Hydrogen generation and related energy applications heavily rely on the hydrogen evolution reaction (HER), which faces challenges of slow kinetics and high overpotential. Efficient electrocatalysts, particularly single-atom catalysts (SACs) on two-dimensional (2D) materials, are essential. This study presents a few-shot machine learning (ML) assisted high-throughput screening of 2D septuple-atomic-layer Ga2CoS4−x supported SACs to predict HER catalytic activity. Initially, density functional theory (DFT) calculations showed that 2D Ga2CoS4 is inactive for HER. However, defective Ga2CoS4−x (x = 0–0.25) monolayers exhibit excellent HER activity due to surface sulfur vacancies (SVs), with predicted overpotentials (0–60 mV) comparable to or lower than commercial Pt/C, which typically exhibits an overpotential of around 50 mV in the acidic electrolyte, when the concentration of surface SV is lower than 8.3%. SVs generate spin-polarized states near the Fermi level, making them effective HER sites. We demonstrate ML-accelerated HER overpotential predictions for all transition metal SACs on 2D Ga2CoS4−x. Using DFT data from 18 SACs, an ML model with high prediction accuracy and reduced computation time was developed. An intrinsic descriptor linking SAC atomic properties to HER overpotential was identified. This study thus provides a framework for screening SACs on 2D materials, enhancing catalyst design.@en

In this study, we explore the mechanisms underlying the exceptional intrinsic strength of face-centered cubic (FCC) Multi-Principal Element Alloys (MPEAs) using a multifaceted approach. Our methods integrate atomistic simulations, informed by both embedded-atom model and neural network potentials, with first-principles calculations, stochastic Peierls-Nabarro (PN) modeling, and symbolic machine learning. We identify a consistent, robust linear correlation between the strength of MPEAs and the standard deviation of the maximum stacking-fault restoring force (τ_max,sd) across various potentials. This finding is substantiated by comparing the experimental strengths of Cantor alloys’ subsystems and Ni_62.5V_37.5 against τ_max,sd values from high-throughput first-principle calculations. Our theoretical insights are derived from integrating the stochastic Peierls-Nabarro model with a shearable precipitation hardening framework, demonstrating that lattice distortion alone does not directly enhance intrinsic strength. Instead, τ_max,sd emerges as a critical determinant, capable of boosting the strength of MPEAs by up to tenfold. Our analysis reveals the critical role of the exponential form of the PN model in achieving substantial strength improvement by transforming the Gaussian-like distribution of τ_max into an exponential-like distribution of local Peierls stress. Additionally, using an advanced symbolic machine learning technique, the sure independence screening and sparsifying operator (SISSO) method, we derive interpretable relationships between MPEA strength, elastic properties, and τ_max statistics, offering new insights into the design and optimization of advanced MPEAs. These findings highlight that the nonlinear physics and atomic fluctuations characterizing MPEAs not only underpin their unconventional intrinsic strength but also contribute to other complex properties such as sluggish diffusion and cocktail effect.

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The technological landscape for industrial processes handling asphaltene is evolving at a rapid pace due to the increase in the extraction of heavy crude oil. The main underlying challenges in this regard are the flow assurance, the recovery of the spent solvent, and the sophisticated extractor setup required to develop the process to an industrial scale. The number of studies focused on the handling of the asphaltene at the atomic and molecular scales is growing enormously in order to identify new sustainable solvents for the effective extraction of asphaltene from heavy crude oil or oil-bearing sands. This Perspective focuses on the importance of density functional theory and molecular dynamics simulations to explore the broader range of asphaltene inhibitors, e.g., nanoparticles, ionic liquids, and deep eutectic solvents, to prevent asphaltene precipitation. We provide a concise overview of the major accomplishments, analyze the aspects that require attention, and highlight the path-breaking studies having a significant impact on the process of chemical enhanced oil recovery from heavy crude oil reservoirs primarily based on atomistic and molecular simulations.

