Search Results (2,731)

Electrochemical water splitting stands as a feasible approach for sustainable hydrogen production, but its industrial implementation is restricted by sluggish oxygen evolution reaction (OER) kinetics and excessive dependence on freshwater resources. As a widely existing alternative, seawater contains a high concentration of chloride ions (Cl⁻), which give rise to serious electrode corrosion and catalyst deactivation, bringing great challenges to actual electrolysis applications. Herein, we report a facile room-temperature two-step soaking strategy to fabricate sulfur-modified NiFe layered double hydroxide (S-NiFe-LDH) catalysts for efficient OER in both alkaline freshwater and seawater electrolytes. The introduction of sulfur not only optimizes the electronic structure of NiFe-LDH to strengthen intrinsic catalytic activity and speed up charge transfer, but also promotes the formation of a Cl⁻-resistant layer, thus significantly improving corrosion resistance. In addition, DFT calculations show sulfur modification in NiFe layered double hydroxide upshifts the O 2p-band center to activate lattice oxygen, switches the oxygen evolution reaction pathway to the lattice oxygen mechanism with reduced thermodynamic barriers, and realizes the selective adsorption of OH⁻ over Cl⁻. As a result, the as-prepared S-NiFe-LDH catalyst exhibits exceptional OER performance, requiring overpotentials (η) of 250, 270, and 290 mV to reach current densities of 50, 100, and 200 mA·cm⁻² in 1 M KOH, respectively, with a Tafel slope of 22.3 mV·dec⁻¹. Moreover, it maintains remarkable stability for more than 200 h in alkaline seawater electrolytes and achieves nearly 100% Faradaic efficiency for water splitting, effectively avoiding the parasitic chlorine evolution reaction (CER). This work provides a scalable and energy-efficient synthetic route for designing advanced non-noble metal catalysts, paving the way for industrial-scale hydrogen production from seawater. Full article

Dry reforming of methane (DRM) is a key reaction for syngas production and greenhouse gas utilisation, involving multiple interacting operating variables. In this work, an interpretable machine learning approach based on CatBoost regression coupled with SHapley Additive exPlanations (SHAP) is applied to a previously published DRM dataset to analyse the influence of reaction temperature, CH₄/CO₂ feed ratio, and Ni loading on CH₄ and CO₂ conversions and H₂ and CO yields. The objective of this study is methodological rather than experimental, focusing on the use of interpretable machine learning to extract variable importance hierarchies and conditional interaction effects from data-limited DRM studies. The analysis confirms that reaction temperature is the dominant controlling parameter, while feed ratio and Ni loading exhibit secondary, regime-dependent influences. No new catalytic mechanisms or experimental findings are proposed. The results illustrate how CatBoost–SHAP analysis can complement experimental DRM research by providing transparent, quantitative interpretation of published datasets under realistic data constraints. These findings are consistent with established DRM thermodynamic and kinetic behaviour, where temperature governs endothermic reforming reactions, while feed composition and metal loading influence carbon formation pathways and catalytic activity. Full article

This study investigates the possibility of producing a complex W–Mo–Cr-containing alloy via metallothermic reduction of oxide concentrates in the presence of direct reduced iron (DRI) in an induction furnace under atmospheric conditions. A complex FeAlSiCa alloy was used as a reductant due to its high exothermicity and combined reducing potential. Thermodynamic analysis showed that the reduction of WO₃ and MoO₃ is more favorable compared to Cr₂O₃, which is reflected in the temperature profiles of the process. Experimental results confirmed that the addition of FeAlSiCa leads to intensive exothermic reactions and promotes melt formation. The estimated apparent recovery of W and Mo reached up to ~99%, while Cr estimated apparent recovery remained lower (up to ~70%) due to its higher thermodynamic stability and kinetic limitations. Microstructural analysis revealed a heterogeneous structure consisting of an Fe-based matrix and W–Mo-rich phases, including characteristic “fishbone” morphologies. An increase in reductant amount led to higher Si content in the alloy, indicating the need for composition optimization. The results demonstrate the feasibility of direct complex alloying as an alternative to conventional ferroalloy-based methods and highlight the potential for developing resource-efficient and low-carbon metallurgical technologies. Full article

