Arsenic pollution in water poses a significant environmental challenge due to its high toxicity and non-degradability. In this study, FeMn-layered double hydroxide (FeMn-LDH) was synthesized using hydrothermal and coprecipitation methods with different precursors for electrochemical arsenic remediation. The crystallinity of FeMn-LDH was enhanced with nitrate precursor compared to chloride precursor. The corresponding calcined layered double oxide obtained through the coprecipitation method (FMO-NO₃-Co) exhibits a significantly increased specific surface area and an optimal average pore size, facilitating efficient ion transport, and enhanced oxidation state of Mn, increasing arsenic removal efficiency. Electrochemical tests indicate that FMH-NO₃-Co exhibits relatively high specific capacitance and excellent electrochemical performance. Notably, the FMO-NO₃-Co achieves an electrosorption capacity of 55.5 mg g^-1 with 56.6 % of As(Ⅲ) being electrochemically oxidized, demonstrating superior electrocatalytic activity for the oxidation of As(Ⅲ) and high-performance electrosorption of As(V). The arsenic removal mechanism was comprehensively analyzed, revealing that Mn²⁺/Mn³⁺ redox cycling played a key role in As(Ⅲ) oxidation, while Fe-based coordination sites contributed to As(V) adsorption. Furthermore, the enhanced porosity and conductivity of the calcined LDH materials significantly improved charge transfer efficiency, thereby accelerating the arsenic removal process. Overall, this study provides valuable insights into the potential application of FeMn-LDH in electrochemical arsenic remediation.

tensile twins were introduced by pre-compressing the rolled AZ31 Mg alloy sheet along the transverse direction (TD) with a strain of 3 %, aiming to investigate the effect of pre-existing twins on its bending deformation behavior. For the AZ31 Mg alloy, the pre-existing tensile twins significantly improved the mechanical properties, the tension-compression yield asymmetry coefficient (0.57 vs. 0.35), and the bending property (bend angle: 97° vs. 65°). The pre-existing twins led to the deflection of the c-axis of the grains, thus modifying the strong (0001) basal texture, which improved the tension-compression yield asymmetry, making the strain distribution during the bending process in each region of the specimen more uniform. The basal slip caused by grain deflection on the rolling direction (RD)-normal direction (ND) plane increased the thickness-direction strain of the specimen during the bending deformation process. Moreover, the introduction of a large number of twin lamellae effectively subdivided and refined the grains, enhancing the plastic deformation ability of the specimen. In summary, these factors led to a significant improvement in the bending formability of the AZ31 Mg alloy.

CdS thin films were fabricated by annealing precursors which were deposited using the method of Sputtering, Evaporation and Sputtering (SES). Effect of sputtering time and RF power on the structural, compositional, surface morphology and optical properties of CdS thin films was investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersion spectrometer (EDS), UV-Vis spectrophotometer and photoluminescence (PL). The results reveal that the properties and growth of the obtained CdS films are greatly influenced by the second sputtering time rather than the first sputtering time. The deposited precursors are substrate/Cd/CdS, and transformed to CdS after annealing. The CdS films are hexagonal structure with a preferred orientation along (002) plane. Besides, the dense CdS films without cracks or pinholes have S/Cd atomic ratios of 0.87-0.99. Additionally, the grain size, morphology and composition of CdS films change with increasing RF power from 80 W to 150 W. All CdS films have a high average transmittance and band gaps of 2.25-2.43 eV. The PL emission peaks at 530 nm for CdS thin films are possibly caused by the band edge emission while the PL emission peaks at 680 nm arise from sulfur vacancies.

