion enhancement" in composite coatings with high SiC content was also revealed. The liquid phase content in composite coatings with high SiC content was low, and the generation of square quartz from the oxidation of SiC increased the viscosity of the liquid phase. The foaming effect of SiC was inhibited, resulting in the formation of a microporous structure with an average pore size of about 2.7 μm, effectively extending the oxygen diffusion path. At the same time, the oxygen in the diffusion process will be continuously consumed by the SiC in the composite coating, so that the excellent oxidation protection was provided at 1200 ℃ for different oxidation durations.

Titanium alloys are indispensable in aerospace and military fields for manufacturing precision components owing to their exceptional specific strength and stiffness—properties that enable weight reduction while maintaining structural integrity under high mechanical loads. However, in harsh low-temperature service environments, titanium alloys suffer from insufficient wear and corrosion resistance, necessitating surface modification. Ceramic coatings, renowned for their high hardness, excellent chemical stability, and resistance to extreme environments, are commonly applied to address this issue. Among various coating technologies, Plasma Electrolytic Oxidation (PEO) stands out due to its advantages of strong film-substrate adhesion and the ability to tailor coating composition for functionalization. Nevertheless, ceramic coatings—primarily composed of ionic or covalent bonds—exhibit inherent brittleness, which is exacerbated at low temperatures. This brittleness severely limits the service reliability and lifespan of titanium alloy components in low-temperature environments. Tetragonal zirconia (t-ZrO₂) has emerged as a promising toughening agent for ceramics by undergoing a martensitic transformation to monoclinic zirconia (m-ZrO₂) under external stress or temperature changes, accompanied by a 3%-5% volume expansion. This expansion generates a compressive stress field that inhibits crack propagation, thereby improving the coating's toughness. Critical to this effect is the martensitic transformation start temperature (M_s) of t-ZrO₂, which is strongly dependent on grain size. Optimizing the grain size of in-situ formed nano t-ZrO₂ to match specific low-temperature service windows thus becomes a key strategy for enhancing the low-temperature mechanical performance of PEO ceramic coatings.

This study aimed to systematically investigate the influence mechanism of in-situ nano t-ZrO₂ grain size on the low-temperature static and dynamic mechanical properties of Ti6Al4V-based PEO ceramic coatings, and to develop a practical process for improving the coatings' service reliability in cryogenic environments. To achieve this, the PEO process was optimized by adjusting the pulse frequency ranging from 500 Hz to 2000 Hz to prepare four sets of TiO₂/t-ZrO₂ composite ceramic coatings denoted as D1, D2, D3, and D4 samples with distinct average t-ZrO₂ grain diameters, alongside a reference sample (RS) without t-ZrO₂. The Ti6A14V substrates were first machined into two standard sizes: 10 mm × 10 mm × 1 mm for static mechanical testing and 60 mm × 6 mm × 1 mm for dynamic testing. Prior to PEO treatment, the substrates were sequentially grounded, cleaned with ethanol, and dried. The zirconium salt electrolyte used for D1-D4 samples consisted of 15 g/L K₂ZrF₆, 5 g/L (NaPO₃)₆, 5 g/L NaH₂PO₄, 10 g/L NH₄HF₂, and 1 L distilled water, and the phosphate electrolyte for RS contained 10 g/L (NaPO₃)₆, 10 g/L NaH₂PO₄, and 15 g/L NH₄HF₂. All PEO treatments were performed using a single-pulse DC power supply (MAO-20D) under constant current mode (0.2 A/cm²), a fixed duty cycle of 20%, and a treatment time of 20 min.

