Opto-Electronic Advances (光电进展)•2026•DOI: 10.29026/oea.2026.250263
The convergence of artificial intelligence (AI) and metaphotonics is creating a new paradigm for controlling light-matter interactions. The synergy of AI's ability to learn complex relationships in multidimensional data and provide ultra-fast inference with the capacity of metaphotonics to engineer optical properties not found in nature is unlocking a new era in computational design, real-time control, and fully automated optical systems. This review provides a comprehensive overview of state-of-the-art AI-driven approaches for metaphotonic systems. We focus on the solutions to real-world problems in accelerating metaphotonic simulations and inverse design, optical data characterization, and the development of fully integrated end-to-end AI-assisted metaphotonic systems. Finally, we provide our perspectives on the future research directions and emerging opportunities at the rapidly evolving intersection of metaphotonics and AI.
Journal of Advanced Ceramics•2026•DOI: 10.26599/JAC.2026.9221339
Practical deployment of Li4SiO4 as a high-temperature CO2 sorbent requires pelletization, which inevitably densifies the microstructure and imposes severe CO2 diffusion limitations. Conventional sacrificial pore-forming agents address this issue but remain single-purpose, serving solely as structural templates without conferring chemical benefits. Here, we demonstrate that spent coffee grounds (SCGs), an abundant food-industry waste, can serve as a single-source modifier that achieves three colocalized enhancements in Li4SiO4 pellets: hierarchical pore engineering, in situ K-doping, and oxygen vacancy generation. The thermal decomposition of SCG creates an interconnected hierarchical macroporous network that effectively reduces intraparticle CO2 diffusion resistance. Meanwhile, the mineral-rich SCG ash provides in situ potassium doping, generating a localized eutectic molten carbonate phase that accelerates liquid-phase ion transport. Crucially, the transient reducing atmosphere during biomass combustion introduces oxygen vacancies into the silicate lattice; density functional theory (DFT) calculations reveal that these vacancies serve as highly active CO2 adsorption sites with a strongly exothermic adsorption energy of −0.914 eV. Benefiting from this triple-synergistic enhancement, the SCG-modified sorbent (LSO-50) achieves a CO2 adsorption capacity of 0.275 g/g at 650 °C under 15 vol% CO2, representing a more than fourfold improvement over unmodified pellets. When further combined with Na2CO3 codoping to promote additional eutectic formation, the optimized sorbent (LSON-50) reaches 0.330 g/g, retains 0.284 g/g after 50 adsorption–desorption cycles, and exhibits robust mechanical stability (< 10% attrition loss). By colocating structural, chemical, and defect features within a single biomass-derived modifier, this work establishes a scalable waste-valorization route for high-performance, eco-friendly CO2 capture.
Journal of Semiconductors (半导体学报 - 中国科学院半导体研究所)•2026•DOI: 10.1088/1674-4926/25070023
Prolonged exposure to n-butanol, a hazardous volatile organic compound (VOC), necessitates sensitive detection at low concentrations for environmental and health monitoring. This study presents a novel Eu/Ce-codoped MOF-ZnO gas sensor for n-butanol detection under ultraviolet (UV) activation at ambient temperature. A series of Eu/Ce-ZnO nanomaterials were synthesized via a simple co-precipitation route by varying the mass ratios of Eu and Ce incorporated into pristine ZnO derived from MOF precursors. Gas testing results revealed that introducing an appropriate amount of Eu and Ce enlarged the specific surface area and enriched the oxygen vacancy content compared to pristine MOF-ZnO. Upon UV irradiation, the 0.03 wt% Eu 0.04 wt% Ce-ZnO sensor achieved a superior response of 611 for 100 ppm n-butanol at room temperature, 15.28 times higher than that of pristine MOF-ZnO (40). Furthermore, the sensor presented rapid response/recovery times (15 s/28 s) and excellent selectivity. The doped rare earth elements Eu and Ce simultaneously suppress the recombination of photogenerated electron-hole pairs, greatly improving response, stability, and selectivity. These findings demonstrate the potential of Eu/Ce-codoped ZnO nanoparticles for efficient, cost-effective n-butanol detection, offering a promising avenue for highly sensitive, UV-enhanced gas sensors for ambient temperature VOC monitoring.