Reliability degradation in semiconductor devices originates from microscopic stochastic processes such as defect motion, diffusion, bond rearrangement, and charge trapping occurring under electrical and thermal stress. Experimental degradation measurements, however, often exhibit smooth empirical scaling behavior, particularly power-law time dependences extending across many orders of magnitude in time. This tutorial reviews the thermodynamic and kinetic foundations underlying these observations and explains how empirical power-law degradation behavior can emerge from the collective interaction of many microscopic stochastic processes. The discussion begins with irreversible thermodynamics, random walk transport, diffusion, and Arrhenius kinetics and then connects these microscopic concepts to the macroscopic degradation trends commonly observed in semiconductor reliability experiments. Attention is given to the interpretation of stress-dependent power-law degradation kinetics and their implications for accelerated lifetime extrapolation. Practical limitations associated with conventional logarithmic degradation analysis are examined, including baseline sensitivity, logarithmic instability near the measurement floor, and systematic curvature that may remain hidden despite high goodness-of-fit metrics. Methods based on transformed-coordinate linearization and curvature-sensitive extraction are discussed together with their implications for time-to-failure extrapolation and activation-energy interpretation. Experimental studies of phenomena such as bias temperature instability frequently show degradation behavior in which the time exponent depends systematically on voltage and temperature stress conditions. Under such conditions, the reciprocal exponent $m=1/n$ can significantly amplify stress acceleration during lifetime extrapolation. This work provides a conceptual framework connecting microscopic stochastic degradation physics with the empirical methods commonly used in practical semiconductor reliability analysis and long-term lifetime prediction. Full article

Background: Daptomycin, a lipopeptide antibiotic with critical clinical applications, presents a formidable crystallization challenge due to its high conformational flexibility and complex ionization equilibrium. Current literature lacks reports on single crystals or highly crystalline powders of this molecule. This study aims to elucidate the thermodynamic and kinetic mechanisms governing daptomycin solubility and crystallization to establish a rational screening pathway. Methods: In this study, the solubility of daptomycin was systematically measured across eight pure solvents using a static gravimetric method. Molecular-level insights were obtained by integrating experimental data with the Conductor-like Screening Model for Real Solvents (COSMO-RS) and molecular dynamics (MD) simulations. Results: Solubility trends correlated strongly with solvent electrostatic and hydrogen-bonding capabilities. MD simulations revealed that the solvent’s ability to modulate conformational diversity—quantified by the number of dominant conformational clusters—is the decisive factor governing crystallization. For instance, aqueous systems exhibited strong Coulombic stabilization (−1126.61 kJ/mol). Crucially, solvents like acetone restricted daptomycin to a limited number of conformers (12 clusters), significantly lowering the nucleation barrier and yielding crystalline powders with distinct PXRD peaks. Conversely, solvents like methanol induced high conformational diversity (53 clusters), resulting exclusively in amorphous precipitates. Conclusions: The “number of conformational clusters” serves as a robust descriptor for rapidly screening crystallization solvents, effectively bridging thermodynamics and kinetics. This strategy provides a rational, reduced-trial-and-error framework for crystallizing complex, flexible macromolecules with multiple dissociation sites, moving beyond traditional trial-and-error approaches. Full article

Among the various CO₂ capture technologies, chemical absorption is currently one of the most widely applied methods in industrial practice. In this study, density functional theory was employed to investigate the reaction mechanisms of CO₂ absorption by typical alkanolamine solvents. Reaction pathways between CO₂ and four representative alkanolamines—monoethanolamine (MEA), diethanolamine (DEA), triethanolamine (TEA), and methyldiethanolamine (MDEA)—were constructed and analyzed. By evaluating the activation energy barriers of different amines, the thermodynamic characteristics and reaction feasibility of the CO₂ absorption process were systematically elucidated. The results show that the primary amine MEA exhibits the lowest activation energy barrier (32.02 kJ/mol), indicating the most favorable reaction kinetics, while the secondary amine DEA shows a slightly higher barrier of 47.35 kJ/mol. As tertiary amines, TEA and MDEA exhibit significantly higher activation energy barriers, indicating slower reaction kinetics; however, they generally possess higher CO₂ loading capacities and less stable reaction products, which facilitate solvent regeneration. The activation energy barriers of MDEA and TEA were calculated to be 54.53 kJ/mol and 94.17 kJ/mol, respectively, indicating that MDEA reacts more readily with CO₂ than TEA. Full article

