Nitrate () is a pervasive pollutant in industrial water treatment due to its widespread presence in industrial processes. Quaternary ammonium (R₄N⁺) groups are key for removal, but their efficiency varies with water quality. This study developed a mixed-grafted ion exchange resin, CMIET-A, by grafting trimethylamine and triethylamine onto a poly (methyl methacrylate) backbone, with Ferromagnetic γ-Fe₂O₃ nanoparticles to enhance separability and recyclability. Experiments and DFT calculations showed that CMIET-A effectively removed across a broad pH range (4.0-10.0), with a maximum adsorption capacity of 82.79 mg/g. The adsorption behavior fit the Freundlich isotherm model, and the process followed the pseudo-second-order kinetic model. After 20 cycles, the resin maintained a removal rate over 70 %. Both experiments on the influence of external ions and Molecular dynamics simulations indicated higher binding energy and diffusion coefficients for CMIET-A with , enhancing performance even in the presence of Cl^-. Characterization revealed that ion exchange, pore filling, electrostatic attraction, hydrogen bonding, and metal bridging collectively drove adsorption. Overall, this novel resin offers an efficient solution for removal in industrial settings.

Hollow noble metal nanostructures have broad applications in catalysis and other fields. Herein, we report that Ag@metal (Ag@M, M = Ru, Os, Ir, Pt, PtRu, PtRuOs) core@shell nanoparticles synthesized in oleylamine can transform into hollow AgM alloy nanoparticles via prolonged heating. The structural evolution mechanism is attributed to the Kirkendall effect, driven by unbalanced interdiffusion of Ag and M atoms: Ag atoms (with higher mobility) diffuse from the core to the shell more rapidly than M atoms, inducing vacancy flow and interface shift, ultimately forming hollow alloys with slightly reduced particle sizes. X-ray photoelectron spectroscopy reveals binding energy shifts of Ag and Pt in hollow AgPt alloys due to electronegativity differences. Electrochemical tests show that despite the lower electrochemically active surface area of hollow AgPt alloys caused by Ag-induced Pt dilution, their methanol oxidation reaction activity and onset potential are comparable to the core-shell precursors. This is because the ensemble effect from Ag-Pt alloying weakens CO adsorption on Pt sites, offsetting the dilution-induced negative effect. This study provides insights for designing efficient Ag-based nanoalloy electrocatalysts.

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.

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.

Mineral processing wastewater poses severe environmental risks due to its complex composition (high suspended solids, residual reagents, heavy metals), making its treatment critical for sustainable mining. This review systematically summarizes mineral processing wastewater treatment technologies, including conventional methods and emerging approaches. Conventional physical-chemical methods are widely used but suffer from sludge production and limited resource recovery. Advanced oxidation processes (e.g., plasma oxidation, photo-Fenton) efficiently degrade refractory organics and novel adsorbents (MOFs, selective resins) enable targeted heavy metal recovery and deep purification. Artificial intelligence and digital twin further promote intelligent process control. Future directions focus on integrating multi-technologies into "classification treatment-quality-based reuse" systems to achieve comprehensive recovery of water, salts, and valuable metals, advancing mining towards a circular economy and near-zero discharge.

The composites composed of Carbon nanotube (CNT) and inorganic magnetic materials are candidates for broadband electromagnetic wave (EMW) absorbing materials (EWAM). However, poor interfacial compatibility between CNT and inorganic magnetic materials limits the enhancement of broadband EMW absorption performance. Herein, this study innovatively prepared the organic magnetic ionic liquid (MIL) with a zwitterionic structure and combined it with CNT to obtain the "Magnetic ionic liquid/CNT composite gel" (MIL/CNT). In the MIL/CNT, the energy of EMW is well attenuated through the multi-EMW dissipating routes, such as conductance loss, polarization loss and magnetic loss. Remarkably, attributed to the zwitterionic structure, the stronger ionic dipole polarization loss has been induced to dissipate the EMW, which achieved an effective absorption band (EAB) of 7.5 GHz (9.44-16.94 GHz) and minimum reflection loss (RL_min) of -46 dB with 2.1 mm thickness at 15.8 GHz. The MIL/CNT composite demonstrated excellent broadband electromagnetic wave absorption, offering a novel strategy for fabricating EMW defense materials with a wide operational frequency range.

More than 2 billion tons of coal-based solid wastes (CBSW) are produced annually in China present not only significant environmental hazards, including air pollution from dust, soil degradation, and water contamination from heavy metals, but also direct safety risks such as spontaneous combustion and landslides. Currently, soil degradation is becoming an increasingly serious concern. Artificial soil is a crucial green construction material. However, the current resource utilization of CBSW in artificial soil is confronted with difficulties such as low efficiency, high ecological risks, and obstacles to industrialization. Therefore, there is an urgent requirement to develop a stable and eco-friendly approach for the construction of artificial soil. This paper reviews the physicochemical properties of CBSW and its adaptability to soil improvement. Considering the application directions of CBSW in ecological soil (such as remediating contaminated soil, improving poor soil quality, and promoting plant growth). It focuses on key methods for preparing artificial soil. These methods include pretreatment technology, optimizing the ratio of solid waste, additives, and soil, and evaluating ecological effects. This work provides insights into transforming coal waste into a valuable resource for ecological restoration.

The urgent need for high-performance energy storage devices has been driving the quest for superior battery-type electrode materials for hybrid supercapacitors (HSCs), however the relevant synthesis methods are usually tedious and poorly affordable. In this paper, a two-step route was elaborated to prepare Ni, Co hydroxide/N-doped porous carbon (Ni_xCo_1-x(OH)₂/NPC) nanocomposites for hybrid supercapacitors. NPC with unique three-dimensional interconnected porous structure was obtained by HIPE high internal phase emulsion (HIPE) polymerization with subsequent pyrolysis. The NPC can act not only as a conductive network providing abundant accessible area and convenient charge transfer routes, but also as an anchoring platform for Ni_xCo_1-x(OH)₂ growth via chemical bath deposition (CBD) without agglomeration. By tuning Ni²⁺/Co²⁺ ratio, the optimized Ni_xCo_1-x(OH)₂/NPC nanocomposite exhibited excellent electrochemical performance with a capacity of 1392 F g^-1 at 1 A g^-1 in 6 M KOH solution. Furthermore, coupling with an activated NPC anode, the assembled hybrid supercapacitor possessed an appreciable energy density of 118.9 Wh kg^-1 at 400.0 W kg^-1 and a capacitance retention ratio of 80.7 % after 5000 charge-discharge cycles, showing considerable application prospects. This work provides new inspirations for the reasonable design and optimization of new electrode materials for first-rate hybrid supercapacitors.