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Checkpoint kinases 1 and 2 (CHK1 and CHK2) are enzymes that are involved in the control of DNA damage. At the present time, these enzymes are some of the most important targets in the fight against cancer since their inhibition produces cytotoxic effects in carcinogenic cells. This paper proposes the use of spirostans (Sp), natural compounds, as possible inhibitors of the enzymes CHK1 and CHK2 from an in silico analysis of a database of 155 molecules (S5). Bioinformatics studies of molecular docking were able to discriminate between 13 possible CHK1 inhibitors, 13 CHK2 inhibitors and 1 dual inhibitor for both enzymes. The administration, distribution, metabolism, excretion and toxicity (ADMETx) studies allowed a prediction of the distribution and metabolism of the potential inhibitors in the body, as well as determining the excretion routes and the appropriate administration route. The best inhibition candidates were discriminated by comparing the enzyme-substrate interactions from 2D diagrams and molecular docking. Specific inhibition candidates were obtained, in addition to studying the dual inhibitor candidate and observing their stability in dynamic molecular studies. In addition, Highest Occupied Molecular Orbital—Lowest Unoccupied Molecular Orbital (HOMO-LUMO) interactions were analyzed to study the stability of interactions between the selected enzymes and spirostans resulting in the predominant gaps from HOMOCHKs to LUMOSp (Highest Occupied Molecular Orbital of CHKs—Lowest Unoccupied Molecular Orbital of spirostan). In brief, this study presents the selection inhibitors of CHK1 and CHK2 as a potential treatment for cancer using a combination of molecular docking and dynamics, ADMETx predictons, and HOMO-LUMO calculation for selection. [ABSTRACT FROM AUTHOR]

This paper systematically investigates the structure, stability, and electronic properties of niobium carbide clusters, NbmCn (m = 5, 6; n = 1–7), using density functional theory. Nb5C2 and Nb5C6 possess higher dissociation energies and second-order difference energies, indicating that they have higher thermodynamic stability. Moreover, ab initio molecular dynamics (AIMD) simulations are used to demonstrate the thermal stability of these structures. The analysis of the density of states indicates that the molecular orbitals of NbmCn (m = 5, 6; n = 1–7) are primarily contributed by niobium atoms, with carbon atoms having a smaller contribution. The composition of the frontier molecular orbitals reveals that niobium atoms contribute approximately 73.1% to 99.8% to NbmCn clusters, while carbon atoms contribute about 0.2% to 26.9%. [ABSTRACT FROM AUTHOR]

Nitrogen-doped graphene has been increasingly utilized in a variety of energy-related applications, serving as a catalyst or support material for fuel cells, and as an anode material for lithium-ion batteries, among others. The thermal reduction of graphene oxide (GO) in nitrogenous sources to incorporate nitrogen, producing nitrogen-doped reduced graphene oxide (NRGO), is the most favored method. Controlling atomic configurations of nitrogen-doped sites is the key factor for tailoring the physico-chemical properties of NRGO, but major challenges remain in identifying detailed atomic arrangements at nitrogen binding sites on highly defective and chemically functionalized GO surfaces. In this paper, we present atomistic-scale modeling of the nitrogen doping process of GO with different types of vacancy defects. Molecular dynamics simulations using a reactive force field indicate that the edge carbon atoms on defect sites are the dominant initiation location for nitrogen doping. Further, first-principles calculations using density functional theory present energetically favorable chemical transition pathways for nitrogen doping. The significance of this work lies in providing important chemical insights for the effective control of the desired properties of NRGO by suggesting a detailed mechanism of the nitrogen doping process of GO. [ABSTRACT FROM AUTHOR]

Hydration and, in particular, the coordination number of a metal ion is of paramount importance as it defines many of its (bio)physicochemical properties. It is not only essential for understanding its behavior in aqueous solutions but also determines the metal ion reference state and its binding energy to (bio)molecules. In this paper, for divalent metal cations Ca 2 + , Cd 2 + , Cu 2 + , Fe 2 + , Hg 2 + , Mg 2 + , Ni 2 + , Pb 2 + , and Zn 2 + , we compare two approaches for predicting hydration numbers: (1) a mixed explicit/continuum DFT-D3//COSMO-RS solvation model and (2) density functional theory based ab initio molecular dynamics. The former approach is employed to calculate the Gibbs free energy change for the sequential hydration reactions, starting from [M( H 2 O)2]2+ aqua complexes to [M( H 2 O) 9]2+, allowing explicit water molecules to bind in the first or second coordination sphere and determining the most stable [M( H 2 O) n]2+ structure. In the latter approach, the hydration number is obtained by integrating the ion–water radial distribution function. With a couple of exceptions, the metal ion hydration numbers predicted by the two approaches are in mutual agreement, as well as in agreement with the experimental data. [ABSTRACT FROM AUTHOR]

To investigate the mechanism of aquatic pathogens in quorum sensing (QS) and decode the signal transmission of aquatic Gram-negative pathogens, this paper proposes a novel method for the intelligent matching identification of eight quorum signaling molecules (N-acyl-homoserine lactones, AHLs) with similar molecular structures, using terahertz (THz) spectroscopy combined with molecular dynamics simulation and spectral similarity calculation. The THz fingerprint absorption spectral peaks of the eight AHLs were identified, attributed, and resolved using the density functional theory (DFT) for molecular dynamics simulation. To reduce the computational complexity of matching recognition, spectra with high peak matching values with the target were preliminarily selected, based on the peak position features of AHL samples. A comprehensive similarity calculation (CSC) method using a weighted improved Jaccard similarity algorithm (IJS) and discrete Fréchet distance algorithm (DFD) is proposed to calculate the similarity between the selected spectra and the targets, as well as to return the matching result with the highest accuracy. The results show that all AHL molecular types can be correctly identified, and the average quantization accuracy of CSC is 98.48%. This study provides a theoretical and data-supported foundation for the identification of AHLs, based on THz spectroscopy, and offers a new method for the high-throughput and automatic identification of AHLs. [ABSTRACT FROM AUTHOR]