Journal of Central South University•2026•DOI: 10.1007/s11771-026-6210-9
The accuracy of wheel-rail rolling contact force is of great significance for vehicle dynamics simulation. A wheel-rail rolling contact behavior model considering wheelset yaw is proposed. The NORM algorithm is adopted to solve the wheel-rail normal contact problem. The extended creep force model (ECF) is used for the tangential contact problem, which considers different interfacial conditions, temperature in the contact area, and the elastoplastic behavior of the third body. A fatigue life prediction framework based on the critical plane method is introduced to evaluate the contact fatigue damage under the coupled influence of yaw angle and interfacial conditions. The effects of wheel yaw angle on the contact pressure and wheel-rail rolling contact fatigue life under dry and wet conditions are investigated. The results show that under both dry and wet conditions, increasing yaw angle leads to an increase in creepage, expansion of the sliding area, enhancement of creep force, and a simultaneous increase in the contact area temperature, thereby causing an increase in the fatigue parameter (FP). The wheel-rail rolling contact life with yaw angle is shortened compared to that without yaw, and the life decay rate under wet condition is slower than that under dry condition.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01845-7
The development of highly efficient and durable bifunctional catalysts with minimal precious metal usage is critical for advancing proton exchange membrane water electrolysis (PEMWE). We present an iridium–platinum nanoalloy (IrPt) supported on lanthanum and nickel co-doped cobalt oxide, featuring a core–shell architecture with an amorphous IrPtOx shell and an IrPt core. This catalyst exhibits exceptional bifunctional activity for oxygen and hydrogen evolution reactions in acidic media, achieving 2 A cm−2 at 1.72 V in a PEMWE device with ultralow loadings of 0.075 mgIr cm−2 and 0.075 mgPt cm−2 at anode and cathode, respectively. It demonstrates outstanding durability, sustaining water splitting for over 646 h with a degradation rate of only 5 μV h−1, outperforming state-of-the-art Ir-based catalysts. In situ X-ray absorption spectroscopy and density functional theory simulations reveal that the optimized charge redistribution between Ir and Pt, along with the IrPt core–IrPtOx shell structure, enhances performance. The Ir–O–Pt active sites enable a bi-nuclear mechanism for oxygen evolution reaction and a Volmer–Tafel mechanism for hydrogen evolution reaction, reducing kinetic barriers. Hierarchical porosity, abundant oxygen vacancies, and a high electrochemical surface area further improve electron and mass transfer. This work offers a cost-effective solution for green hydrogen production and advances the design of high-performance bifunctional catalysts for PEMWE.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01832-y
Silicon (Si) is a promising anode material for rechargeable batteries due to its high theoretical capacity and abundance, but its practical application is hindered by the continuous growth of porous solid-electrolyte interphase (SEI), leading to capacity fade. Herein, a LiF-Pie structured SEI is proposed, with LiF nanodomains encapsulated in the inner layer of the organic cross-linking silane matrix. A series of advanced techniques such as cryogenic electron microscopy, time-of-flight secondary ion mass spectrometry, and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry have provided detailed insights into the formation mechanism, nanostructure, and chemical composition of the interface. With such SEI, the capacity retention of LiCoO2||Si is significantly improved from 49.6% to 88.9% after 300 cycles at 100 mA g−1. These findings provide a desirable interfacial design principle with enhanced (electro) chemical and mechanical stability, which are crucial for sustaining Si anode functionality, thereby significantly advancing the reliability and practical application of Si-based anodes.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01812-2
