The growing demand for energy-efficient transportation systems has intensified the need for structural materials that combine low density, high strength, and environmental responsibility. High-entropy alloys (HEAs), owing to their vast compositional flexibility and tunable mechanical properties, are promising candidates for nextgeneration lightweight structural applications. However, systematic experimental exploration of their expansive compositional design space remains time-consuming and resource-intensive. In this study, a physics-guided surrogate modelling framework is developed for sustainability-aware screening of HEA compositions under datalimited conditions. Starting from 32 experimentally reported alloys spanning FCC-, BCC-, and multiphase systems, a deterministic descriptor-driven strategy was employed to generate a physically consistent synthetic dataset across a 14-element compositional space. Key thermodynamic and atomic-scale descriptors including valence electron concentration (VEC), atomic size mismatch (δ), configurational entropy (ΔS mix ), electronegativity deviation (χ_std), mixing enthalpy proxies, and density-related features were incorporated to preserve metallurgical coherence. An XGBoost regression model trained on this physics-constrained dataset achieved strong internal consistency (R 2 ≈ 0.99) under controlled noise conditions, reflecting accurate reconstruction of the embedded descriptor–property relationships. Validation against an independent experimental literature dataset (N = 58 alloys) yielded R 2 = 0.81, indicating physically meaningful transferability despite realworld microstructural and processing variability not explicitly captured by composition-based descriptors. Feature-importance and SHAP analyses consistently identified VEC, atomic size mismatch, and density-related terms as dominant contributors to yield strength, aligning with established solid-solution strengthening mechanisms. To extend the framework beyond mechanical optimization, a sustainability index based on elemental abundance, toxicity, and resource criticality was integrated into a composite eco-performance metric. The results demonstrate that strength-to-weight efficiency and environmental responsibility can be jointly optimized within the explored compositional domain. Overall, this work establishes a transparent and reproducible foundation for physics-informed, sustainability-aware HEA screening, positioning surrogate modelling as a structured compositional pre-screening tool to accelerate data-driven alloy design while maintaining alignment with metallurgical principles and sustainability objectives.

Metal matrix composites (MMCs) are gaining prominence over conventional metals due to their superior strength-to-weight ratio, low density, minimal thermal expansion, and high-temperature resistance. This study investigates the enhancement of MMC properties by reinforcing Al-6061 alloy with fly ash particles. The composites were fabricated using the stir casting method, varying fly ash grain sizes (0-75 μm, 75-90 μm, and 90-150 μm), weight percentages (10%, 20%, and 30%), and melting temperatures (800 ℃, 850 ℃, and 900 ℃). A novel multi-objective optimization technique based on non-dominated sorting with Pareto fronts identified the optimal parameters as 30% fly ash weight, 0-75 μm grain size, and 850 ℃ melting temperature. Microstructural analysis confirmed the uniform distribution of fly ash in the matrix, and hardness testing revealed significant improvement with smaller grain sizes and higher fly ash content. This study highlights the potential of fly ash-reinforced MMCs for applications demanding superior mechanical properties.

The use of magnesium (Mg) alloy as biomedical implants has garnered increased attention over the years due to its capability to progressively biodegrade in vivo, thereby avoiding the need for surgical removal of metallic implants after a complete recovery. This would, in turn, mitigate any further post-surgical and post-operative complications, reducing costs from revisional surgeries as compared to the usage of traditional metallic implants. This overview discusses the advantages that Mg-based alloys possess in biomedical implants owing to their excellent mechanical, bioactivity, and biocompatibility traits. The major limitations, mainly due to the rapid corrosive and degradative nature of Mg-based alloys in the biological environment, are reviewed comprehensively. To address the problems of Mg-based alloys for biomedical applications, the solution of plasma electrolytic oxidation (PEO) on the surface of Mg-based alloys was introduced as it could potentially help alleviate and enhance the properties of Mg-based alloys, providing improved performance in orthopedic applications. The corrosion protections can be further enhanced by combining the benefits of PEO with other biocompatible sealing layers toward practical medical applications.