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Non-polarizable force fields fail to accurately predict free energies of aqueous electrolytes without compromising the predictive ability for densities and transport properties. A new approach is presented in which (1) TIP4P/2005 water and scaled charge force fields are used to describe the interactions in the liquid phase and (2) an additional Effective Charge Surface (ECS) is used to compute free energies at zero additional computational expense. The ECS is obtained using a single temperature-independent charge scaling parameter per species. Thereby, the chemical potential of water and the free energies of hydration of various aqueous salts (e.g., NaCl and LiCl) are accurately described (deviations less than 5% from experiments), in sharp contrast to calculations where the ECS is omitted (deviations larger than 20%). This approach enables accurate predictions of free energies of aqueous electrolyte solutions using non-polarizable force fields, without compromising liquid-phase properties.@en

Efficiently designing lightweight alloys with combined high corrosion resistance and mechanical properties remains an enduring topic in materials engineering. Due to the inadequate accuracy of conventional stress-strain machine learning (ML) models caused by corrosion factors, a novel reinforcement self-learning ML algorithm combined with calculated features (accuracy R² >0.92) is developed. Based on the ML models, calculated work functions and mechanical moduli, a Computation Designed Corrosion-Resistant Al alloy is fabricated and verified. The performance (elongation reaches ∼30 %) is attributed to the H trapping Al-Sc-Cu phases (-1.44 eV H⁻¹) and Cu-modified η/η' precipitates inside the grain boundaries (GBs).

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Vapor-Liquid Equilibria (VLE) of hydrogen (H₂) and aqueous electrolyte (KOH and NaCl) solutions are central to numerous industrial applications such as alkaline electrolysis and underground hydrogen storage. Continuous fractional component Monte Carlo simulations are performed to compute the VLE of H₂ and aqueous electrolyte solutions at 298-423 K, 10-400 bar, 0-8 mol KOH/kg water, and 0-6 mol NaCl/kg water. The densities and activities of water in aqueous KOH and NaCl solutions are accurately modeled (within 2% deviation from experiments) using the non-polarizable Madrid-2019 Na⁺/Cl⁻ ion force fields for NaCl and the Madrid-Transport K⁺ and Delft Force Field of OH⁻ for KOH, combined with the TIP4P/2005 water force field. A free energy correction (independent of pressure, salt type, and salt molality) is applied to the computed infinite dilution excess chemical potentials of H₂ and water, resulting in accurate predictions (within 5% of experiments) for the solubilities of H₂ in water and the saturated vapor pressures of water for a temperature range of 298-363 K. The compositions of water and H₂ are computed using an iterative scheme from the liquid phase excess chemical potentials and densities, in which the gas phase fugacities are computed using the GERG-2008 equation of state. For the first time, the VLE of H₂ and aqueous KOH/NaCl systems are accurately captured with respect to experiments (i.e., for both the liquid and gas phase compositions) without compromising the liquid phase properties or performing any refitting of force fields.

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Two-dimensional (2D) Janus monolayers, distinguished by their intrinsic vertical electric fields, emerge as highly efficient and eco-friendly materials for advancing the field of hydrogen evolution reactions (HER). In this study, we explore, for the first time, the potential viability of the oxygenation phase of two-dimensional Janus transition metal dichalcogenides MoOX (X = S, Se, and Te) monolayers as an exceptionally efficient photocatalyst for hydrogen production. Based on first-principles computations, we demonstrate that all three monolayers exhibit semiconductor behavior, characterized by a band gap ranging from 0.66 to 1.55 eV. This narrow band gap renders the proposed materials highly efficient at absorbing light within the visible region. Excitingly, the introduction of an electrostatic potential difference ΔΦ has granted us the ability to surpass the conventional bandgap limit (E_g≥1.23). Consequently, all monolayers exhibit favorable band alignment with respect to the vacuum level. Moreover, the calculated solar-to-hydrogen efficiency for the envisaged monolayer exceeds the established theoretical limit. Particularly, the MoOTe monolayer emerges as an infrared-light-driven photocatalyst, demonstrating a remarkable solar-to-hydrogen efficiency limit of up to 25,21% when considering the entire solar spectrum. A thorough examination of the Gibbs free energy differences across these monolayers has revealed that the values during the oxygenation phase are significantly smaller and approach the optimum, in contrast to the parental two-dimensional Janus transition metal dichalcogenides. Our results conclusively establish that the proposed materials exhibit exceptional efficiency as photocatalysts for hydrogen evolution reactions. Notably, their efficacy is demonstrated even in the lack of co-catalysts or sacrificial agents.