In the era of global climate change, personal thermoregulation has become critical to addressing the growing demands for thermoadaptability, comfort, health, and work efficiency in dynamic environments. Here, we introduce an innovative three-dimensional (3D) self-folding knitted fabric that achieves dual thermal regulation modes through architectural reconfiguration. In the warming mode, the fabric maintains its natural 3D structure, trapping still air with extremely low thermal conductivity to provide high thermal resistance (0.06 m2 K W−1), effectively minimizing heat loss. In the cooling mode, the fabric transitions to a 2D flat state via stretching, with titanium dioxide (TiO2) and polydimethylsiloxane (PDMS) coatings that enhance solar reflectivity (89.5%) and infrared emissivity (93.5%), achieving a cooling effect of 4.3 °C under sunlight. The fabric demonstrates exceptional durability and washability, enduring over 1000 folding cycles, and is manufactured using scalable and cost-effective knitting techniques. Beyond thermoregulation, it exhibits excellent breathability, sweat management, and flexibility, ensuring wear comfort and tactile feel under diverse conditions. This study presents an innovative solution for next-generation adaptive textiles, addressing the limitations of static thermal fabrics and advancing personal thermal management with wide applications for wearable technology, extreme environments, and sustainable fashion.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01730-3
Amplification-free, highly sensitive, and specific nucleic acid detection is crucial for health monitoring and diagnosis. The type III CRISPR-Cas10 system, which provides viral immunity through CRISPR-associated protein effectors, enables a new amplification-free nucleic acid diagnostic tool. In this study, we develop a CRISPR-graphene field-effect transistors (GFETs) biosensor by combining the type III CRISPR-Cas10 system with GFETs for direct nucleic acid detection. This biosensor exploits the target RNA-activated continuous ssDNA cleavage activity of the dCsm3 CRISPR-Cas10 effector and the high charge density of a hairpin DNA reporter on the GFET channel to achieve label-free, amplification-free, highly sensitive, and specific RNA detection. The CRISPR-GFET biosensor exhibits excellent performance in detecting medium-length RNAs and miRNAs, with detection limits at the aM level and a broad linear range of 10−15 to 10−11 M for RNAs and 10−15 to 10−9 M for miRNAs. It shows high sensitivity in throat swabs and serum samples, distinguishing between healthy individuals (N=5) and breast cancer patients (N=6) without the need for extraction, purification, or amplification. This platform mitigates risks associated with nucleic acid amplification and cross-contamination, making it a versatile and scalable diagnostic tool for molecular diagnostics in human health.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01732-1
Terahertz (THz) devices, owing to their distinctive optical properties, have achieved myriad applications in diverse domains including wireless communication, medical imaging therapy, hazardous substance detection, and environmental governance. Concurrently, to mitigate the environmental impact of electronic waste generated by traditional materials, sustainable materials-based THz functional devices are being explored for further research by taking advantages of their eco-friendliness, cost-effective, enhanced safety, robust biodegradability and biocompatibility. This review focuses on the origins and distinctive biological structures of sustainable materials as well as succinctly elucidates the latest applications in THz functional device fabrication, including wireless communication devices, macromolecule detection sensors, environment monitoring sensors, and biomedical therapeutic devices. We further highlight recent applications of sustainable materials-based THz functional devices in hazardous substance detection, protein-based macromolecule detection, and environmental monitoring. Besides, this review explores the developmental prospects of integrating sustainable materials with THz functional devices, presenting their potential applications in the future.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01688-2
Artificial carbon fixation is a promising pathway for achieving the carbon cycle and environment remediation. However, the sluggish kinetics of oxygen evolution reaction (OER) and poor selectivity of CO2 reduction seriously limited the overall conversion efficiencies of solar energy to chemical fuels. Herein, we demonstrated a facile and feasible strategy to rationally regulate the coordination environment and electronic structure of surface-active sites on both photoanode and cathode. More specifically, the defect engineering has been employed to reduce the coordination number of ultrathin FeNi catalysts decorated on BiVO4 photoanodes, resulting in one of the highest OER activities of 6.51 mA cm−2 (1.23 VRHE, AM 1.5G). Additionally, single-atom cobalt (II) phthalocyanine anchoring on the N-rich carbon substrates to increase Co–N coordination number remarkably promotes CO2 adsorption and activation for high selective CO production. Their integration achieved a record activity of 109.4 μmol cm−2 h−1 for CO production with a faradaic efficiency of >90%, and an outstanding solar conversion efficiency of 5.41% has been achieved by further integrating a photovoltaic utilizing the sunlight (>500 nm).