The t-ZrO₂ grain diameter decreased significantly with increasing PEO pulse frequency: D1 samples (500 Hz) had an average grain diameter of ~40 nm, D2 sample (1000 Hz) ~30 nm, D3 sample (1500 Hz) ~22 nm, and D4 sample (2000 Hz) ~17 nm. This trend was attributed to shorter single-pulse times at higher frequencies, which restricted t-ZrO₂ nanocrystal growth during PEO. XRD analysis revealed that all composite coatings consisted of t-ZrO₂, TiO₂, and a small amount of m-ZrO₂, with the t-ZrO₂ characteristic peak at 30.2° showing increased full width at half maximum and decreased intensity with higher pulse frequency—consistent with Scherrer formula calculations for reduced grain size. The M_s temperature of t-ZrO₂ decreased with decreasing grain diameter. XRD-derived t-ZrO₂ volume fraction (V_t) showed that V_t of D1 sample exhibited a sharp drop from 68% to 26% at 250 K, D2 sample and D3 sample at 200 K, while D4 sample showed no significant V_t change down to 150 K. This was explained by higher interfacial energy in smaller grains, which increased the martensitic nucleation energy barrier. When service temperatures were near M_s, the coatings' plastic deformation ability was significantly enhanced. Nanoindentation tests showed that D1-D4 samples had higher H and E than RS samples, with stepwise H³/E² increases corresponding to stress-induced martensitic transformation. Dynamic mechanical properties were markedly improved by t-ZrO₂ and smaller grain sizes. Dynamic Mechanical Analysis (DMA) results showed that D1-D4 samples had higher loss modulus and tanθ than RS samples across all temperatures. D1 sample peaked at 300 K, D2 sample at 250 K, D3 sample at 200 K, and D4 sample at 150 K, aligning with their M_s temperatures. Smaller grains exhibited superior damping due to increased grain boundary area, which promoted energy dissipation via grain boundary sliding and intragranular dislocation motion. MD simulations confirmed inhomogeneous strain distribution concentrated at t-ZrO₂/TiO₂ interfaces and t-ZrO₂ grains, and an inverse Hall-Petch effect in small grains. D4 sample sacrificed ~29% tensile strength compared to D1 sample to achieve a ~60% higher strain rate, enhancing ductility.

This work demonstrates that adjusting PEO pulse frequency to control t-ZrO₂ grain diameter is an effective strategy to optimize the low-temperature mechanical properties of ceramic coatings. The mechanism involving M_s temperature regulation, interfacial energy enhancement, and grain boundary sliding provides theoretical and experimental basis for the design of low-temperature vibration-resistant coatings on titanium alloys, which is of great significance for improving the service life of titanium alloy components in low-temperature aerospace environments.

The escalating demand for advanced energy storage systems in modern electronics, electric vehicles, and renewable power grids has propelled the development of high-performance dielectric capacitors. Among various types of capacitors, those based on polymer dielectrics are highly prized for their ultrahigh power density, low loss, and ability to operate at high voltages. However, a fundamental limitation of pure polymers is their relatively low dielectric constant, which constrains their energy storage density. A promising strategy to overcome this is to create composite materials that combine the high breakdown strength of polymers with the high dielectric constant of ceramic fillers. Sandwich-structured composites, in particular, have emerged as an ideal architecture. By strategically layering materials with complementary properties, it is possible to synergistically enhance both the dielectric constant and the breakdown strength, the two key parameters determining energy storage performance. Nevertheless, the design space for such multi-layered composites is vast and complex. Relying solely on experimental trial-and-error to optimize parameters like filler concentration and distribution is inefficient and costly. This study, therefore, aims to systematically design and theoretically investigate a novel sandwich-structured composite film. Using a phase-field model, we seek to elucidate the impact of critical microstructural parameters on the overall energy storage properties, providing a foundational guide for the experimental fabrication of next-generation high-energy-density capacitors.