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The introduction of pharmaceuticals into aquatic ecosystems can lead to the generation of antibiotic-resistant bacteria. This paper employed molecular dynamics simulations to examine the interactions between cationic/anionic surfactants and two antibiotics or drugs, namely, ciprofloxacin and azithromycin. The analysis focused on many factors to elucidate the mechanism by which the surfactant bilayer molecular structure affects the selected antibiotics. These factors include the tilt angle, rotational angle of the surfactants, electrostatic potential, and charge density along the bilayers. Our molecular-level investigation of the adsorption mechanisms of hydrophobic (azithromycin) and hydrophilic (ciprofloxacin) drugs on the cationic/anionic surfactant bilayer offers a crucial understanding for comprehending the optimal selection of surfactants for effectively separating antibiotics.

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Advanced (ultra)high-strength steels that utilise bcc-fcc microstructures are appealing solutions for producing a combination of high strength and deformability. However, they are also susceptible to hydrogen embrittlement (HE). As larger less stable retained austenite (RA) can impair mechanical performance, its size and morphology are critical factors for achieving and maintaining the desired properties. Here, we present a combined experimental–density functional theory (DFT) study on HE with medium-carbon direct-quenched and partitioned (DQ&P) martensitic steels with varying vol% and film-thickness of RA, showing significantly improved HE resistance as a function of bcc-enrichment and increasing RA film-thickness. DFT reveals low attraction of hydrogen in bcc-Fe with Al, implying a stronger push towards fcc. Furthermore, the solubility of hydrogen increases dramatically with the carbon-enrichment of fcc-Fe when hydrogen and carbon are second neighbours. The theoretical results explain the observed differences in hydrogen diffusion, trap density, and the consecutively lower HE in Al-DQ&P over Si-DQ&P. Our combined experimental and theoretical study thus highlights the important interplay of bcc and fcc phases and H-uptake within austenite-containing carbon steels.

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Rapid developments in the field of hydrogen energy have prompted the need for safe and efficient hydrogen transportation and storage. Steels form the backbone of the current energy infrastructure and thus offer a fast and cost-effective solution. Their excellent mechanical properties are attributed to the underlying microstructure which comprises of finely dispersed nano-precipitates. However, one major factor restricting their application is their susceptibility to Hydrogen Embrittlement (HE). In the past decade, experimental and theoretical works have been carried out to understand if the nano-sized carbides can aid in reducing the susceptibility to HE along with providing strengthening. Within this ab-inito study, we investigated the effectiveness of fully coherent nano-carbides (i.e. TiC, VC and NbC) to limit the diffusible hydrogen content in bcc Fe. Our study revealed that the interplay between hydrogen and carbon vacancies, local atomic environment at interface as well as elastic strain fields at the interface can lead to significantly increased hydrogen solubilities. While in TiC, the deepest traps were found to be in the bulk of carbides, in VC and NbC, the elastic strain fields around the interface led to the strongest trapping. Further, the formation of a two-hydrogen-vacancy complex was found to be favourable in VC. Finally, the migration barriers for hydrogen trapping in bulk TiC as well as across the Fe/TiC coherent interface indicate that these deep traps in the form of carbon vacancies are fairly accessible.