Diabetes, a chronic metabolic disease, has become a severe health problem worldwide. According to the latest data from the International Diabetes Federation (IDF), there were 537 million diabetic mellitus (DM) patients worldwide in 2021, expected to increase to 783 million by 2045. Over 90% of people with diabetes have type 2 diabetes, which is driven by socio-economic, demographic, environmental, and genetic factors. Diabetes is still a major global health issue, with prevalence rates rising all across the world. This not only imposes a significant burden on healthcare systems but also impacts the quality of life of affected individuals and their families. Therefore, there is a continuous high demand worldwide to develop novel, more effective, and easily affordable medications against diabetes. This paper illustrates the in-vitro antidiabetic activity and probable binding mechanism prediction of phytoconstituents of Allamanda cathartica against type 2 diabetes molecular targets. Through the application of bioactivity score prediction, molecular docking, and ADMET prediction approach, the potential and selective phytoconstituents with the highest binding affinity and lower toxicity were gained from the curated datasets. Further molecular dynamics simulations and DFT calculations were carried out to identify the favorable binding conformations when the top-scored phytoconstituents bind with the PPAR γ receptors compared to the rosiglitazone. Compound AC2 interacts with the PPAR γ proteins by forming seven hydrogen bonds with the amino acid residues Phe282, His449, Tyr327, His323, and Ser289. The ligand was bound to the protein during the simulation since none of the complex conformations was unstable, and no unfolding or folding occurred. Our results provided an approach to further design and optimize the natural product-inspired small druglike molecules as potential antidiabetic agents. This study highlighted that the phytoconstituents of Allamanda cathartica have antidiabetic potential through the binding of PPAR γ , α -amylase and α -glucosidase proteins that can be further explored for novel antidiabetic drug development. The ethyl acetate extract of A. cathartica displayed significant α -amylase inhibition compared to other fractions, reaching its peak inhibition at a concentration of 4 mg/mL. The organic extract prominently inhibited the enzyme α -glucosidase compared to other fractions, with maximal inhibition observed at a concentration of 4 mg/mL. Phytoconstituents of Allamanda cathartica have shown antidiabetic potential through the binding of PPAR γ , α -amylase, GLP-1 and α -glucosidase proteins Compound AC2 (1-deoxy-d-mannitol) interacts with the PPAR γ proteins through the formation of 7 hydrogen bonds with the residues Phe282, His449, Tyr327, His323 and Ser289, while compound AC31 (Phytol) forms two hydrogen bonds with His323 and Tyr473 amino acid residues. Compounds AC28 (Octanoic acid) show a better binding affinity for GLP-1 target protein. Compounds AC34 (Quercetin) and AC23 (Kaempferol) show excellent binding affinity for α -amylase and α -glucosidase enzymes. [ABSTRACT FROM AUTHOR]

In pursuit of environmentally friendly and effective photocatalytic materials for water splitting, this research paper presents a thorough evaluation of WSi 2 N 4 , WGe 2 N 4 , and their Janus counterpart WSiGeN 4 monolayers through the application of Density Functional Theory. The study elucidates the optical, electronic, and structural characteristics of these monolayers, thereby demonstrating their potential as highly favorable contenders for applications involving photocatalytic water splitting. By means of comprehensive optimization and analysis, it is shown that these monolayers possess advantageous characteristics, such as favorable band gaps, stable work functions, and stability over a broad pH range. These attributes are of utmost importance in ensuring the effectiveness of hydrogen evolution reaction (HER). The inclusion of Janus WSiGeN 4 , which possesses an intrinsic mirror asymmetry, significantly improves the photocatalytic efficacy of the material. This is achieved by meeting the demands of optimal redox reaction levels in both the conduction and valence bands. In conjunction with machine learning force fields, ab initio molecular dynamics (AIMD) simulations validate the thermal stability of these monolayers at 300 K. In addition, our analysis of the optical properties reveals substantial absorption in the visible spectrum - vital for photocatalytic applications powered by solar energy. In summary, the research highlights the potential of Janus WSiGeN 4 , WGe 2 N 4 , and WSi 2 N 4 monolayers as multifunctional and effective substances for forthcoming photocatalytic water-splitting systems. This advancement indicates of a significant stride in the direction of sustainable energy solution development. • Analyzed WSi 2 N 4 , WGe 2 N 4 , and WSiGeN 4 for effective hydrogen production. • Proved thermal stability at 300 K, enabling real-world use. • Highlighted Janus WSiGeN 4 's superior efficiency for photocatalysis. • Confirmed stability via machine learning, promising for sustainable technology. • Noted significant visible light absorption for solar-driven applications. [ABSTRACT FROM AUTHOR]

Aiming at the problem that coal gasification fine slag is difficult to float effectively, this paper combines flotation experiments and molecular simulation methods to study the mechanism of composite collectors on the flotation performance of gasification fine slag. In the aspect of molecular simulation, the quantum chemical characteristics of collector molecules and coal molecules in gasification fine slag were studied by density functional theory (DFT) calculation, and the electrostatic potential and frontier orbitals were calculated. Then, the flotation behavior of composite collectors in gasification fine slag was simulated by molecular dynamics. It was found that dodecane and dodecylamine had the best flotation effect as collectors. Finally, the flotation experiment verified that the recovery rate and other related indexes of gasification fine slag were better when dodecane and dodecylamine were used as collectors. [ABSTRACT FROM AUTHOR]

Density functional theory (DFT) calculations were carried out to investigate the absorption spectra and photoelectric properties of new metal-free dyes integrating an acene group positioned proximal to the donor moiety, exemplified by the 2-amino pyrrole. A linear carbon chain (LCC) with varying lengths serves as the link between the donor group and two distinct electron-attracting groups: cyanoacrylate and a derivative of pyridinium salt. Molecular orbital analysis reveals strategically positioned energy levels for efficient electron recovery, ensuring favorable thermodynamics for injection. UV-VIS absorption properties underscore superior outcomes for dyes with longer π–spacers, particularly those with pentacene showcase a panchromatic effect extending beyond 920 nm. Furthermore, the study explores the electron transfer process at the dye–semiconductor interface, emphasizing stable adsorption modes and favorable interactions. Photovoltaic property estimations, considering electron injection and recombination rates, indicate that dyes with pyridinium salt as the withdrawing group, specifically, P-Pen-4-A2 and P-Ant-4-A2, exhibit excellent values for both open-circuit voltage (Voc) and short-circuit photocurrent density (Jsc), thus demonstrating superior photovoltaic outcomes. The investigation of J–V curves predicts outstanding photoelectric conversion efficiency values of 29.72% and 27.90% for these dyes. Moreover, derivatives incorporating cyanoacrylate yields commendable PCE values of 20.30% and 25.01% for P-Ant-4-A2 and P-Pen-4-A2. Classical molecular dynamics simulations (MD) demonstrate that, over the course of 200 ns simulation time, the dyes maintain a vertical adsorption configuration. These results underscore the potential of the designed dyes for both standalone and co-sensitizing applications, presenting a promising avenue for the development of efficient and panchromatic DSSCs. [ABSTRACT FROM AUTHOR]