A comprehensive phase-field model was developed to simulate the polarization response and dielectric breakdown behavior of the proposed sandwich-structured composite films. The modeled structure consisted of a three-layer film: two outer layers of polyetherimide (PEI), a polymer known for its high breakdown strength and thermal stability, and a central layer of polyvinylidene fluoride (PVDF), a polymer with a relatively high intrinsic dielectric constant. Barium titanate (BaTiO₃, BT) nanoparticles, a classic ferroelectric ceramic with a very high dielectric constant, were incorporated as fillers exclusively within the central PVDF layer. This design intentionally confines the high-dielectric-constant ceramic phase to the middle layer, shielding it with the high-breakdown-strength PEI outer layers. The phase-field simulations accounted for key physical phenomena, including electric field distribution and the evolution of electrical treeing during breakdown. The primary variables investigated were the volume fraction of BT nanoparticles and their spatial dispersion uniformity within the PVDF matrix. The energy storage density of the materials was subsequently obtained through calculation of the simulation data.

Simulation results revealed a non-monotonic relationship between the energy storage density and the volume fraction of BT nanoparticles. Initially, the energy storage performance enhanced with the addition of BT fillers. This improvement is attributed to the significant increase in the overall dielectric constant of the composite material due to the high dielectric constant of BT nanoparticles, enabling the storage of more charge under a given applied electric field. However, further increase in filler content led to deterioration in energy storage performance. This decline is primarily due to the formation of excessive interfacial areas between the polymer and ceramic phases and the increased likelihood of nanoparticle agglomeration. These interfaces create local field concentrations, which act as hotspots for premature electrical breakdown, thereby limiting the maximum applicable electric field. The trade-off between enhanced permittivity and reduced breakdown strength defines this optimal loading.

Furthermore, the study unequivocally demonstrated that the dispersion uniformity of the BT nanoparticles is a critical factor, often as important as the filler content itself. A heterogeneous, agglomerated distribution of nanoparticles resulted in severe local field distortion around the large clusters. These high-field regions became preferential paths for the initiation and propagation of breakdown channels, drastically reducing the overall dielectric strength of the composite. In contrast, a highly homogeneous dispersion of nanoparticles minimized local field concentrations, leading to a more uniform electric field distribution throughout the material. This uniformity allowed the composite to withstand much higher global electric fields before breakdown occurred, thereby maximizing the energy storage density. The results underscore that achieving a fine and uniform dispersion of nanofillers is paramount in material processing to realize the full potential of the composite design.

This work utilizes an advanced phase-field modeling framework to successfully design and analyze the energy storage performance of a PEI/PVDF-BT/PEI sandwich-structured composite film. The key conclusion is that both the volume fraction and the spatial distribution of ceramic nanofillers are decisive in determining the energy storage characteristics. An optimal BT nanoparticle volume fraction exists that balances the benefit of increased permittivity against the detriment of reduced breakdown strength. More significantly, a homogeneous dispersion of nanoparticles is crucial for mitigating local electric field concentrations and achieving a high breakdown strength. The findings provide profound insights and valuable quantitative guidance for the material-by-design of multilayer polymeric composites for high-energy-density capacitor applications.

Vacuum environment engineering has attracted significant attention due to its revolutionary applications in ultra-high-speed transportation, space technology, and frontier physics experiments. Concrete, as the most widely used construction material globally, remains an ideal choice for constructing ultra-high-speed vacuum pipelines and space bases. However, under harsh vacuum conditions, concrete faces severe challenges such as rapid dehydration, increased brittleness, drying shrinkage cracking, and reduced durability. To effectively enhance the vacuum service performance of concrete, this study designs a type of polymer-fiber modified concrete that leverages the film-forming toughening effects of polymers and the high strength and high elastic modulus characteristics of fibers to effectively mitigate the brittle behavior of concrete when exposed to vacuum. Utilizing acoustic emission techniques, the study examines how vacuum conditions, polymers, and fibers affect the mechanical properties of the modified concrete, further elucidating the underlying mechanisms with scanning electron microscopy (SEM) imaging.