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This study aims to identify photo-/electrocatalysts that can enhance the oxygen evolution reaction (OER), hydrogen evolution reaction (HER), and oxygen reduction reaction (ORR), which are of utmost importance in electro-/photochemical energy systems, such as solar energy, fuel cells, water electrolyzers, or metal-air batteries. Our study focused on investigating the 2D Ge₂Se₂P₄ monolayer and found that it exhibits a bifunctional photocatalyst with a very high solar-to-hydrogen efficiency. The two-dimensional (2D) Ge₂Se₂P₄ monolayer has superior HER activity compared to that of most 2D materials, and it also outperforms the reference catalysts IrO₂(110) and Pt(111) in terms of low overpotential values for ORR and OER mechanisms. Such superior catalytic performance in the 2D Ge₂Se₂P₄ monolayer can be attributed to its electron states, charge transfer process, and suitable band alignments referring to normal hydrogen electrodes. Overall, the study suggests that the Ge₂Se₂P₄ monolayer could be an excellent bifunctional catalyst for advancing photo-/electrochemical energy systems.

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The ability of neat deep eutectic solvents (DESs) to influence protein structure and function has gained considerable interest due to the unstable nature of enzymes or therapeutic proteins, which are often exposed to thermal, chemical, or mechanical stresses when handled at an industrial scale. In this study, we simulated a model globular protein, lysozyme, in water and six choline chloride-based DES using molecular dynamics simulations, to investigate the structural changes in various solvent environments, giving insights into the overall stability of lysozyme. Root mean square deviation (RMSD) and root mean square fluctuations (RMSF) of the C-α backbone indicated that most DESs induced a less flexible and rigid lysozyme structure compared to water. The radius of gyration and end-to-end distance calculations pointed towards higher structural compactness in reline and levuline, while the structure of lysozyme considerably expanded in oxaline. Protein-solvent interactions were further analysed by hydrogen bonding interactions and radial distribution functions (RDF), which indicated a higher degree of lysozyme-hydrogen bond donor (HBD) interactions compared to lysozyme-choline hydrogen bonding. Surface area analysis revealed an overall % increase in total positive, negative, donor, and acceptor surface areas in malicine and oxaline compared to water and other DESs, indicating the exposure of a larger number of residues to interactions with the solvent. Reline, levuline, and polyol-based DESs comparatively stabilized lysozyme, even though changes in the secondary/tertiary structures were observed. Communicated by Ramaswamy H. Sarma.

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Through a density functional theory-driven survey, a comprehensive investigation of two-dimensional (2D) Janus aluminum-based monochalcogenides (Al₂XY with X/Y = S, Se, and Te) has been performed within this study. To begin with, it is established that the examined phase, in which the Al-atoms are located at the two inner planes while the (S, Se, and Te)-atoms occupy the two outer planes in the unit cell, are energetically, mechanically, dynamically, and thermally stable. To address the electronic and optical properties, the hybrid function HSE06 has been employed. It is at first revealed that all three monolayers display a semiconducting nature with an indirect band gap ranging from 1.82 to 2.79 eV with a refractive index greater than 1.5, which implies that they would be transparent materials. Furthermore, the monolayers feature strong absorption spectra of around 10⁵ cm⁻¹ within the visible and ultraviolet regions, suggesting their potential use in optoelectronic devices. Concerning the photocatalytic performance, the conduction band-edge positions straddle the hydrogen evolution reaction redox level. Also, it is observed that the computed Gibbs free energy is around 1.15 eV, which is lower and comparable to some recently reported 2D-based Janus monolayers. Additionally, the thermoelectric properties are further investigated and found to offer a large thermal power as well as a high figure of merit (ZT) around 1.03. The aforementioned results strongly suggest that the 2D Janus Al-based monochalcogenide exhibits suitable characteristics as a potential material for high-performance optoelectronic and thermoelectric applications.