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01682-8
Renewable 2,5-furandicarboxylic acid-based polyesters are one of the most promising materials for achieving plastic replacement in the age of energy and environmental crisis. However, their properties still cannot compete with those of petrochemical-based plastics, owing to insufficient molecular and/or microstructure designs. Herein, we utilize the Ti3C2Tx-based MXene nanosheets for decorating carbon nanotube (CNT) and obtaining the structurally stable and highly dispersed dendritic heterostructured MXene@CNT, that can act as multi-roles, i.e., polycondensation catalyst, crystal nucleator, and interface enhancer of polyester. The bio-based MXene@CNT/polybutylene furandicarboxylate (PBF) (denoted as MCP) nanocomposites are synthesized by the strategy of “in situ catalytic polymerization and hot-pressing”. Benefiting from the multi-scale interactions (i.e., covalent bonds, hydrogen bonds, and physical interlocks) in hybrid structure, the MCP presents exceptional mechanical strength (≈101 MPa), stiffness (≈3.1 GPa), toughness (≈130 MJ m−3), and barrier properties (e.g., O2 0.0187 barrer, CO2 0.0264 barrer, and H2O 1.57 × 10−14 g cm cm−2 s Pa) that are higher than most reported bio-based materials and engineering plastics. Moreover, it also displays satisfactory multifunctionality with high reprocessability (90% strength retention after 5 recycling), UV resistance (blocking 85% UVA rays), and solvent-resistant properties. As a state-of-art high-performance and multifunctional material, the novel bio-based MCP nanocomposite offers a more sustainable alternative to petrochemical-based plastics in packaging and engineering material fields. More importantly, our catalysis-interfacial strengthening integration strategy opens a door for designing and constructing high-performance bio-based polyester materials in future.
New Carbon Materials (新型炭材料)•2025•DOI: 10.1016/S1872-5805(NCM2024-39-03-09)
Metal chloride-intercalated graphite with excellent conductivity and a large interlayer spacing is highly desired for use in sodium ion batteries. However, halogen vapor is usually indispensable in initiating the intercalation process, which makes equipment design and experiments challenging. In this work, SO2Cl2 was used as a chlorine generator to intensify the intercalation of BiCl3 into graphite (BiCl3-GICs), which avoided the potential risks, such as Cl2 leakage, in traditional methods. The operational efficiency in the experiment was also improved. After the reaction of SO2Cl2, BiCl3, and graphite at 200 °C for 20 h, the synthesized BiCl3-GICs had a large interlayer spacing (1.26 nm) and a high amount of BiCl3 intercalation (42%), which gave SIBs a high specific capacity of 213 mAh g−1 at 1 A g−1 and an excellent rate performance (170 mAh g−1 at 5 A g−1). In-situ Raman spectra revealed that the electronic interaction between graphite and intercalated BiCl3 is weakened during the first discharge, which is favorable for sodium storage. This work broadly enables the increased intercalation of other metal chloride-intercalated graphites, offering possibilities for developing advanced energy storage devices.
Journal of Semiconductors (半导体学报 - 中国科学院半导体研究所)•2025•DOI: 10.1088/1674-4926/25040027
A monolithic integrated full-wave bridge rectifier consisted of horizontal Schottky-barrier diodes (SBD) is prepared based on 100 nm ultra-thin β-Ga2O3 and demonstrated the solar-blind UV (SUV) light-modulated characteristics. Under SUV light illumination, the rectifier has the excellent full-wave rectification characteristics for the AC input signals of 5, 12, and 24 V with different frequencies. Further, experimental results confirmed the feasibility of continuously tuning the rectified output through SUV light-encoding. This work provides valuable insights for the development of optically programmable Ga2O3 AC-DC converters.
Int. Journal of Mining Science and Technology (采矿与安全工程)•2025•DOI: 10.1016/j.ijmst.2025.11.006
Investigating the damage evolution of surrounding rock under thermal shock cycles is crucial for ensuring the stability of engineering rock masses. This study performed Brazilian splitting tests on granite specimens under varying temperature and cycle conditions, employing acoustic emission monitoring, digital image correlation, and three-dimensional scanning technology. A systematic analysis was conducted on the patterns of damage evolution, failure precursor, and response mechanisms under combined thermal and cyclic loading. Experimental results show that both P-wave velocity and tensile strength degrade significantly with increasing temperature and cycle count, with temperature having a more pronounced effect than cycle count. Notably, damage evolution exhibits a dual-threshold behavior in which degradation accelerates markedly above 400 °C and stabilizes after 5 thermal cycles. Fracture surfaces evolve from initially planar to rugged morphologies, with peak-valley height differences at 600 °C being approximately three times greater than those at 200 °C. Furthermore, based on acoustic emission energy entropy analysis, we introduce a novel failure precursor indicator where the sustained increase and critical surge in average entropy serve as reliable early-warning signals for impending rock failure. These findings establish a solid theoretical basis and practical methodology for damage assessment and instability early-warning systems in high-temperature rock engineering.