Based on the principles of dense particle packing and gradational hydration, a mix design was developed for the binder system (including cement, fly ash, slag, and silica fume). Redispersible latex powder (RDP) and styrene-butadiene latex-modified emulsified asphalt (MEA) were selected as the polymer modification materials, while ultra-high molecular weight polyethylene fibers (PEF) and carbon fibers (CF) were chosen as the fiber reinforcement materials. To balance the strength and toughness of the concrete, the polymer dosage was set at 3.5% by mass of the binder, and the fiber volume fraction at 0.8%. A polycarboxylate-based superplasticizer was used at 1.2% by mass of the binder to ensure the workability of the fresh paste. The concrete was mixed using a dual-axis horizontal mixer. Initially, the coarse and fine aggregates and binder were dry-mixed for 1 min, then water and superplasticizer were added and mixed for 1 min. Finally, the polymer and fibers were incorporated and mixed for an additional 2-3 min to produce a fresh paste. The specimens were cured under standard conditions for 28 days before being exposed to either atmospheric exposure (AE) or vacuum exposure (VE) conditions.

AE was conducted in an ambient pressure room maintained at a temperature of (20±2) ℃ and a relative humidity of 55%-65%. VE was simulated using a homemade vacuum chamber with a vacuum pressure of approximately 100 Pa, a relative humidity of <10%, and a temperature essentially identical to that of the AE environment. In accordance with GB/T 50081-2019 "Standard Test Methods for the Physical and Mechanical Properties of Concrete," uniaxial compression tests and four-point bending tests were performed on specimens before and after exposure. Extensometers were used to record the axial and mid-span displacements of the specimens, and the corresponding stress-strain curves and load-displacement curves were plotted. During the mechanical performance tests, acoustic emission monitoring was conducted simultaneously. The mechanical damage characteristics of the concrete specimens were analyzed based on the acoustic emission signal intensity, b-value, and RA-AF plots. Finally, SEM was employed to observe the microstructure of the samples, revealing the degradation mechanism of concrete under vacuum exposure as well as the modification mechanism of the polymer-fiber combination.

VE is beneficial to the compressive strength of the concrete but detrimental to its bending strength. Compared with SC, the concrete in the control group under VE shows a 3.3% increase in compressive strength and a 22.8% decrease in flexural strength. For the polymer-fiber modified concrete, the compressive strength increased by 6%-31%, whereas the flexural strength decreased by 9%-16%. The modified concrete also exhibited significantly improved compression and flexural toughness under VE conditions. Notably, the combination of RDP and PEF yielded the greatest enhancement in mechanical properties, increasing compressive energy absorption capacity over two-fold and flexural energy absorption capacity more than ten-fold compared to the control group. Acoustic emission test results indicate that VE can reduce the damage-warning time by approximately 40%. The RA-AF correlation features show that the proportion of shear cracks increases significantly during the failure stage, which is attributed to intensified fiber-matrix interfacial debonding and the propagation of microcracks in the interfacial transition zone (ITZ). SEM images revealed that vacuum exposure promotes RDP/MEA film formation, creating an interpenetrating network of rigid cement paste and flexible film. This film bonds strongly with hydration products, reducing internal stresses and preventing microcracks. Additionally, PEF enhances post-peak toughness through its three-dimensional network and sliding energy dissipation, while the low fracture elongation and strong matrix adhesion of CF lead to brittle pull-out, thereby reducing concrete toughness.

The main conclusions of this paper are summarized as follows. The compressive and flexural toughness of the control group concrete under VE is significantly reduced, while modification with polymers and fibers can effectively avert this issue. Vacuum exposure enhances the film-forming effect of the polymer, effectively bridging hydration products and forming a high-toughness three-dimensional network structure together with the fibers, thereby inhibiting microcrack propagation. In particular, the combination of RDP and PEF exerts the optimal synergistic toughening effect, allowing the specimens to better retain their post-peak toughness. The synergistic mechanism of "film toughening-sliding energy dissipation" effectively reduces the brittleness of the concrete and improves its performance under vacuum conditions. These findings provide practical references for the optimized design of the new ultra-high-speed vacuum pipeline maglev transportation system as well as materials for deep space engineering.