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In this work, we computed electrical conductivities under ambient conditions of aqueous NaCl and KCl solutions by using the Einstein-Helfand equation. Common force fields (charge q = ±1 e) do not reproduce the experimental values of electrical conductivities, viscosities, and diffusion coefficients. Recently, we proposed the idea of using different charges to describe the potential energy surface (PES) and the dipole moment surface (DMS). In this work, we implement this concept. The equilibrium trajectories required to evaluate electrical conductivities (within linear response theory) were obtained by using scaled charges (with the value q = ±0.75 e) to describe the PES. The potential parameters were those of the Madrid-Transport force field, which accurately describe viscosities and diffusion coefficients of these ionic solutions. However, integer charges were used to compute the conductivities (thus describing the DMS). The basic idea is that although the scaled charge describes the ion-water interaction better, the integer charge reflects the value of the charge that is transported due to the electric field. The agreement obtained with experiments is excellent, as for the first time electrical conductivities (and the other transport properties) of NaCl and KCl electrolyte solutions are described with high accuracy for the whole concentration range up to their solubility limit. Finally, we propose an easy way to obtain a rough estimate of the actual electrical conductivity of the potential model under consideration using the approximate Nernst-Einstein equation, which neglects correlations between different ions.

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Deep eutectic solvents (DESs) are industrially promising solvents and posses numerous applications in wide areas such as metal processing, synthesis media, synthesis of nanoparticles, gas sequestration and many more. In this work, we synthesized and investigated the performance of three deep eutectic solvents (DESs) i.e., reline, glyceline and ethaline in the separation of pure asphaltene from organic solvents, i.e., toluene and n-heptane using experimental techniques and classical molecular dynamics (MD) simulations. The DESs are prepared and characterized by Fourier transform infrared (FTIR) spectroscopy and density meter analysis. The separation and aggregation of asphaltene from the organic solvent phase into the DES phase at various DES concentrations are visually observed using optical microscopy. MD simulations are used to probe the end-to-end distance and diffusion coefficient of the asphaltene molecules in DESs-organic solvent mixtures. Further, the trajectory density contours of asphaltene in three DESs-toluene/n-heptane systems are calculated to analyze asphaltene aggregation in the presence of the DESs. Our experimental-simulations synergistic study shows the superior performance of glyceline DES in toluene and reline DES in n-heptane for efficient separation of the asphaltene.

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Sodium borohydride (NaBH₄) has a high hydrogen (H₂ ) gravimetric capacity of 10.7 wt %. NaBH₄ releases H₂ through a hydrolysis reaction in which aqueous NaB(OH)₄ is formed as a byproduct. NaB(OH)₄ strongly influences the thermophysical properties of aqueous solutions (i.e., densities, viscosities, and electrical conductivities) and the hydrolysis reaction kinetics and conversion of NaBH₄. Here, molecular dynamics (MD) simulations are performed to compute viscosities, electrical conductivities, and self-diffusivities of H₂ , Na⁺, and B(OH)₄^- for a temperature and concentration range of 298-353 K and 0-5 mol NaB(OH)₄/kg water, respectively. Continuous fractional component Monte Carlo (CFCMC) simulations are used to compute the solubilities of H₂ and activities of water in aqueous NaB(OH)₄ solutions for the same temperature and concentration range. A new force field is developed (Delft force field of B(OH)₄^-: DFF/B(OH)₄^-) in which B(OH)₄^- is modeled as a tetrahedral structure with a scaled charge of −0.85. The OH group in B(OH)₄^- is modeled as a single interaction site. This force field is based on TIP4P/2005 water and the Madrid-2019 Na⁺ force field. The MD simulations can accurately capture the densities and viscosities within 2.5% deviation from available experimental data at 298 K up to a concentration of 5 mol NaB(OH)₄/kg water. The computed electrical conductivities deviate by ca. 10% from experimental data at 298 K for the same concentration range. Based on the molecular simulations results, engineering equations are developed for shear viscosities, self-diffusivities of H₂, Na⁺, and B(OH)₄^-, and solubilities of H₂, which can be used to design and model NaBH₄ hydrolysis reactors.