Selenium is a crucial trace element integrated into selenoproteins such as glutathione peroxidases (GPxs), thioredoxin reductases (TrxRs), and selenoprotein P (SELENOP), which preserve redox homeostasis by neutralizing reactive oxygen species (ROS) and preventing lipid peroxidation, thus alleviating oxidative stress associated with carcinogenesis. This review clarifies selenium’s biochemistry, encompassing selenocysteine biosynthesis and integration through SECIS elements, as well as its modulation of the Nrf2 pathway for antioxidant gene expression, highlighting its intricate dual roles in normal cytoprotection versus potential cancer promotion under chronic activation. Experimental evidence from in vitro, animal, and epidemiological studies illustrates anticancer effects through apoptosis induction (via p53/Bcl-2/caspase pathways), cell cycle arrest, antiangiogenesis, epigenetic regulation (DNA demethylation and histone modifications), and immune modulation. Clinical trials such as SELECT and NPC emphasize benefits predominantly in selenium-deficient populations utilizing organic forms like selenomethionine rather than inorganic selenite. Optimal bioavailability differs by form of organic compounds, such as methylselenocysteine demonstrate enhanced absorption and reduced toxicity, while novel selenium nanoparticles improve targeted delivery, highlighting selenium’s potential in cancer prevention strategies customized to genetic and nutritional profiles.

We investigate solvent-mediated nucleation and crystallization of poly(ethylene terephthalate) (PET) from trifluoroacetic acid (TFA) solutions upon gradual addition of water, a poor solvent for PET. The system undergoes liquid–liquid phase separation, formation of PET-rich domains, and growth of nanoparticles, interpreted within classical nucleation theory and polymer solution thermodynamics, where solvent composition controls the balance between bulk free-energy gain and interfacial free-energy cost. On this conventional basis, we introduce a strictly heuristic analogy between surface-energy-dominated PET nucleation and entropy–area concepts from black-hole thermodynamics. In this view, increasing water content drives the system from a homogeneous, high-entropy solution to an aggregated state and the PET–solution interface is used metaphorically as a “soft-matter event horizon” beyond which individual chain conformations become experimentally inaccessible. Inspired by Bekenstein’s area law, we explore a simple toy model in which an effective entropy-like measure is postulated to scale with aggregate surface area, without claiming experimental verification of entropy–area scaling in PET or literal applicability of gravitational bounds. Thus, the work provides an experimentally grounded study of PET nucleation, augmented by a cross-disciplinary, metaphorical framework for discussing boundary-dominated thermodynamics.

Utilizing ultrasonic techniques at a fixed frequency of 1 MHz, this study examines the molecular interactions and acoustic properties of the high molecular weight polysaccharide Dextran (Mw 70,000) dissolved in aqueous 1(M) NaOH at different concentrations (0.1%, 0.25%, 0.5%, 0.75%, and 1% w/v) and temperatures (303 K, 308 K, 313 K, 318 K, and 323 K). Important acoustical and thermodynamic parameters, such as acoustic impedance (Z), adiabatic compressibility (β), intermolecular free length (L f ), relaxation time (τ), and Gibbs free energy for molecular interaction (ΔG), were calculated using the experimental measurements of ultrasonic velocity, density, and viscosity. These results offer important new information about Dextran's conformational behavior, solvation dynamics, and interaction mechanisms in a highly basic aqueous medium. The study provides a better understanding of molecular relationships in intricate biopolymer solutions and demonstrates the usefulness of ultrasonic techniques in characterizing polymer–solvent systems.

Aluminum, as a metal material with excellent mechanical properties and high energy density, is widely used in fields such as aerospace, automotive manufacturing, and energetic materials. However, the performance of nano aluminum powder (ANP) is limited due to issues such as surface oxidation, formation of oxide layers, and aggregation. Carbon coating, as an effective surface modification method, can significantly enhance the high-temperature stability and oxidation resistance of ANP. This article focuses on aluminum based carbon coated nano composite particles with core-shell structure, summarizes the research progress of molecular dynamics (MD) method, and deeply explores the thermal melting behavior and high-temperature oxidation mechanism of nano metal particles. By analyzing the influence of factors such as carbon coating thickness, structure, and temperature on the thermal stability and oxidation kinetics of composite particles, the micro evolution mechanism of core-shell structure under thermal action is revealed. Finally, a summary and outlook are made on optimizing the preparation process of carbon coated ANP and expanding its application scenarios. This study can provide reference opinions for researchers of aluminum based carbon coated nanocomposites with core-shell structures and scientists and engineers.