Natural hydraulic lime (NHL), as an inorganic cementitious material with both hydraulic and air-hardening properties, mainly consists of dicalcium silicate, calcium hydroxide and calcium carbonate. It has moderate strength, good breathability and low soluble salt content, and its inherent cementitious properties are significantly superior to traditional lime in the restoration of cultural relics and ancient buildings. However, there are still considerable challenges in the large-scale application of NHL in the restoration of ancient buildings, and the performance requirements for NHL in different restoration projects of ancient buildings may also vary. Due to the typical phase composition of NHL, the pozzolanic effect of silica fume can significantly affect the hydration process in NHL. However, the mechanism of silica fume action around typical performance development is not clear, which is obviously insufficient to explain the relationship between the physical and mechanical properties of NHL under the action of silica fume and the phase composition and microstructure evolution, as well as the macro and micro development influence mechanism. In this work, the physical-mechanical properties of NHL under the action of silica fume and its phase composition and microstructure were studied, and the corresponding relationship between phase composition, pore structure and performance was explored.

The experiment utilized NHL (NHL2 level), whose main mineral composition was dicalcium silicate (β-C₂S), calcium hydroxide (Ca(OH)₂) and calcium carbonate (CaCO₃). Silica fume (SF) was used, which was composed of micro-nano amorphous silica spherical particles. The designed water-binder ratio was 0.55, and the binder-sand ratio was 1:3. The dosage of polycarboxylate superplasticizer was 0.4% (in mass, the same below). SF was used to replace 0%, 5%, 10% and 15% of the NHL mass respectively to prepare paste and mortar specimens. The specimens were covered with isolation film to prevent excessive evaporation of free water and were cured in a standard curing chamber for 72 h before demolding. After that, the specimens were cured under conditions of (20±2) ℃ and RH of 65%±5% for 7, 14 and 28 days.

The setting time, fluidity, compressive and flexural strength, drying shrinkage and mass change were tested in accordance with relevant standards. The phase composition was analyzed by XRD (Ultima IV, Rigaku) and thermogravimetry (STA 449 F3, NETZSCH). The microstructure and pore structure were analyzed by SEM (JSM-6700F) and MIP (Autopore 500) respectively. Before testing, the samples need to be treated with isopropanol to interrupt hydration, and then dried to a constant mass in a vacuum drying oven at 40 ℃.

SF has a significant promoting effect on the setting of NHL paste, the initial and final setting times of NS15 paste were shortened by 0.96 h and 0.60 h respectively, while the fluidity of its slurry and mortar decreased by 48.3% and 68.1% respectively. The mechanical strength of NS mortar with SF was significantly increased compared to NHL mortar. The compressive strength of NS5, NS10 and NS15 mortar at 28 days reached 4.62, 8.51 MPa and 10.92 MPa respectively. The drying shrinkage rate and mass loss rate of NS mortar with SF gradually increased, and the shrinkage amount exceeded that of NHL mortar after 7 days. At 28 days, the drying shrinkage reached about 1400 μm·m^-1, which was significantly greater than that of NHL mortar. The pozzolanic reaction caused free water to transform into chemical bound water, and the evaporation of free water in pores increased the number of pores available for the transmission of external CO₂ into the interior, promoting the occurrence of carbonation in the system and resulting in an increase in mass.