China Foundry•2025•DOI: 10.1007/s41230-025-3171-9
The grain size of TiAl alloy castings prepared by traditional casting process is coarse, thus showing poor mechanical properties. In this study, a new type of high performance Ti-46Al alloy tube prepared by vacuum centrifugal casting technology was introduced. This research comprehensively examined the influence of pouring time on the microstructure and mechanical performance of the castings, employing both experimental approaches and ProCast simulation methodologies. The findings indicate that prolonging the pouring time facilitates a microstructural evolution from coarse columnar grains to refined equiaxed grains. Under the condition of pouring temperature of 1,600 °C, rotation speed of 800 r·min-1 and pouring time of 6 s, the tensile strength of Ti-46Al alloy at room temperature reaches 650 MPa, and the tensile strength at 800 °C reaches 705 MPa, which is significantly higher than that of traditional as-cast Ti-Al alloy.
Int. Journal of Minerals, Metallurgy and Materials (矿物冶金与材料学报)•2025•DOI: 10.1007/s12613-024-3070-x
Al2O3 and MgO serve as the primary gangue components in sintered ores, and they are critical for the formation of CaO–Fe2O3–xAl2O3 (wt%, C–F–xA) and CaO–Fe2O3–xMgO (wt%, C–F–xM) systems, respectively. In this study, a nonisothermal crystallization thermodynamics behavior of C–F–xA and C–F–xM systems was examined using differential scanning calorimetry, and a phase identification and microstructure analysis for C–F–xA and C–F–xM systems were carried out by X-ray diffraction and scanning electron microscopy. Results showed that in C–F–2A and C–F–2M systems, the increased cooling rates promoted the precipitation of CaFe2O4 (CF) but inhibited the formation of Ca2Fe2O5 (C2F). In addition, C–F–2A system exhibited a lower theoretical initial crystallization temperature (1566 K) compared to the C–F system (1578 K). This temperature further decreases to 1554 K and 1528 K in the C–F–4A and C–F–8A systems, respectively. However, in C–F–xM system, the increased MgO content raised the crystallization temperature. This is because that the enhanced precipitation of MF (a spinel phase mainly comprised Fe3O4 and MgFe2O4) and C2F phases suppressed the CF precipitation reaction. In kinetic calculations, the Ozawa method revealed the apparent activation energies of the C–F–2A and C–F–2M systems. Malek’s method revealed that the crystallization process in C–F–2A system initially followed a logarithmic law ( or ), later transitioning to a reaction order law ((1−α)−1 or (1−α)−1/2, n = 2/3) or the function of the exponential law. In C–F–2M system, it consistently followed the sequence ƒ(α) = (1−α)2 (α is the crystallization conversion rate; n is the Avrami constant; ƒ(α) is the differential equations for the model function of C2F and CF crystallization processes).
Chinese Journal of Mechanical Engineering•2025•DOI: 10.1186/s10033-025-01347-y
The average stiffness performance indices throughout the workspace are commonly used as global stiffness performance indices to evaluate the overall stiffness performance of parallel mechanisms, which involves an analysis of the stiffness performance of numerous discrete points in the workspace. This necessitates time-consuming and inefficient calculation, which is particularly pronounced in the optimization design stage of the mechanism, where the variations in the global stiffness performance indices versus various dimensional and structural parameters need to be analyzed. This paper presents a semi-analytical approach for stiffness modeling of the novel (R(RPS&RP))&2-UPS parallel mechanism (referred to as the Trifree mechanism) and proposes “local” stiffness performance indices as alternatives to global indices. Drawing on the screw theory, the Cartesian stiffness matrix of the Trifree mechanism is formulated explicitly by considering the compliances of all elastic elements and the over-constraint characteristics inherent in the mechanism. Based on the spherical motion pattern of the Trifree mechanism, four special reference configurations are extracted within the workspace. This yields “local” stiffness performance indices capable of accurately evaluating the overall stiffness performance of the mechanism and effectively improving the computational efficiency. The variations in global and “local” stiffness performance indices versus key design parameters are investigated. Furthermore, the proposed indices are applied to the Tricept and Trimule mechanisms. The results demonstrate that the proposed indices exhibit excellent computational accuracy and efficiency in evaluating the overall stiffness performance of these spherical parallel mechanisms. Moreover, the stiffness performance of the novel parallel mechanism investigated in this study closely resembles that of the well-known Tricept and Trimule mechanisms. This research proposes a semi-analytic stiffness model of the Trifree mechanism and “local” stiffness performance indices to evaluate the overall stiffness performance, thereby substantially improving the computational efficiency without sacrificing accuracy.