Data-centric materials informatics has become a transformative paradigm for accelerating the discovery and design of superalloys, particularly by enabling efficient prediction of properties that are experimentally inaccessible or computationally intractable due to constraints in cost, time, or complexity. By harnessing the ability of machine learning (ML) to model complex, nonlinear, and high-dimensional relationships, this approach provides a compelling alternative to traditional trial-and-error and simulation-based strategies. This review presents a comprehensive and critical assessment of recent advances in ML for superalloys. We first delineate the essential workflow for ML-enabled superalloy design, encompassing foundational data resources, quantitative assessments of data quality, feature descriptors and feature-selection strategies, representative algorithms tailored to small and heterogeneous datasets, rigorous model-evaluation protocols, and model interpretation through explainable ML and symbolic regression. We then summarize state-of-the-art ML applications targeting specific high-temperature performance metrics, particularly γ' phase stability, creep behavior, fatigue life, and oxidation resistance, and highlight how approaches such as multi-fidelity learning, data augmentation, transfer learning, and optimization algorithms facilitate efficient exploration of vast composition-processing design spaces. Finally, we discuss persisting challenges and emerging opportunities, including data scarcity and reliability, model confidence and uncertainty quantification, cross-system generalizability across Co-, Ni-, and multi-principal superalloys, high-dimensional multi-objective optimization, and the integration of physics-informed models and large language models into materials-informatics workflows. By synthesizing these developments, this review outlines a strategic roadmap for harnessing ML to accelerate the discovery, performance optimization, and intelligent design of next-generation superalloys.

The present study investigates the performance and mechanism of nitrogen-doped carbon-based catalysts in selective catalytic reduction (SCR) reactions for removing nitrogen oxides (NO_x) through a combination of experiments and density functional theory (DFT) calculations. A series of catalysts with a gradient distribution of nitrogen content were prepared, and the types, contents, and structural characteristics of their nitrogen-containing functional groups were characterised. The experimental findings demonstrated that with an increase in nitrogen content, there was an initial rise and subsequent decrease in NO conversion among the catalysts. The AC-N-3 catalyst exhibited the highest NO conversion, with an observed value of 83.0 %. DFT calculations revealed that nitrogen doping enhanced the adsorption capacity of the catalysts for NO and O₂ through the introduction of functional groups. The active centre is located at the nitrogen functional group and its adjacent carbon atom. The centre of the molecule is responsible for driving the charge migration process, which in turn causes a stretching of the bond length of the reactants. This effect leads to the efficient pre-activation of the reactants, thereby significantly enhancing their catalytic activity. Through the analysis of the NH₃-SCR reaction pathway, the fundamental steps of the reaction were presented in a comprehensible manner.

This study investigates a novel phenomenon of non-Hermitian phonon quantization in Eu³⁺: BiPO₄ crystals controlled by different phases. The hexagonal (H) -phase (0.5:1) with low symmetry has strongest destructive gamma phonon quantization as compare to high symmetry phases H-Monoclinic (M) phases (12:1, 1:1) in fluorescence (FL) region, while strong constructive dominant dressing quantization exhibits due to higher phonon density of states in spontaneous four wave mixing (SFWM) region. Strong Spectral Autler-Townes (SAT) is observed in (6:1) phase at small angle and time gate position (GP = 500 ns), while, strong Temporal Autler-Townes (TAT) is studied at GP = 1ns. Also, (6:1) exhibits angle destructive quantization in FL region. Comparison between the H-M (12:1) phase and H = M (6:1) phases reveals that the H-M phase exhibits stronger destructive gamma quantization in FL region due to larger gamma phonon in (12:1) phase. Moreover, H-phase (0.5:1) exhibits large number of phonon density and shows strong constructive quantization as compare to M-phase (7:1) in SWFM region. Additionally, two destructive dressing quantization are observed in fluorescence region where gamma quantization is affected by additional laser. This work establishes a deterministic relation between non-Hermitian phonon quantization and different phases of Eu³⁺: BiPO₄, enabling applications in quantum memory and tunable bandpass filters. The Band pass filter control through phonon quantization with different phases of Eu³⁺: BiPO₄.