SF has a high specific surface area and may act as a nucleation site to promote the hydration of C₂S and the formation of C-S-H gel and Ca(OH)₂ in NS. The pozzolanic reaction caused by SF in NS promotes the generation of a large amount of C-S-H gel while consuming Ca(OH)₂. SF will further react with the Ca(OH)₂ generated by hydration through "secondary hydration (pozzolanic reaction)" to form C-S-H gel. In addition, SF has a significant promoting effect on the carbonation of NS system. These effects significantly influence the pore structure composition in the hardened NS slurry. SF can refine the pore size and increase the pore density, thereby promoting a significant increase in mechanical strength. Conclusions SF can significantly shorten the setting period of NHL paste, but it will cause a significant decrease in its fluidity. The compressive strength of NS mortar with SF addition is significantly increased, and the 28-day compressive strength of NS15 mortar reaches 10.92 MPa, which is 3.97 times higher than that of NHL mortar. SF shows a change pattern of first inhibiting and then promoting the drying shrinkage of NHL mortar. The hydration of C₂S to form C-S-H gel and Ca(OH)₂ is the basic hydration process in NHL. The combined effects of SF acting as a nucleation site to promote the hydration of C₂S, the pozzolanic reaction between SF and Ca(OH)₂ in NHL, and the secondary hydration of SF and Ca(OH)₂ formed by the C₂S hydration, and result in a significant increase in the C-S-H and a significant decrease in the content of Ca(OH)₂ in NS system. The content of CaCO₃ generated by carbonation in NS with SF addition increases significantly. Pore structure of NHL is mainly composed of capillary pores and macro pores, with a total porosity of 51.31% at 28 days. The proportion of gel pores and transition pores in NS significantly increases, and with the increase of SF dosage, the most probable pore diameter shifts towards smaller pores, and the average pore diameter also decreases significantly. The filling effect of SF and the generation of more C-S-H and CaCO₃ due to the hydration and carbonation of NHL can significantly refine the pore size and densify the pore structure.

While advances in fabricating tailored silica and PiSG geometries are notable, two critical challenges require immediate attention. The first limitation is the confinement of the IM/sintering technique to silica glass, as the production of multicomponent silicate glasses remains unreported. This bottleneck stems from a lack of commercially available amorphous nanoparticles for other glass compositions, underscoring the necessity for research into novel multicomponent nanopowders. The second challenge is the restricted spectral output of PiSG color converters, which currently only emit between 500-850 nm. Extending this range to 500-1500 nm for next-generation LEDs necessitates the incorporation of new NIR-emitting phosphors. Ideal candidates must exhibit high quantum efficiency and high thermal stability. Consequently, systematic research is essential to optimize these properties and realize injection-molded multicomponent glasses and ultra-broadband LEDs.

Enhancing conductivity is pivotal for optimizing LMFP electrochemical performance. Current strategies effectively improve electronic conductivity via carbon coating, doping, conductive additives, and nanostructuring, while ionic conductivity benefits from morphology design, ion doping, and ionically conductive surface coatings. However, single modification approaches remain insufficient to fundamentally resolve LMFP's low conductivity. Future research must focus on synergistic modification strategies, constructing integrated 3D electron/ion conduction networks within particles and electrodes. Additionally, deeper investigation into microstructure-property relationships is essential to guide material optimization. This will enable cost-effective ultra-fast charging solutions for new energy vehicles and grid storage, advancing high-safety, long-lifetime, high-rate lithium batteries for energy transition.

Despite significant advancements in mitigating the "shuttle effect" through polymer electrolyte innovations, lithium-sulfur batteries still face multifaceted challenges that demand interdisciplinary solutions. Fundamental understanding remains incomplete regarding "shuttle effect" mechanisms across diverse polymer matrices, necessitating systematic comparative studies to establish universal theoretical frameworks. While catalytic site integration and functionalized polymer designs have improved polysulfide (LiPS) conversion kinetics, atomic-level manipulation of active sites and precise microstructural control of polymeric networks require further optimization to achieve directional LiPS transformation. Notably, metal-organic frameworks (MOFs), despite their success in sulfur cathodes, remain underexplored in polymer electrolyte systems, where theoretical investigations combining density functional theory calculations and molecular dynamics simulations could elucidate critical interfacial interactions and lithium-ion transport mechanisms. Advanced characterization platforms integrating synchrotron X-ray spectroscopy and cryo-electron microscopy are urgently needed to complement conventional electrochemical techniques like cyclic voltammetry, as current methods cannot directly resolve LiPS dynamic evolution or atomic-scale ion transport phenomena. Concurrently, material optimization must balance enhanced ionic conductivity through molecular engineering against preserved LiPS adsorption/catalytic capabilities, demanding innovative multiscale designs that address hierarchical structure-property relationships and interfacial stability under operational conditions. These interconnected challenges highlight the imperative for coordinated efforts combining computational modeling, advanced characterization, and rational material design to overcome existing barriers in polymer electrolyte development.