Chinese Journal of Mechanical Engineering•2025•DOI: 10.1186/s10033-025-01263-1
The research on rolling bearing early fault detection is mainly focused on degradation index extraction and adaptive setting of alarm threshold. The mainstream methods are to extract degradation indicators based on adaptive features and set adaptive alarm thresholds based on the Shewhart control chart. However, the adaptive feature extraction method does not consider the correlation between features, and the Shewhart control chart is not sensitive to small fluctuations caused by early faults. In this study, a rolling bearing early fault detection method based on a feature clustering fusion degradation index is proposed. The multidomain statistical features are extracted to form the initial feature set, and the improved hierarchical clustering algorithm is combined with the feature evaluation index to select features to form a preferred feature subset, to ensure the richness of index information and reduce redundancy. After the construction of the degradation index, to suppress the interference caused by nonstationary and abnormal shocks in early fault detection, the accurate evaluation method and anomaly determination strategy of control chart parameters are studied, and an improved exponential weighted move average control chart is designed to monitor the degradation index. The effectiveness and superiority of the proposed method are verified by public data sets. This research provides a rolling bearing early fault detection method, which can provide comprehensive degradation indicators, eliminate interference caused by random anomalies and running in periods, and achieve an accurate detection of early bearing failures.
Journal of Central South University•2025•DOI: 10.1007/s11771-025-6077-1
With the continuous expansion of deep underground engineering and the growing demand for safety monitoring, microseismic monitoring has become a core method for early warning of rock mass fracture and engineering stability assessment. To address problems in existing methods, such as low data processing efficiency and poor phase recognition accuracy under low signal-to-noise ratio (SNR) conditions in complex geological environments, this study proposes an intelligent phase picking model based on ResUNet. The model integrates the residual learning mechanism of ResNet with the multi-scale feature extraction capability of UNet, effectively mitigating the vanishing gradient problem in deep networks. It also achieves cross-layer fusion of shallow detail features and deep semantic features through skip connections in the encoder-decoder structure. Compared with traditional short-time average/long-time average (STA/LTA) algorithms and advanced neural network models such as PhaseNet and EQTransformer, ResUNet shows superior performance in picking P- and S-wave phases. The model was trained on 400000 labeled microseismic signals from the Stanford earthquake dataset (STEAD) and was successfully applied to the Shizhuyuan polymetallic mine in Hunan Province, China. The results demonstrate that ResUNet achieves high picking accuracy and robustness in complex geological conditions, offering reliable technical support for early warning of disasters such as rockburst in deep underground engineering.
Int. Journal of Minerals, Metallurgy and Materials (矿物冶金与材料学报)•2025•DOI: 10.1007/s12613-025-3225-4
The effects of direct aging (DA) on the microstructure and mechanical properties of TiB2/AlSi7Mg alloys fabricated via laser powder bed fusion (LPBF) were systematically investigated. DA significantly improves strength while maintaining satisfactory ductility. Optimal performance is obtained through under-aging (UA) at 150°C for 4 h, resulting in a yield strength of 361 MPa, tensile strength of 503 MPa, and elongation of 9.1% in the horizontal direction. DA does not substantially alter the grain size or cellular structure but promotes the formation of nanoprecipitates within the α-Al matrix. Specifically, UA induces dot-like and needle-like Si precipitates, whereas over-aging (OA) additionally generates short rod-like β'-Mg1.8Si phases. The strengthening mechanism is attributed to the Hall–Petch effect associated with grain and cell boundaries, and the Orowan mechanism induced by nanoprecipitates. Work-hardening behavior is governed by interactions between dislocations and nanoprecipitates. The OA sample exhibits rapid saturation of work hardening due to a high initial hardening rate and dynamic recovery of dislocations, resulting in limited uniform elongation. In contrast, the UA sample demonstrates a more balanced work hardening response. These findings provide theoretical and experimental validation of DA as an effective post-processing approach aimed at enhancing the performance of LPBF Al–Si–Mg alloys in engineering applications.