The investigation of the compounding mechanisms of mixed collectors in low-rank coal flotation has gradually progressed from a macro to a micro level, and the accuracy of research outcomes significantly depends on the development of micro models. While All-Atom Molecular Dynamics (AAMD) simulations have been used for this purpose, the employment of an excessive amount of collector in the system leads to a failure in replicating the actual flotation process, which in turn, limits the practical applicability of research findings. To overcome this drawback, this paper suggests using the MARTINI Coarse-Grained force field (CGFF), developed by the S.J.Marrink group, to construct a simulation system that accurately mimics the amount of collector employed in practical flotation processes. In light of this, to make the MARTINI force field more applicable for research in the low-rank coal field, we employ density functional theory (DFT) and coarse-grained molecular dynamics (CGMD) methods to investigate water cluster interactions, identify magic number clusters, and fit the corresponding CGFF parameters to develop a CG water model suitable for exploring the compounding mechanism of mixed collectors. This research lays the groundwork for future investigations into the aggregation behavior of mixed collectors under actual usage conditions, as well as their synergistic adsorption at the coal/water interface. [ABSTRACT FROM AUTHOR]

The dynamics of an inertial confinement fusion capsule, or of a stellar or planet interior, obey a very similar set of equations: magneto-radiative-hydrodynamic equations. The solutions of these equations, however, depend entirely on the transport properties associated with the different materials at play. To properly model the dynamics of these systems, it is necessary to determine with high accuracy the transport coefficients of several materials over a large range of thermodynamic conditions. Experimental capabilities in this respect are still limited due to the nature of the microphysics at play and the extreme conditions involved. Numerical simulations are thus necessary, and in this respect, molecular dynamics simulations based on density functional theory offer exquisite possibilities to constrain the transport properties in the warm to hot dense matter regime. In this paper, we report the methodology used to extract different transport properties based on molecular dynamics performed with the software Abinit. The examples shown are based on the specific cases identified for the purpose of the second charged-particle transport code comparison workshop. [ABSTRACT FROM AUTHOR]

Because of their unique physicochemical integration mode, energetic host–guest solvates provide a balanced method to expand CL-20 high explosives. CL-20/hydrogen peroxide (H2O2) energetic solvates maintain their detonation performance by combining H2O2 molecules into a lattice akin to hydrate CL-20/H2O solvate (α-CL-20). Herein, using periodic density functional theory (DFT) calculation and molecular dynamics simulation, the structural evolution and intermolecular interaction mechanism of orthorhombic CL-20/H2O2 (o-CL-20/H2O2), monoclinic CL-20/H2O2 (m-CL-20/H2O2) and CL-20/H2O solvates were monitored by the vibrational spectrum and vibrational density of states (VDOS) in the THz region when the temperature was increased from 298 K to 558 K. There was greater similarity in the vibrational characteristics of THz spectra for o-CL-20/H2O2 and CL-20/H2O solvates that was supported by the thermal expansion anisotropy of lattice parameters and that of difference for the m-CL-20/H2O2 solvate. With increased temperature, spectral signals in the power spectrum of VDOS reflected the conformational evolution of CL-20 molecules in o-CL-20/H2O2 solvate and structural insensitivity of m-CL-20/H2O2 solvate. THz peaks of CL-20/H2O revealed the weakening of intermolecular interactions of CL-20 and H2O molecules, which were in agreement with the fact that H2O molecules more easily escape from host–guest solvates, whereas the H2O2 molecule was restricted in a cage of CL-20 molecules for the m-CL-20/H2O2 solvate. RDF and hydrogen bond (H-bond) interaction analyses were performed to further clarify stronger intermolecular H-bond interactions in the o-CL-20/H2O2 solvate as compared to that of the other two combined with H2O2 or H2O solvates. This finding introduces new insights into clarifying the formation mechanism of hydroxide with CL-20-based energetic host–guest solvates. [ABSTRACT FROM AUTHOR]

Three chitosan ionic liquid type Schiff bases (CS-IL-SBs) were synthesized by grafting three aldehydes (vanillin, cinnamaldehyde, and pyridine-4-carboxaldehyde) on CS-IL (chitosan grafted with p-toluene sulfonic acid) through a Schiff base reaction. Thermogravimetric analysis indicated that the thermal stability of CS was enhanced by the modification of IL and Schiff base groups. All CS-IL-SBs present a non-crystalline structure as analyzed using X-ray diffraction technique and have a positively charged surface in solution for improved dispersion stability as analyzed using zeta potential testing. A corrosion inhibition performance investigation using electrochemical and mass loss methods was undertaken, which were supported with surface analysis and computational studies. All the CS-IL-SBs act as effective corrosion inhibitors obeying Langmuir adsorption isotherm containing both chemisorption and physisorption for N80 steel in 15% HCl solution. Among them, CS-IL-Vin (grafted by vanillin) exhibits a maximum inhibition efficiency of 83.66% at 400 mg L−1. The analysis of the corroded metal surface via scanning electron microscopy depicts a considerably smooth morphology in the presence of adsorbed CS-IL-SBs. Contact angle tests indicated that the water-repellent ability of the metal surface was increased by the addition of CS-IL-SBs. Density functional theory calculations indicated that the active regions of CS-IL-SBs are mainly distributed in –SO3−, benzene rings, and Schiff base groups. Molecular dynamics simulations show that CS-IL-SBs are parallelly adsorbed on the metal surface to form a stable protective film. CS-IL-Vin shows the best performance among the three CS-IL-SBs, which was selected to be compounded with aided inhibitors with different electrical properties. When CS-IL-Vin was compounded with negatively charged 3-carboxybenzene sulfonate in a ratio of 1 : 3, corrosion inhibition efficiency was the highest, reaching 93.45%. [ABSTRACT FROM AUTHOR]