Although researchers have made significant progress in the development of catalysts for direct seawater electrolysis, there are still many challenges to be overcome for their practical application. Whether for direct or indirect seawater electrolysis, developing electrocatalysts with high activity, high selectivity, and long-term stability at industrially relevant current densities is a prerequisite. However, even though various strategies have been adopted to design anode catalysts with high selectivity and durability, the corrosion effect and competitive reactions remain the main challenges for seawater electrolysis at high current densities. In the future, when designing catalysts, it is crucial to have an in-depth understanding of the degradation mechanisms caused by soluble ions and other impurities in seawater, which is essential for maximizing the activity of the catalyst/electrode, extending the lifespan of the electrolyzer, and reducing the operating cost. Secondly, the composition of real seawater is complex and varies globally, which has a significant impact on the efficiency and lifespan of seawater electrolyzers. Despite a great deal of effort, there is currently no breakthrough strategy that can completely avoid the influence of complex components on direct seawater electrolysis. It is urgent to study the specific impacts of ions and impurities on these membrane materials and their degradation mechanisms during the seawater electrolysis process. In addition, combining technologies such as photovoltaic/wind power generation, seawater electrolyzers, fuel cells, ammonia synthesis, and methanol synthesis is of great significance for solving the energy and freshwater supply problems in offshore and remote areas.

The annealing process for perovskite thin films helps to increase the nucleation rate during film formation, then enhances the grain density, and subsequently promotes the formation of larger and uniformly distributed grains, and ultimately results in high-quality perovskite films, thereby improving the photovoltaic performance of the devices. This article systematically reviews the influencing mechanisms of the annealing process, the types of annealing methods, the process parameters affecting annealing outcomes, and the latest advancements in annealing-free techniques for perovskite thin films. The aim is to provide theoretical foundations and technical references for the preparation of high-quality perovskite films and high-performance PSCs.

By optimizing the uniformity and coverage of perovskite films, the annealing process promotes grain growth and passivates interface defects, thereby enhancing the crystalline quality and optoelectronic properties of the films. While traditional thermal annealing improves film quality to some extent, it can also lead to issues such as pinholes and uneven grain size, which limit the development of PSCs. Consequently, a variety of novel annealing techniques have been developed, including electromagnetic wave (infrared, ultraviolet, laser, and microwave) annealing, ultrasonic annealing, pressure annealing, and solvent annealing. Moreover, precise control of annealing parameters—such as temperature, heating rate, duration, and ambient atmosphere—has been proven critical to optimizing annealing outcomes and directly influences the photovoltaic performance of the devices.

Despite significant progress in annealing techniques, their side effects cannot be overlooked. For instance, high-temperature annealing may trigger perovskite decomposition, some methods are complex and lack reproducibility, and the process incurs additional costs. As a result, annealing-free techniques are gaining attention, as they simplify the fabrication process of PSCs, reduce energy consumption, and lower costs. However, the crystalline quality of annealing-free films still lags behind that of annealed films, warranting further exploration.

Looking ahead, research on the annealing process for perovskite thin films is likely to develop in the following directions:

First, further advancement of in-situ characterization techniques to deeply reveal the microscopic mechanisms of crystal growth during annealing.

Second, leveraging the advantages of machine learning for high-throughput screening of annealing process data to guide the laboratory preparation and industrial application of high-efficiency PSCs.

Third, continued development of novel annealing and annealing-free techniques that balance efficiency and low energy consumption, ensuring high film quality while simplifying the fabrication process and reducing costs.

Currently, the industrialization of perovskite solar cells is becoming increasingly prominent, particularly in perovskite-silicon tandem solar cells. There is an urgent need to address the challenge of achieving uniform crystallization of large-area perovskite films compatible with industrial-grade silicon wafers, which will propel the industrialization of perovskite photovoltaics to a new stage.