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A primary concern towards achieving a robust and sustainable water-splitting strategy consists in the development and designing of non-precious hydrogen evolution electrocatalysts capable of operating at relatively high current densities. In the present density functional theory (DFT) based study, we explored and identified α-NbB₂-based catalysts consisting of Borophene as graphene-like noble metal-free networks in Niobium-metal based networks, as promising catalysts for the hydrogen-evolution reaction (HER). Our results unveiled that Fe/Co covalent doping in α-NbB₂ {001} surface provides high-efficiency HER activity sites, namely, T_Nb-sites in Nb-terminated Fe/Co-NbB₂ {001} surface with the lowest ΔG_H^∗ Gibbs free energy value of about 0.264/0.278 eV, which further drops to a very optimal value in the range of ΔG_H^∗ ≤ ± 0.10 eV upon the implementation of an external electric field. Furthermore, it was also revealed that in contrast to the extensively used Pt-based surface catalysts, both α-NbB₂ and Fe/Co-NbB₂ catalysts can sustain consistently high catalytic activity for HER over a very large hydrogen coverage and thus ensure a large density of effective catalytic free sites.

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One of the major constituents of heavy oil is asphaltenes. They are responsible for numerous problems in petroleum downstream and upstream processes, such as catalyst deactivation in heavy oil processing and blocking pipes while transporting crude oil. Probing the efficiency of new nonhazardous solvents in separating asphaltenes from crude oil is key to avoid conventional volatile and hazardous solvents by replacing these conventional solvents with new ones. In this work, we have investigated the efficiency of ionic liquids to separate asphaltenes from organic solvents (such as toluene and hexane) using molecular dynamics simulations. Triethylammonium-dihydrogen-phosphate and triethylammonium acetate ionic liquids are considered in this work. Various structural and dynamical properties are calculated, such as radial distribution function, end-to-end distance, trajectory density contour, and diffusivity of asphaltene in the ionic liquid-organic solvent mixture. Our results explain the role of anions, i.e., dihydrogen-phosphate and acetate ions, in separating asphaltene from toluene and hexane. Our study provides an important revelation about the dominant role played by the IL anion in intermolecular interactions which depends on the type of solvent (i.e., toluene or hexane) in which the asphaltene is present. The anion induces enhanced aggregation in the asphaltene-hexane mixture compared to the asphaltene-toluene mixture. The molecular insights obtained within this study on the role played by ionic liquid anion in asphaltene separation are key for the preparation of new ionic liquids for asphaltene precipitation applications.

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Data for several key thermodynamic and transport properties needed for technologies using hydrogen (H₂), such as underground H₂ storage and H₂O electrolysis are scarce or completely missing. Force field-based Molecular Dynamics (MD) and Continuous Fractional Component Monte Carlo (CFCMC) simulations are carried out in this work to cover this gap. Extensive new data sets are provided for (a) interfacial tensions of H₂ gas in contact with aqueous NaCl solutions for temperatures of (298 to 523) K, pressures of (1 to 600) bar, and molalities of (0 to 6) mol NaCl/kg H₂O, (b) self-diffusivities of infinitely diluted H₂ in aqueous NaCl solutions for temperatures of (298 to 723) K, pressures of (1 to 1000) bar, and molalities of (0 to 6) mol NaCl/kg H₂O, and (c) solubilities of H₂ in aqueous NaCl solutions for temperatures of (298 to 363) K, pressures of (1 to 1000) bar, and molalities of (0 to 6) mol NaCl/kg H₂O. The force fields used are the TIP4P/2005 for H₂O, the Madrid-2019 and the Madrid-Transport for NaCl, and the Vrabec and Marx for H₂. Excellent agreement between the simulation results and available experimental data is found with average deviations lower than 10%.

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