Photocatalytic nitrogen reduction to produce ammonia under ambient conditions is a promising green route. In this study, we demonstrate that one-dimensional (1D) TiO₂ nanobelts, prepared via a facile hydrothermal method, can convert gaseous dinitrogen to ammonia in pure water under light irradiation. The photocatalytic ammonia production performance of TiO₂ nanobelts can be further enhanced through acid corrosion treatment, which generates secondary nanostructures. These surface nanostructures serve as potential catalytically active sites for nitrogen adsorption and reduction. Both photoelectrochemical measurements and photoluminescence spectra confirm that the optimized TiO₂ nanobelts exhibit improved charge separation. Given their excellent stability and unique 1D nanostructure, acid-corroded TiO₂ nanobelts are a promising support material for constructing high-performance composite photocatalysts for nitrogen fixation.

The development of efficient, stable, and low-cost electrocatalysts is crucial for hydrogen production via water electrolysis. While multi-principal element alloys (MPEAs) show great potential due to their multi-component synergy and tunable electronic structures, their practical application is often hampered by insufficient active sites and poor long-term stability. Herein, we report a phase-engineering-guided dealloying strategy to fabricate a high-performance MPEA catalyst for hydrogen evolution reaction (HER). This approach employs a triple-phase Al₆₀Ni₂₇Fe₅Co₅Mo₃ precursor, wherein chemical dealloying in an alkaline medium transforms the BCC parent phase into an ordered B2 phase, while completely dissolving the less stable FCC and tetragonal phases. This process results in a unique heterogeneous structure of Ni-based oxide nanocrystals enveloped by a Mo-rich metallic glass phase, coating the B2 phase surface. Benefiting from the abundant heterogeneous interfaces and synergistic interactions among multiple phases generated during dealloying, the catalyst exhibits outstanding activity and stability for HER in alkaline media, achieving a low overpotential of 35 mV at 10 mA cm^-2 and exceptional durability for 500 h at 100 mA cm^-2 with negligible activity degradation. This work presents a novel pathway for designing multiphase MPEAs and underscores the significant potential of high-performance electrocatalyst preparation by combining phase engineering with dealloying.

Proton exchange membrane water electrolysis (PEMWE) has long been regarded as a promising technology for hydrogen production due to its high electrolytic efficiency, reliability, and rapid response to renewable energy sources. Currently, noble metals and their oxides—such as Pt, IrO₂, and RuO₂—remain the most widely used and high active electrocatalysts in acidic media to accelerate the water electrolysis processes. However, their large-scale pratical application is severely hindered by the factors such as scarcity and the trade-off between activity and stability. Recently, the integration of artificial intelligence (AI) with high-throughput synthesis technology has demonstrated an increasingly vital role in material screening, enabling the design of highly efficient and cost-effective catalysts. This paper first reviews the fundamental catalytic mechanisms of the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER) in acidic media. Then, it summarizes the design strategies and prevailing challenges for noble metal catalysts in acidic water electrolysis. Finally, it presents several data-driven, synergistic approaches enabled by AI in noble metal catalyst research and development (R&D), along with the latest progress, current challenges, and future prospects.

Powder metallurgy (PM), as an advanced manufacturing method, offers different microstructures and mechanical properties for titanium (Ti) alloys compared to forging metallurgy (FM). Therefore, investigating the hot deformation behaviour of PM and FM Ti alloys is of great significance. Herein, we systematically study the hot workability and hot deformed microstructure of PM and FM Ti6Al4V alloys deformed at 1000 ℃-1200 ℃ and 0.01 s^-1~10 s^-1 strain rates, so as to compare the different hot working properties. The true stress-strain curves were drawn through the isothermal compression tests, and the constitutive equations as well as hot processing maps of PM and FM alloys were further constructed. Results show that the PM alloy displays smaller hot deformation resistance, larger hot working safe zone and smaller instable zone when compared with FM alloy. PM alloy has higher dynamic recrystallization (DRX) degree. In DRX process, the PM alloy was dominated by discontinuous dynamic recrystallization (DDRX), while the FM alloy was dominated by continuous dynamic recrystallization (CDRX). This work reveals the difference between PM and FM Ti6Al4V alloys in hot deformation behavior and hot working properties, and further explains the underlying deformation mechanism.