The post-combustion carbon capture process with monoethanolamine/piperazine (MEA/PZ) blends encounters notable modeling and optimization challenges. These arise from strong thermodynamic–kinetic nonlinear coupling, as well as limited availability of high-quality experimental data. To address this, we propose a machine learning and multi-objective optimization strategy driven by physicochemical features. By extracting explicit physical features and embedding physicochemical constraints into data-driven models, this study evaluated the predictive performance of three distinct algorithms based on wet-wall column experimental data. These algorithms included natural gradient boosting (NGBoost), sure independence screening and sparsifying operator (SISSO), and gaussian process regression (GPR). Subsequently, an optimization problem aimed at minimizing $P_{{\mathrm{CO}}_2}^{*}$ and maximizing $k_{\mathrm{g}}^{\prime }$ was formulated. The multi-objective beluga whale optimization (MOBWO) algorithm was then employed for global optimization and benchmarked against the traditional non-dominated sorting genetic algorithm II (NSGA-II). Results indicate that the Gaussian process regression (GPR) model performed best when it was enhanced by physicochemical features and optimized via Bayesian hyperparameter tuning. It achieved R² values of 0.989 and 0.953 for $P_{{\mathrm{CO}}_2}^{*}$ and $k_{\mathrm{g}}^{\prime }$, with average absolute relative deviations (AARDs) kept below 15.7% and 12.2% respectively. Feature importance analysis validated the underlying physical laws. Specifically, temperature dictates thermodynamic equilibrium, while CO₂ loading limits mass transfer kinetics. In the optimization phase, MOBWO outperformed NSGA-II by generating a more uniformly distributed Pareto front. Decision-making analysis further identified three typical operating regimes encompassing kinetics-dominant, thermodynamics-dominant, and comprehensive equilibrium conditions. This framework provides a robust paradigm for small-sample modeling and optimization in complex chemical processes. Full article

The concurrent accumulation of plastic waste and CO₂ emissions poses a critical environmental challenge while presenting a compelling opportunity for integrated carbon management. Coupled plastic waste reforming and CO₂ conversion has recently emerged as a promising strategy to valorize these abundant waste streams into fuels and value-added chemicals, enabling a closed carbon cycle. This review systematically summarizes recent advances in integrated electrochemical and photoelectrochemical systems for the co-conversion of plastic waste and CO₂. Fundamental reaction pathways, including plastic depolymerization, reforming, and oxidation, are discussed in conjunction with their thermodynamic and kinetic coupling to CO₂ reduction. Particular emphasis is placed on paired electrochemical processes, such as plastic-derived alcohol oxidation coupled with CO₂ reduction processes, all of which offer enhanced energy efficiency. Photoelectrochemical approaches driven by renewable energy are further highlighted for their potential to operate under mild conditions. In addition, key design strategies for catalysts and electrodes—focusing on earth-abundant materials, redox stability, interfacial engineering, and selectivity control—are critically evaluated. Finally, current challenges and future opportunities are outlined to accelerate the development of scalable, efficient, and sustainable technologies for circular chemical manufacturing. Full article

A sustainable alginate-based composite adsorbent was developed by valorizing soy whey wastewater for the efficient removal of copper (II) ions from aqueous solutions. Soy whey wastewater/sodium alginate/cellulose (SWWSAC) beads were fabricated via a controlled slow-release calcium ion cross-linking strategy. This strategy resulted in homogeneous gelation, effective encapsulation of wastewater-derived organics and the formation of a hierarchical mesoporous structure. Compared with pure sodium alginate (SA) and sodium alginate–cellulose (SAC) beads, the SWWSAC beads exhibited a significantly higher specific surface area (3.95 m²/g) and pore volume (0.021 cm³/g), thus having markedly enhanced copper (II) ion adsorption performance. Batch adsorption experiments demonstrate that the adsorption process was strongly dependent on solution pH, adsorbent dosage, contact time and initial metal concentration. Kinetic analysis indicates that the adsorption process followed a pseudo-second-order model, while equilibrium data were well described by the Langmuir isotherm, corresponding to monolayer chemisorption. Based on this isotherm, SWWSAC beads had a theoretical maximum adsorption capacity of 168.3 mg/g (25 °C), 190.8 mg/g (35 °C), and 204.4 mg/g (45 °C). Thermodynamic results reveal that the adsorption was spontaneous and endothermic. FTIR and XPS analyses confirm that copper (II) ion removal was governed by synergistic complexation involving carboxyl, hydroxyl, carbonyl, and protein-derived nitrogen-containing functional groups. Moreover, the SWWSAC beads had a copper (II) ion removal efficiency of (92.4 ± 0.4)% and retained 73.3% of their initial adsorption capacity after six regeneration cycles in actual electroplating wastewater treatment. In this process, the beads exhibited good anti-interference performance against coexisting cations and good structural stability. Therefore, this work demonstrates an effective and low-cost strategy for copper (II) ion removal while providing a value-added route for the sustainable utilization of soy whey wastewater. Full article