Int. Journal of Minerals, Metallurgy and Materials (矿物冶金与材料学报)•2025•DOI: 10.1007/s12613-025-3201-z
The performance of the fuel electrode in a solid oxide electrolysis cell (SOEC) is crucial to facilitating fuel gas electrolysis and is the key determinant of overall electrolysis efficiency. Nevertheless, the commercialization of integrated CO2–H2O electrolysis in SOEC remains constrained by suboptimal catalytic efficiency and long-term stability limitations inherent to conventional fuel electrode architectures. A novel high-entropy Sr2FeTi0.2Cr0.2Mn0.2Mo0.2Co0.2O6−δ (SFTCMMC) was proposed as a prospective electrode material of co-electrolysis in this work. The physicochemical properties and electrochemical performance in the co-electrolysis reaction were investigated. Full cell is capable of electrolyzing H2O and CO2 effectively with an applied voltage. The effects of temperature, H2O and CO2 concentrations, and applied voltage on the electrochemical performance of Sc0.18Zr0.82O2−δ (SSZ)-electrolyte supported SOEC were investigated by varying the operating conditions. The SOEC obtains a favorable electrolysis current density of 1.47 A·cm−2 under co-electrolysis condition at 850°C with 1.5 V. Furthermore, the cell maintains stable performance for 150 h at 1.3 V, and throughout this period, no carbon deposition is detected. The promising findings suggest that the high-entropy SFTCMMC perovskite is a viable fuel electrode candidate for efficient H2O/CO2 co-electrolysis.
Int. Journal of Minerals, Metallurgy and Materials (矿物冶金与材料学报)•2025•DOI: 10.1007/s12613-025-3109-7
Utilizing coarse aggregates containing mining waste rock for backfilling addresses the strength requirements and reduces the expenses associated with binder and solid waste treatment. However, this type of material is prone to aggregate segregation, which can lead to uneven deformation and damage to the backfill. We employed an image-segmentation method that incorporated machine learning to analyze the distribution information of the aggregates on the splitting surface of the test blocks. The results revealed a nonlinear relationship between aggregate segregation and variations in solid concentration (SC) and cement/aggregate ratio (C/A). The SC of 81wt%–82wt% and C/A of 10.00wt%–12.50wt% reflect surges in fluid dynamics, friction effects, and shifts in their dominance. A uniaxial compression experiment, supplemented with additional strain gauges and digital image correlation technology, enabled us to analyze the mechanical properties and failure mechanism under the influence of aggregate segregation. It was found that the uniaxial compressive strength, ranging from 1.75 MPa to 12.65 MPa, is linearly related to both the SC and C/A, and exhibits no significant relationship with the degree of segregation in numerical terms. However, the degree of segregation affects the development trend of the elastic modulus to a certain extent, and a standard deviation of the aggregate area ratio of less than 1.63 clearly indicates a higher elastic modulus. In the pouring direction, the top area of the test block tended to form a macroscopic fracture surface earlier. By contrast, the compressibility of the bottom area was greater than that of the top area. The intensification of aggregate segregation widened the differences in the deformation and failure characteristics between the different areas. For samples with different uniformities, significant differences in local deformation ranging from 515.00 με to 1693.70 με were observed during the stable deformation stage. The extreme unevenness of the aggregate leads to rapid crack penetration in the sample, causing macroscopic tensile failure and resulting in premature structural failure.
Int. Journal of Minerals, Metallurgy and Materials (矿物冶金与材料学报)•2025•DOI: 10.1007/s12613-025-3110-1
Real-time identification of rock strength and cuttability based on monitoring while cutting during excavation is essential for key procedures such as the precise adjustment of excavation parameters and the in-situ modification of hard rocks. This study proposes an intelligent approach for predicting rock strength and cuttability. A database comprising 132 data sets is established, containing cutting parameters (such as cutting depth and pick angle), cutting responses (such as specific energy and instantaneous cutting rate), and rock mechanical parameters collected from conical pick-cutting experiments. These parameters serve as input features for predicting the uniaxial compressive strength and tensile strength of rocks using regression fitting and machine learning methodologies. In addition, rock cuttability is classified using a combination of the analytic hierarchy process and fuzzy comprehensive evaluation method, and subsequently identified through machine learning approaches. Various models are compared to determine the optimal predictive and classification models. The results indicate that the optimal model for uniaxial compressive strength and tensile strength prediction is the genetic algorithm-optimized backpropagation neural network model, and the optimal model for rock cuttability classification is the radial basis neural network model.