Corannulenes have received much interest due to their electronic properties, which differ between the convex and concave surfaces of the molecule. The ability to control the shapes of corannulenes to optimize charge distribution is therefore important for the development of seminconductors and electronic devices. In this paper, the interactions of corannulenes are modeled inside carbon nanotubes of various sizes using the Lennard–Jones potential and a continuum approach. The major contribution of this work is the analytical expressions for the interaction energy, which are obtained as a function of the nanotube's radius, the offset distance of corannulene from the tube's axis and the orientation of corannulene. Minimizing this energy, the range of nanotube's radii that allow the corannulene to adopt lying, tilting and standing configurations both on‐ and off‐axis of the nanotubes is determined. These results are supported by the density functional theory calculations and agree with previously published work using molecular dynamics simulations for corannulenes located on the nanotube's axis. [ABSTRACT FROM AUTHOR]

[Display omitted] • The paper introduces a novel two-dimensional inorganic inorganic graphenylene based on indium nitride (IGP-InN). • The material demonstrates dynamic and thermal stability at elevated temperatures (700 K) and exhibits competitive cohesive energy compared to its hexagonal InN counterpart. • An indirect band gap transition with energy (E gap) of 2.49 eV was noted, making IGP-InN suitable for optoelectronic applications in the UV visible. • An accentuated decrease in the E gap can be noted for tensile strains, with a variation of 1.19 eV. • A transition to a planar structure at tensile strains higher than 4% was observed, and a new symmetry (P 6/ m) was found. This paper reveals the structural, electronic and mechanical properties of a novel inorganic graphenylene based on indium nitride (IGP-InN). The IGP-InN was characterized via density functional theory (DFT) simulations. The phonon dispersion shows the dynamic stability of IGP-InN, and molecular dynamics simulations confirm its thermal stability up to 700 K. Besides the electronic properties, the indirect band gap transition with energy (E gap) of 2.49 eV makes IGP-InN suitable for optoelectronic applications under UV–visible. Also, the E gap tunability with mechanical strain was analyzed, with a decrease of 1.19 eV in the E gap for tensile strains. The structural buckling plays an important role, with a transition to a planar structure for tensile strains. This work reveals a new class of 2D materials, buckled inorganic graphenylenes, and provides valuable insights into designing and optimizing graphenylene-like materials. [ABSTRACT FROM AUTHOR]

[Display omitted] • A NF/Mn 2 CoO 4 @MoO 2 electrode was prepared for Pb2+-targeted removal via CDI technology. • SCR of the electrode relies on preferential adsorption and sluggish desorption for Pb2+. • Synergistic effects of Mn 2 CoO 4 and MoO 2 are beneficial for Pb2+ capacitive removal. • Theoretical calculations confirm SCR is due to stronger bonding between Pb2+ and MoO 2. • Electrodepositing loaded MoO 2 onto NF/Mn 2 CoO 4 for 60 min achieved optimum capacitance. To achieve targeted removal of Pb2+ from industrial wastewater, a NF/Mn 2 CoO 4 @MoO 2 composite electrode, synthesised using the hydrothermal method combined with electrodeposition technology, was employed to construct an asymmetric capacitive deionization (CDI) system to selectively electro-adsorb and desorb Pb2+ ions. The electrode exhibited pseudocapacitive characteristics in solutions containing Pb2+, facilitating rapid and reversible redox reactions. The asymmetric CDI system, utilising graphite paper as the positive electrode and NF/Mn 2 CoO 4 @MoO 2 as the negative electrode, displayed exceptional adsorption performance at 1.4 V for 1 h, decreasing the Pb2+ concentration from 50 ppm to 4 ppb, achieving an adsorption capacity of 156.24 mg g−1, and displaying outstanding cyclic stability. Moreover, the electrode demonstrated preferential adsorption of Pb2+ in mixed solutions containing multiple heavy metal ions, with relative removal coefficients of 4.48 − 19.86 compared with other ions. Analysis of the adsorption mechanism indicated that during the adsorption process, Pb2+ was embedded between MoO 2 layers, disrupting the electron cloud symmetry and triggering an oxidation reaction. Octahedral MoO 2 then lost electrons and transformed into tetrahedral [MoO 4 ]2-, forming PbMoO 4 with embedded Pb2+ between the layers, and achieving effective removal of Pb2+ with high selectivity. Molecular dynamics simulations and density functional theory (DFT) calculations confirmed the high selectivity of the prepared electrode for Pb2+ ions based on stronger binding of Pb2+ to MoO 2 than other ions. The electrode has application potential for the capacitive removal of Pb2+ from industrial effluent through CDI technology. [ABSTRACT FROM AUTHOR]

[Display omitted] • The machine-learned potential for aluminum was developed as based on Behler-Parrinello neural network scheme. • The potential demonstrates an excellent agreement with experimental data and DFT calculations concerning thermodynamic, elastic, liquid phase and generalized stacking fault energy properties. • High accuracy was achieved due to the optimal training set and configuration parameters used to generate the machine learning potential. Aluminum and its alloys are most often used as structural materials due to their specific properties, such as low weight, low energy consumption for remelting and the possibility of almost complete processing. This paper utilizes machine learning, specifically the Behler-Parrinello neural network scheme, to develop a powerful potential for studying the underlying mechanisms of deformation, fracture, and defect formation. By surpassing the limitations of first principles calculations, the application of machine-learned potentials (MLP) becomes highly advantageous for describing pure aluminum (Al) in its solid and liquid phases. Specifically, from the generated potential equilibrium, thermodynamic, elastic, and vibrational properties of face-centered cubic (fcc) Al are obtained in very good agreement especially with density functional theory (DFT) results as well as with previous calculations using existing semi-empirical potentials, such as EAM and MEAM, recent machine-learned potentials, and experimental data. Furthermore, our potential proves to accurately reproduce defect formation energies such as previously computed and measured stacking-fault energy curves. Finally, stacking fault profiles as well as key quantities of the liquid phase such as the melting point at ambient pressure, temperature-dependent densities, and radial distribution functions are also calculated in very good agreement with the results from previous theoretical and experimental investigations. Nevertheless, our investigation goes beyond previous studies in proving excellent agreement with experimental data especially of the specific heat and the melting point at very high pressures. The competitive analysis performed in this work thus clearly demonstrates the validity and accuracy of the generated machine-learned potential to describe a wide range of properties of Al at various temperatures and pressures and thereby lays ground for future applications. [ABSTRACT FROM AUTHOR]