This study investigates the effect of para-substituents on the reaction rate in the synthesis of para-substituted benzoyl thiosemicarbazide, using Hammett’s equation as a theoretical framework. Hammett’s equation relates reaction rates and equilibrium constants to the electronic nature of substituents on aromatic rings. The reaction rates were measured for benzoic acids with various para-substituents, and deviations from Hammett’s linear correlation were observed, particularly with electron-donating groups. These deviations highlight the complex influence of substituent electronic effects on reaction kinetics. Melting point analysis was used to assess the purity and identity of the synthesized compounds. UV absorption spectra were recorded with a BIO-TEK spectrophotometer, and IR spectra were obtained using a Bio-Rad Merlin FT-IR Mod FTS3000 spectrometer. Spectroscopic data provided further insight into the structural and electronic characteristics of the products, supporting the kinetic findings. Overall, the study underscores how substituent electronic properties modulate reactivity, not always in full agreement with classical Hammett behavior.

Plants are a valuable source of pharmaceuticals, as most plant parts contain bioactive components. Sumac (Rhus coriaria L.) is a widespread shrub in the Mediterranean region, and it has been historically used as a spice and flavoring component. Due to its widespread therapeutic use in the northern Iraqi towns of Koisinjaq and Erbil, the sumac plant was chosen for this purpose. Phytochemical and antioxidant studies on the plant were not conducted in this location, despite having been done in other places. The study focused on the phytochemical constituents, chromatographic fractionations and antioxidant activities of sumac fruits. Methanolic sumac extract was subjected to column chromatography using toluene-EtOAc-HCO 2 H (4:5:2) mobile phase, resulting in the separation of seven fractions. Identification of the extract and fraction was done using HPLC/DAD. The methanolic extract was rich in phenolic content (138.46[Formula: see text]mg GAE/g dry weight (dw)), flavonoids (5.54[Formula: see text]mg QE/g), flavonols (10.15[Formula: see text]mg RE/g) and anthocyanins (5.33[Formula: see text]mg/kg), indicating the high antioxidant activity of sumac fruits. Furthermore, the extract demonstrated ferric-reduction and metal-chelating capabilities, containing 92.31[Formula: see text]mg FeSO 4 /g and 638.46[Formula: see text]mg Fe[Formula: see text]/g. This research suggests that the food and pharmaceutical sectors could benefit from the antioxidants and natural phytochemicals found in the sumac plant.

In this study, density functional theory (DFT) was used to evaluate the corrosion inhibition potential of six commonly used molecular drugs: diazepam, chlorpromazine, amitriptyline, cimetidine, metformin, and ranitidine. These compounds were chosen based on their structural features and electron-rich functional groups, which are believed to promote interactions with metal surfaces. Quantum chemical calculations were performed in both gas and aqueous phases using the 6-311[Formula: see text]G (d, p) basis set. Key electronic descriptors, including HOMO, LUMO, energy gap (Eg), dipole moment, ionization energy, electron affinity, hardness, softness, and chemical potential, were calculated to assess molecular reactivity and predict inhibition efficiency. Additional analysis involved molecular electrostatic potential (MEP) mapping, natural bond orbital (NBO) analysis, and Fukui function calculations to identify electron-rich (nucleophilic) and electron-deficient (electrophilic) regions of each molecule. Metropolis Monte Carlo simulations with Materials Studio were conducted to estimate the adsorption behavior and configuration energies of the drug molecules on iron surfaces. The results show that chlorpromazine and amitriptyline demonstrate the strongest inhibition potential due to favorable electron donation and high molecular softness, while diazepam exhibits the least effectiveness due to its higher energy gap and lower adsorption tendencies. This research highlights the feasibility of using DFT and molecular simulations to predict corrosion inhibition behavior, which is especially valuable for screening drug molecules with dual functions — both therapeutic and protective — particularly in resource-limited settings. The computational approach presented offers a reliable framework for the theoretical evaluation of corrosion inhibitors prior to experimental validation.