The present study investigates the solar-assisted photo-Fenton-like degradation of a reactive azo dye (Red SPR) using an iron-based metal–organic framework, MIL-100(Fe), as a heterogeneous catalyst. The synthesized MIL-100(Fe) was successfully characterized by XRD, SEM, EDX, and FTIR analyses, confirming the formation of a crystalline, porous structure with well-dispersed Fe active sites. The catalytic performance was systematically evaluated under various operational parameters, including hydrogen peroxide dosage, catalyst loading, pH, circulation flow rate, initial dye concentration, and temperature. The results demonstrated that optimal degradation efficiency was achieved at pH 3.0, H₂O₂ concentration of 400 mg L⁻¹, and catalyst dosage of 40 mg L⁻¹, while a circulation flow rate of 400 mL min⁻¹ ensured optimal hydrodynamic conditions. The system exhibited rapid degradation kinetics, achieving nearly complete dye removal within 60 min under solar irradiation. Kinetic analysis revealed that the degradation process follows pseudo-first-order behavior, with rate constants increasing from 0.1040 to 0.1589 min⁻¹ as temperature increased from 25 to 55 °C. Thermodynamic analysis indicated that the process is endothermic (ΔH` = 8.72 kJ mol⁻¹) and kinetically favorable with a low activation energy (Ea = 11.32 kJ mol⁻¹), while negative entropy values suggested the formation of an ordered transition state. Radical scavenger experiments confirmed that hydroxyl radicals (•OH) are the dominant reactive species, with secondary contributions from superoxide radicals (O₂•⁻). The enhanced performance is attributed to the synergistic effect of solar irradiation and Fe³⁺/Fe²⁺ redox cycling within the MIL-100(Fe) framework. Hence, the study demonstrates that MIL-100(Fe) is a highly efficient and sustainable catalyst for solar-driven wastewater treatment applications. Full article

Producing hydrogen from ethanol steam reforming (ESR) is a carbon-neutral and environment-friendly method, which has been expected to reduce the excessive emission of environmental pollution and over-exploitation of fossil resources. Currently, great advances have been made on heterogeneous catalysts, but an in-depth and more comprehensive understanding to further promote this reaction process is still required. Herein, the thermodynamic and kinetic analyses of ESR are firstly highlighted. Then, various reaction pathways of ESR are discussed in detail, respectively combined with experimental studies and density functional theory calculations. On this basis, the key factors affecting the catalytic performance over non-noble and noble metal catalysts are summarized, such as alloying, optimization of the preparation methods, promoter addition and support modification. In addition, the process intensification technologies, including catalytic membrane reactors, adsorption-enhanced reforming and microchannel reactors, are analyzed regarding breaking the thermodynamic limitations and improving the heat and mass transfer efficiency. Finally, the challenges and potential strategies of ESR in the research of dynamic reaction mechanisms, regulation of catalyst stability and integration of intensification technologies are summarized. Full article

High-entropy alloys and the broader class of compositionally complex alloys have recently attracted significant attention as promising materials for solid-state hydrogen storage. Their potential arises not only from high configurational entropy but also from the possibility of tailoring phase composition, crystal structure, local chemical environment, and defect states that govern hydrogen sorption thermodynamics and kinetics. This review summarizes current understanding of hydrogen interaction mechanisms in HEAs and discusses the role of body-centered cubic (BCC), face-centered cubic (FCC), and Laves phases in determining hydrogen capacity, reversibility, and cyclic stability. The limitations of commonly used descriptors, including valence electron concentration (VEC), atomic size mismatch δ, enthalpy of mixing ΔH_mix, and Ω parameter, in predicting hydrogen storage behavior are critically analyzed. Particular attention is given to the effects of processing methods, phase transformations during hydrogenation/dehydrogenation, and the energetic heterogeneity of interstitial sites in multicomponent systems. The review highlights that future progress will depend on the transition from empirical alloy discovery toward physically informed multiparametric design integrating CALPHAD, DFT modeling, machine learning, and in situ/operando characterization techniques for the development of efficient and durable hydrogen storage materials. Full article

Developing low-cost, non-noble-metal electrocatalysts to replace platinum-based benchmarks for the alkaline hydrogen evolution reaction (HER) remains a critical challenge. Using density functional theory (DFT) calculations combined with the computational hydrogen electrode (CHE) model, we systematically investigate the thermodynamics, kinetics, and intrinsic reaction mechanism of HER on a TiO₂-supported Ni₃ trimer (Ni₃/TiO₂) in alkaline media. We find that the Ni₃ trimer, rather than the TiO₂ support, provides multiple active sites for intermediate adsorption. The trimeric Ni₃ motif generates delocalized electronic states, leading to electron-rich active sites that significantly lower the barrier for water dissociation, facilitate intermediate desorption, and sustain catalytic turnover. The reaction proceeds predominantly via the Volmer–Heyrovsky pathway, where either water dissociation or H₂ desorption can be the rate-determining step, depending on the applied potential. Crucially, the significantly reduced reaction barrier heights demonstrate that the alkaline HER activity of Ni₃/TiO₂ is comparable to that of benchmark Pt₁/TiO₂ single-atom catalysts (SACs). This work establishes a promising design strategy for constructing high-performance non-noble metal few-atom catalysts (FACs) to replace noble metal SACs for multi-step electrocatalytic reactions. Full article