Method(s) that can reliably predict phase evolution across thermodynamic parameter space, especially in complex systems, are of critical significance in academia as well as in the manufacturing industry. In the present work, the phase stability in an equimolar AlCuFeMn multi-principal-component alloy (MPCA) was predicted using complementary first-principles density functional theory calculations and ab initio molecular dynamics (AIMD) simulations. The temperature evolution of completely disordered, partially ordered, and completely ordered phases was examined based on the Gibbs free energy. Configurational, electronic, vibrational, and lattice mismatch entropies were considered to compute the Gibbs free energy of the competing phases. Additionally, elemental segregation was studied using AIMD. The predicted results at 300 K align well with room-temperature experimental observations using x-ray diffraction and scanning and transmission electron microscopy on a sample prepared using commercially available pure elements. The adopted method could help in predicting plausible phases in other MPCA systems with complex phase stability. [ABSTRACT FROM AUTHOR]

Construction resting on soil and rocks containing montmorillonite (MMT) are prone to damage induced by swelling, which involves a significant release of energy. It is often desirable to enhance these soils to mitigate swelling potential, regulate volume changes, and manage energy release. Experimental findings suggest that increasing temperature is one method to improve these soils, with water content, initial volume, and boundary conditions also influencing the swelling mechanism. This study utilizes ab initio molecular dynamics calculations to explore changes in volume and energy within MMT unit cells at the nanoscale due to temperature variations. The response of unit cells of MMT with varying dimensions and quantities of water molecules to temperature is assessed under constrained and unconstrained conditions. Results indicate that the volume changes and energy release of unit cells in response to temperature are contingent upon the presence of water molecules. In unit cells containing water molecules, both energy and volume decrease with rising temperature, whereas in unit cells devoid of water molecules, energy decreases while volume increases as temperature rises. Given the inherent association of soils with water in natural settings, it can be deduced that increasing temperature presents a viable method for enhancing naturally occurring MMT-dominated soils. Density functional theory calculations demonstrate that alterations in the volume and energy of MMT stem from shifts in interactions among the minerals, cations, and water molecules, as well as intrinsic structural defects like isomorphic substitution and peroxy links within the unit cells. These modifications induce variations in charge carriers and electrical properties, consequently influencing volume and energy changes within MMT unit cells. Additionally, it was observed that the failure of peroxy links can significantly impact the optimal temperature selection for the thermal enhancement of MMT. [ABSTRACT FROM AUTHOR]

Transition metal dichalcogenides (TMDCs) are among the most exciting materials in nano-size particles. In this study, MX2 (M = Mo and W; X = S, Se, and Te) nanotubes and monolayers were evaluated to show the structural, mechanical, and electronic properties. The results showed that the stability of MX2 monolayers changes similarly to nanotubes with the sequence of MS2 > MSe2 > MTe2 (M = Mo and W). Besides, MX2 nanotubes and monolayers are semiconductors, and the band gap energy increases with a similar sequence with stability properties. The structural stability and band gap energy of WX2 structures are more than MoX2 structures. Young's modulus of nanotubes was studied with density functional theory (DFT) and molecular dynamics (MD) simulations with Stillinger-Weber (SW) potential methods. The results are similar to the formation and band gap energy showing that Young's modulus of the MX2 structures is in order of MS2 > MSe2 > MTe2 (M = Mo and W) and WX2 > MoX2 (X = S, Se or Te). Structural defects in monolayers, which were M-vacancy (VM), X2-vacancy (VX2), M-X2-vacancy (VM-X2), and M-X4-vacancy (VM-X4), were studied and it showed that the mechanical properties could be decreased. However, the defects do not affect electronic properties. [ABSTRACT FROM AUTHOR]

The stability of hybrid organic–inorganic halide perovskite semiconductors remains a significant obstacle to their application in photovoltaics. To this end, the use of low‐dimensional (LD) perovskites, which incorporate hydrophobic organic moieties, provides an effective strategy to improve their stability, yet often at the expense of their performance. To address this limitation, supramolecular engineering of noncovalent interactions between organic and inorganic components has shown potential by relying on hydrogen bonding and conventional van der Waals interactions. Here, the capacity to access novel LD perovskite structures that uniquely assemble through unorthodox S‐mediated interactions is explored by incorporating benzothiadiazole‐based moieties. The formation of S‐mediated LD structures is demonstrated, including one‐dimensional (1D) and layered two‐dimensional (2D) perovskite phases assembled via chalcogen bonding and S–π interactions. This involved a combination of techniques, such as single crystal and thin film X‐ray diffraction, as well as solid‐state NMR spectroscopy, complemented by molecular dynamics simulations, density functional theory calculations, and optoelectronic characterization, revealing superior conductivities of S‐mediated LD perovskites. The resulting materials are applied in n‐i‐p and p‐i‐n perovskite solar cells, demonstrating enhancements in performance and operational stability that reveal a versatile supramolecular strategy in photovoltaics. [ABSTRACT FROM AUTHOR]

Since the first report of ferroelectricity in nanoscale HfO2-based thin films in 2011, this silicon-compatible binary oxide has quickly garnered intense interest in academia and industry, and continues to do so. Despite its deceivingly simple chemical composition, the ferroelectric physics supported by HfO2 is remarkably complex, arguably rivaling that of perovskite ferroelectrics. Computational investigations, especially those utilizing first-principles density functional theory (DFT), have significantly advanced our understanding of the nature of ferroelectricity in these thin films. In this review, we provide an in-depth discussion of the computational efforts to understand ferroelectric hafnia, comparing various metastable polar phases and examining the critical factors necessary for their stabilization. The intricate nature of HfO2 is intimately related to the complex interplay among diverse structural polymorphs, dopants and their charge-compensating oxygen vacancies, and unconventional switching mechanisms of domains and domain walls, which can sometimes yield conflicting theoretical predictions and theoretical-experimental discrepancies. We also discuss opportunities enabled by machine-learning-assisted molecular dynamics and phase-field simulations to go beyond DFT modeling, probing the dynamical properties of ferroelectric HfO2 and tackling pressing issues such as high coercive fields. [ABSTRACT FROM AUTHOR]