Int. Journal of Minerals, Metallurgy and Materials (矿物冶金与材料学报)•2025•DOI: 10.1007/s12613-024-2984-7
To investigate the mechanisms of how nanobubbles enhance the flotation separation performance of galena from pyrite, the effects of nanobubbles on the surface properties of galena and pyrite and the interactions between mineral particles and air bubbles were examined in this study. Various analytical techniques, including focused beam reflectance measurement (FBRM), three-phase contact line (TPCL) analysis, atomic force microscopy (AFM), and contact angle measurement, were employed. It has been demonstrated that nanobubbles significantly enhanced the flotation recovery of galena and its flotation selectivity from pyrite, as compared to the conventional flotation process. The preferential formation of nanobubbles on the galena surface, which is more hydrophobic than pyrite surface, further increased the surface hydrophobicity and agglomeration of galena particles. The introduction of nanobubbles into the flotation system also increased in the maximum TPCL length and detachment length between the galena surface and bubbles, contributing to the enhanced flotation efficiency.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-024-01536-9
The incidence of large bone defects caused by traumatic injury is increasing worldwide, and the tissue regeneration process requires a long recovery time due to limited self-healing capability. Endogenous bioelectrical phenomena have been well recognized as critical biophysical factors in bone remodeling and regeneration. Inspired by bioelectricity, electrical stimulation has been widely considered an external intervention to induce the osteogenic lineage of cells and enhance the synthesis of the extracellular matrix, thereby accelerating bone regeneration. With ongoing advances in biomaterials and energy-harvesting techniques, electroactive biomaterials and self-powered systems have been considered biomimetic approaches to ensure functional recovery by recapitulating the natural electrophysiological microenvironment of healthy bone tissue. In this review, we first introduce the role of bioelectricity and the endogenous electric field in bone tissue and summarize different techniques to electrically stimulate cells and tissue. Next, we highlight the latest progress in exploring electroactive hybrid biomaterials as well as self-powered systems such as triboelectric and piezoelectric-based nanogenerators and photovoltaic cell-based devices and their implementation in bone tissue engineering. Finally, we emphasize the significance of simulating the target tissue’s electrophysiological microenvironment and propose the opportunities and challenges faced by electroactive hybrid biomaterials and self-powered bioelectronics for bone repair strategies.
Int. Journal of Mining Science and Technology (采矿与安全工程)•2024•DOI: 10.1016/j.ijmst.2024.12.010
The deformation energy (Wd) of soil-like tectonic coal is crucial for investigating the mechanism of coal and gas outbursts. Tectonic coal has a significant nonlinear constitutive relationship, which makes traditional elastic-based models for computing Wd unsuitable. Inspired by critical state soil mechanics, this study theoretically established a new calculation model of Wd suitable for the coal with nonlinear deformation characteristics. In the new model, the relationship between energy and stress no longer follows the square law (observed in traditional linear elastic models) but exhibits a power function, with the theoretical value of the power exponent ranging between 1 and 2. Hydrostatic cyclic loading and unloading experiments were conducted on four groups of tectonic coal samples and one group of intact coal samples. The results indicated that the relationship between Wd and stress for both intact and tectonic coal follows a power law. The exponents for intact and tectonic coal are close to 2 and 1, respectively. The stress-strain curve of intact coal exhibits small deformation and linear characteristics, whereas the stress-strain curves of tectonic coal show large deformation and nonlinear characteristics. The study specifically investigates the role of coal viscosity in the cyclic loading/unloading process. The downward bending in the unloading curves can be attributed to the time-dependent characteristics of coal, particularly its viscoelastic behavior. Based on experimental statistics, the calculation model of Wd was further simplified. The simplified model involves only one unknown parameter, which is the power exponent between Wd and stress. The measured Wd of the coal samples increases with the number of load cycles. This phenomenon is attributed to coal’s viscoelastic deformation. Within the same stress, the Wd of tectonic coal is an order of magnitude greater than that of intact coal. The calculation model of Wd proposed in this paper provides a new tool for studying the energy principle of coal and gas outbursts.