Although amorphous calcium phosphate (ACP) has been extensively employed as a biomaterial in dental and orthopedic fields, its exploration for environmental applications—particularly in potentially toxic element remediation—remains notably limited in the scientific literature. This study reports the rational design of a multifunctional adsorbent by integrating sodium citrate-stabilized ACP (Cit-ACP) nanoparticles into calcium-crosslinked sodium alginate (SA) hydrogel beads for selective Cu²⁺ sequestration from aqueous systems. Comprehensive sorption assessments revealed that equilibrium uptake aligned with the Freundlich isotherm (indicating heterogeneous surface interactions), while kinetic profiles adhered to pseudo-second-order behavior, characteristic of chemisorption-driven processes. Under optimized operational parameters (pH 5.0, 45 °C), the Cit-ACP/SA composite attained an exceptional maximum adsorption amount of 307.76 mg/g. Thermodynamic analysis further confirmed the spontaneity (ΔG° < 0) and endothermic nature (ΔH° > 0) of the process. Multi-technique characterization (XPS, FTIR, XRD, pH trajectory) elucidated a dual-mode adsorption mechanism: (i) ion exchange between aqueous Cu²⁺ and structural Ca²⁺ within both the alginate matrix and ACP framework; and (ii) in situ surface precipitation yielding copper-substituted hydroxyapatite. Owing to its facile aqueous-phase synthesis, superior adsorption performance, biodegradability, macroscopic bead morphology enabling rapid separation, and robust selectivity in complex matrices, the Cit-ACP/SA composite presents a sustainable, scalable, and eco-compatible platform for practical remediation of copper-contaminated wastewater. Full article

Heavy metal pollution in water threatens ecosystems and human health, necessitating efficient, low-cost, and sustainable remediation technologies. A manganese-modified bamboo biochar (Mn-BC) was synthesized via impregnation of raw biochar in KMnO₄ followed by pyrolysis at 500 °C, and its adsorption ability was systematically evaluated for Pb(II) and Cr(VI) removal through batch adsorption experiments investigating the effects of solution pH (2–9), adsorbent dosage (0.1–0.9 g in 20 mL), contact time (0–50 min), initial metal concentration (20–100 mg L⁻¹), and temperature (25–50 °C). SEM/TEM-EDS and XRD confirmed successful Mn incorporation as MnO_x phases, while textural analysis showed improved porosity after modification, with the BET surface area and total pore volume increasing from 77.28 m² g⁻¹ to 123.51 m² g⁻¹ and from 0.041 cm³ g⁻¹ to 0.063 cm³ g⁻¹, respectively. Batch adsorption experiments demonstrated strong pH dependence, with optimum removal at pH 8 for Pb(II) (91.87%) and pH 5 for Cr(VI) (88.2%). Adsorption was rapid within the first 30 min and reached equilibrium. A pseudo-second-order (PSO) model provided the best kinetic description (R² = 0.99) with calculated q_e values of 19.98 mg g⁻¹ for Pb(II) and 19.13 mg g⁻¹ for Cr(VI). Isotherm analysis yielded Langmuir monolayer capacities of 37.24 mg g⁻¹ (Pb(II)) and 16.39 mg g⁻¹ (Cr(VI)), with Pb(II) better described by Freundlich behavior and Cr(VI) closely fitting Langmuir assumptions. Thermodynamic results indicated endothermic adsorption (ΔH° = 41.98 and 29.67 kJ mol⁻¹ for Pb(II) and Cr(VI)) and increased interfacial randomness (ΔS°), with adsorption becoming more favorable at higher temperature (maximum removal at 50 °C: 93.21% Pb(II), 87.37% Cr(VI)). Mn-BC maintained >60% efficiency after five regeneration cycles. Mechanistically, Pb(II) removal was primarily governed by ion exchange and surface complexation, whereas Cr(VI) removal involved electrostatic attraction, partial reduction to Cr(III), and subsequent complexation on oxygenated and Mn–O sites. Overall, these findings demonstrate that Mn-BC is a practical, reusable, and competitive adsorbent for the efficient removal of Pb(II) and Cr(VI) from wastewater, supporting sustainable water treatment strategies. Full article