Silicon-based two-dimensional (2D) materials have garnered significant attention due to their unique properties and potential applications in electronics, optoelectronics, and other advanced technologies. Here, we present a comprehensive investigation of a novel silicon allotrope, Popsilicene (Pop-Si), derived from the structure of Popgraphene. Using density functional theory and ab initio molecular dynamics simulations, we explore the thermal stability, mechanical and electronic properties, and optical characteristics of Pop-Si. Our results demonstrate that Pop-Si exhibits good thermal stability at 1000 K. Electronic structure calculations reveal that Pop-Si is metallic, with a high density of states at the Fermi level. Furthermore, our analysis of the optical properties indicates that Pop-Si has pronounced UV–Vis optical activity, making it a promising candidate for optoelectronic devices. Mechanical property assessments show that Pop-Si has Young's modulus ranging from 10 to 92 GPa and a Poisson's ratio of 0.95. These results combined suggest its potential for practical applications. [ABSTRACT FROM AUTHOR]

Extensive ab initio density functional theory molecular dynamics calculations were used to evaluate stability conditions for relevant phases of InN. In particular, the p-T conditions of the thermal decomposition of InN and pressure-induced wurtzite–rocksalt solid–solid phase transition were established. The comparison of the simulation results with the available experimental data allowed for a critical evaluation of the capabilities and limitations of the proposed simulation method. It is shown that ab initio molecular dynamics can be used as an efficient tool for simulations of phase transformations of InN, including solid–solid structural transition and thermal decomposition with formation of N2 molecules. It is of high interest, because InN is an important component of epitaxial quantum structures, but it has not been obtained as a bulk single crystal. This makes it difficult to determine its basic physical properties to develop new applications. [ABSTRACT FROM AUTHOR]

This work presents the studies of a very strong hydrogen bond (VSHB) in biologically active phthalic acids. Research on VSHB comes topical due to its participation in many biological processes. The studies cover the modelling of intermolecular interactions and phthalic acids with 2,4,6-collidine and N,N-dimethyl-4-pyridinamine complexes with aim to obtain a VSHB. The four synthesized complexes were studied by experimental X-ray, IR, and Raman methods, as well as theoretical Car–Parrinello Molecular Dynamics (CP-MD) and Density Functional Theory (DFT) simulations. By variation of the steric repulsion and basicity of the complex' components, a very short intramolecular hydrogen bond was achieved. The potential energy curves calculated by the DFT method were characterized by a low barrier (0.7 and 0.9 kcal/mol) on proton transfer in the OHN intermolecular hydrogen bond for 3-nitrophthalic acid with either 2,4,6-collidine or N,N-dimethyl-4-pyridinamine cocrystals. Moreover, the CP-MD simulations exposed very strong bridging proton dynamics in the intermolecular hydrogen bonds. The accomplished crystallographic and spectroscopic studies indicate that the OHO intramolecular hydrogen bond in 4-nitrophthalic cocrystals is VSHB. The influence of a strong steric effect on the geometry of the studied cocrystals and the stretching vibration bands of the carboxyl and carboxylate groups was elaborated. [ABSTRACT FROM AUTHOR]

The corrosion-inhibiting effect of vanillin molecule (VAN) and its protonated ( VANH + ) and deprotonated ( VAND - ) forms was investigated to evaluate the relationship between molecule structures and their associated efficiencies using density functional theory (DFT). The primary objective is to establish a comprehensive understanding of the relationship between molecular structures and their corrosion-inhibiting efficiencies. Global and local reactivity descriptors based on conceptual density functional theory (DFT), including the highest occupied molecular orbital energy (EHOMO), the lowest unoccupied molecular orbital energy (ELUMO), energy gap (ΔEgap), global hardness (η), global softness (σ), global electrophilicity (ω), electro-donating power ( ω - ), electro-accepting power ( ω + ), and Hirshfeld Fukui indices, have been investigated. The central aim of the present study is to elucidate the adsorption mechanism and provide a clear understanding of how these inhibitors interact with the Al(111) surface under different conditions. Molecular dynamics simulations in solid-state physics were employed to explore the adsorption mechanism of inhibitors in their neutral, protonated, and deprotonated species onto the Al(111) surface. The predicted adsorption suggests that the studied inhibitors for both parallel and perpendicular orientations decrease in the order VAND - > VAN > VANH + . The VAN molecule can adsorb on the Al(111) surface in various orientations, both parallel and perpendicular, as well as using different sides of the molecule. The parallel adsorption of VAN and VAND - inhibitors on the Al(111) surface occurs primarily due to the creation of an Al‒O bond, while the VANH + form adheres to the Al(111) surface through the formation of an Al‒C bond. Furthermore, the adsorption of the neutral VAN on the Al(111) surface is not only via the oxygen atom but also through the carbon C7 atom of the carbonyl group. [ABSTRACT FROM AUTHOR]

Finding alloys with specific design properties is challenging due to the large number of possible compositions and the complex interactions between elements. This study introduces a multi-objective Bayesian optimization approach guiding molecular dynamics simulations for discovering high-performance refractory alloys with both targeted intrinsic static thermomechanical properties and also deformation mechanisms occurring during dynamic loading. The objective functions are aiming for excellent thermomechanical stability via a high bulk modulus, a low thermal expansion, a high heat capacity, and for a resilient deformation mechanism maximizing the retention of the BCC phase after shock loading. Contrasting two optimization procedures, we show that the Pareto-optimal solutions are confined to a small performance space when the property objectives display a cooperative relationship. Conversely, the Pareto front is much broader in the performance space when these properties have antagonistic relationships. Density functional theory simulations validate these findings and unveil underlying atomic-bond changes driving property improvements. [ABSTRACT FROM AUTHOR]

The study was designed to explore the corrosion prevention capabilities of Citrullus colocynthis seeds alkaloid-rich extract (CSEA) on MS in a 1 M HCl environment by use of electrochemical and theoretical methods. Notably, Electrochemical Impedance Spectroscopy (EIS) and potentiodynamic polarization were used to probe the impact of immersion time and temperature. Energy-dispersive X-ray spectroscopy (EDX) and spanning electron microscopy (SEM) were used to confirm the presence of a protective layer on the substrate surface. Density functional theory (DFT) method was used to optimize the investigated species by use of B3LYP/6–31 + G(d, p) level of theory. The global and local quantum chemical reactivity descriptors were calculated to explore the inhibition corrosion efficiency and to identify the most favorable sites for electrophilic and nucleophilic attacks. Monte Carlo (MC) and molecular dynamics simulation (MDS) methods were used to study the interactions between corrosion inhibitor and metal surface. Noteworthy, results showed that CSEA exhibited an impressive inhibition efficiency, which reached 94.3% with a concentration of 2 g/L at 298 K. Potentiodynamic polarization revealed that the extract acted as a mixed-type inhibitor. Nyquist graphs showed that charge-transfer resistance and dæouble-layer capacitance both rised with increasing CSEA concentration, suggesting better inhibition efficiency. Notably, the Langmuir adsorption isotherm is well-aligned with the adsorption of inhibitor compounds. Importantly, all aforementioned theoretical methods were in agreement with the experimental findings. The outcome of the present work supported using Citrullus colocynthis seeds alkaloid-rich extract as ecofriendly agents to prevent corrosion. [ABSTRACT FROM AUTHOR]

Hydrogen storage materials play a pivotal role in the development of a sustainable hydrogen economy. However, the discovery and optimization of high-performance storage materials remain a significant challenge due to the complex interplay of structural, thermodynamic and kinetic factors. Computational materials science has emerged as a powerful tool to accelerate the design and development of novel hydrogen storage materials by providing atomic-level insights into the storage mechanisms and guiding experimental efforts. In this comprehensive review, we discuss the recent advances in crystal structure prediction and performance assessment of hydrogen storage materials from a computational perspective. We highlight the applications of state-of-the-art computational methods, including density functional theory (DFT), molecular dynamics (MD) simulations, and machine learning (ML) techniques, in screening, evaluating, and optimizing storage materials. Special emphasis is placed on the prediction of stable crystal structures, assessment of thermodynamic and kinetic properties, and high-throughput screening of material space. Furthermore, we discuss the importance of multiscale modeling approaches that bridge different length and time scales, providing a holistic understanding of the storage processes. The synergistic integration of computational and experimental studies is also highlighted, with a focus on experimental validation and collaborative material discovery. Finally, we present an outlook on the future directions of computationally driven materials design for hydrogen storage applications, discussing the challenges, opportunities, and strategies for accelerating the development of high-performance storage materials. This review aims to provide a comprehensive and up-to-date account of the field, stimulating further research efforts to leverage computational methods to unlock the full potential of hydrogen storage materials. [ABSTRACT FROM AUTHOR]

Aluminum (Al) ion implantation is one of the most important technologies in SiC device manufacturing processes due to its ability to produce the p-type doping effect, which is essential to building p–n junctions and blocking high voltages. However, besides the doping effect, defects are also probably induced by the implantation. Here, the impacts of Al ion implantation-induced defects on 4H-SiC MOSFET channel transport behaviors are studied using a multiscale simulation flow, including the molecular dynamics (MD) simulation, density functional theory (DFT) calculation, and tight-binding (TB) model-based quantum transport simulation. The simulation results show that an Al ion can not only replace a Si lattice site to realize the p-doping effect, but it can also replace the C lattice site to induce mid-gap trap levels or become an interstitial to induce the n-doping effect. Moreover, the implantation tends to bring additional point defects to the 4H-SiC body region near the Al ions, which will lead to more complicated coupling effects between them, such as degrading the p-type doping effect by trapping free hole carriers and inducing new trap states at the 4H-SiC bandgap. The quantum transport simulations indicate that these coupling effects will impede local electron transports, compensating for the doping effect and increasing the leakage current of the 4H-SiC MOSFET. In this study, the complicated coupling effects between the implanted Al ions and the implantation-induced point defects are revealed, which provides new references for experiments to increase the accepter activation rate and restrain the defect effect in SiC devices. [ABSTRACT FROM AUTHOR]

Exploring therapeutic options is crucial in the ongoing COVID-19 pandemic caused by SARS-CoV-2. Nirmatrelvir, which is a potent inhibitor that targets the SARS-CoV-2 Mpro, shows promise as an antiviral treatment. Additionally, Ivermectin, which is a broad-spectrum antiparasitic drug, has demonstrated effectiveness against the virus in laboratory settings. However, its clinical implications are still debated. Using computational methods, such as molecular docking and 100 ns molecular dynamics simulations, we investigated how Nirmatrelvir and Ivermectin interacted with SARS-CoV-2 Mpro(A). Calculations using density functional theory were instrumental in elucidating the behavior of isolated molecules, primarily by analyzing the frontier molecular orbitals. Our analysis revealed distinct binding patterns: Nirmatrelvir formed strong interactions with amino acids, like MET49, MET165, HIS41, HIS163, HIS164, PHE140, CYS145, GLU166, and ASN142, showing stable binding, with a root-mean-square deviation (RMSD) of around 2.0 Å. On the other hand, Ivermectin interacted with THR237, THR239, LEU271, LEU272, and LEU287, displaying an RMSD of 1.87 Å, indicating enduring interactions. Both ligands stabilized Mpro(A), with Ivermectin showing stability and persistent interactions despite forming fewer hydrogen bonds. These findings offer detailed insights into how Nirmatrelvir and Ivermectin bind to the SARS-CoV-2 main protease, providing valuable information for potential therapeutic strategies against COVID-19. [ABSTRACT FROM AUTHOR]

Due to the serious consequences of the accumulation of heavy metals in organisms throughout the aqueous phase, the treatment of heavy metal pollution has received extensive attention. Porous geopolymer adsorbent (PGA) has been proposed as a promising remover of heavy metal ions due to its production convenience, low cost, and large surface area. However, it is easy to be broken under water impact. Besides, compared to some other adsorbents, the heavy metal ions capacity of PGA needs to be enhanced. In this paper, PGA with 1000 kg/m3 density was directly prepared based on solid waste including fly ash and slag at room temperature. Nano-silica (NS) was added to improve material strength. The compressive strength of PGA with 2 % NS addition increases up to 63.5 % compared with the material without NS addition, and the removal rate of Cu2+ goes to 78.4 % under this condition. Although the filling effect caused by NS addition is not beneficial for the adsorption ability improvement, the molecular dynamics simulation results confirm that the physical adsorption ability upward is mainly caused by the more Natrium-Aluminate-Silicate-Hydrate formation due to the decreasing Ca/Si ratio. Compared with Calcium-Aluminate-Silicate-Hydrate, Natrium-Aluminate-Silicate-Hydrate has a higher physical adsorption ability due to the evenly distributed electropositive region known from the density functional theory analysis, which contributes to PGA adsorption capacity from the outside environment. [Display omitted] • Porous geopolymer adsorbent is a promising remover of heavy metal ions. • NS addition improves adsorbent strength by 63.5% avoiding the adsorbent from being broken. • NS addition leads to more NASH formation contributing to adsorption ability improvement. • The rate of Cu2+ removed by porous geopolymer adsorbent in this study reaches 78.4%. • The evenly distributed electropositive region of NASH contributes to a stronger adsorption ability. [ABSTRACT FROM AUTHOR]

Amine-modified mesoporous silicon was widely used for CO 2 capture. However, its adsorption capability was significantly affected by temperature and humidity. In this paper, tetraethylenepentamine (TEPA) modified SBA-15 adsorbents were prepared for capturing CO 2. The effects of the modification method, the concentration of TEPA, the adsorption temperature, and the humidity of atmosphere on CO 2 adsorption capability were studied. Moreover, combined with molecular dynamics (MD) and density functional theory (DFT) computations, the diffusion characteristics and adsorption mechanism were explored. The CO 2 adsorption capability of the adsorbent prepared by the ultrasonic impregnation method was higher than those prepared by the stirring impregnation method, owing to that ultrasonic impregnation could promote the uniformity of TEPA. With the increase of TEPA concentration of SBA-15, the CO 2 adsorption capability increased. SBA-15-2 had the highest CO 2 adsorption capability of 1.17 mmol/g at 30 °C. This was due to the N-containing functional groups, showing good affinity for CO 2 , introduced by TEPA impregnation. When the temperature increased from 30 °C to 70 °C, the CO 2 adsorption capability of all modified SBA-15 adsorbents decreased, since the CO 2 adsorption was an exothermic reaction. SBA-15-2 showed better water vapor resistance than SBA-15-2 (Stir). This was related to the higher dispersity of organic carbon chain introduced by TEPA modification after ultrasonic impregnation. The organic carbon chain of SBA-15-2 increased the water vapor resistance by reducing the hydroxyl group. Finally, from a microscopic aspect, the MD simulation suggested that impregnated TEPA inside SBA-15 may improve CO 2 capture by increasing the thickness of effective adsorption layer. Besides, the DFT simulation showed that TEPA modification increased the adsorption energy of SBA-15 on CO 2. This serves as a reference for later mesoporous silicon adsorbent research and development on CO 2 capture. [Display omitted] • Ultrasonic impregnation promoted the water vapor resistance of TEPA-SBA-15. • The –NH, –NH 2 , O C–N and –NH 3 + had good adsorption performance for CO 2. • Modified SBA-15 had wide temperature range (30 °C–70 °C) for CO 2 capture. • TEPA inside SBA-15 increases the effective adsorption layer thickness of CO 2. [ABSTRACT FROM AUTHOR]

The deterioration of mild steel in an acidic environment poses a significant challenge in various industries. The emergence of effective corrosion inhibitors has drawn attention to studies aimed at reducing the harmful consequences of corrosion. In this study, the corrosion inhibition efficiency of Prinivil in a 1M HCl solution through various electrochemical and gravimetric techniques has been investigated for the first time. The results demonstrated that the inhibition efficiency of Prinivil expanded from 61.37% at 50 ppm to 97.35% at 500 ppm concentration at 298 K. With a regression coefficient (R²) of 0.987, Kads value of 0.935 and Ea value of 43.024 kJ/mol at 500 ppm concentration of inhibitor, a strong affinity of Prinivil for adsorption onto the metal surface has been significantly found. Scanning electron microscopy (SEM) and contact angle measurement analyses further support the inhibitory behavior of Prinivil, demonstrating the production of a defensive layer on the surface of mild steel. Additionally, molecular dynamics (MD) and Monte Carlo simulations were employed to investigate the stability and interactions between Prinivil and the metallic surface (Fe (1 1 0)) at the atomic level. The computed results reveal strong adsorption of Prinivil upon the steel surface, confirming its viability as a corrosion inhibitor. [ABSTRACT FROM AUTHOR]

High-entropy oxides have recently attracted the interest of the community as a way of attuning the properties of oxides to energy applications. Here, we employ molecular dynamics simulations combined with empirical pair potential models to examine the predicted oxygen diffusivity of fluorite-structured high-entropy oxides. We show that lower levels of the dopants increase the overall diffusivity of the composition, but not to the levels of diffusion seen in yttria-doped zirconia. We attribute this to an increased resistance of the cation sublattice to the distortion that occurs through any multiple substitutions on the cation sublattice. To conclude, it is calculated that oxygen self-diffusion in high-entropy oxides is suppressed as compared to isostructural ternary oxides. [ABSTRACT FROM AUTHOR]

Thiazolin-4-ones and their derivatives represent important heterocyclic scaffolds with various applications in medicinal chemistry. For that reason, the synthesis of two 5-substituted thiazolidin-4-one derivatives was performed. Their structure assignment was conducted by NMR experiments (2D-COSY, 2D-NOESY, 2D-HSQC and 2D-HMBC) and conformational analysis was conducted through Density Functional Theory calculations and 2D-NOESY. Conformational analysis showed that these two molecules adopt exo conformation. Their global minimum structures have two double bonds (C=N, C=C) in Z conformation and the third double (C=N) in E. Our DFT results are in agreement with the 2D-NMR measurements. Furthermore, the reaction isomerization paths were studied via DFT to check the stability of the conformers. Finally, some potential targets were found through the SwissADME platform and docking experiments were performed. Both compounds bind strongly to five macromolecules (triazoloquinazolines, mglur3, Jak3, Danio rerio HDAC6 CD2, acetylcholinesterase) and via SwissADME it was found that these two molecules obey Lipinski's Rule of Five. [ABSTRACT FROM AUTHOR]

Dependence on petroleum and petrochemical products is unsustainable; it is both a finite resource and an environmental hazard. Biodiesel has many attractive qualities, including a sustainable feedstock; however, it has its complications. The pyrolysis (a process already in common use in the petroleum industry) of biodiesel has demonstrated the formation of smaller hydrocarbons comprising many petrochemical products but experiments suffer from difficulty quantifying the myriad reaction pathways followed and products formed. A computational simulation of pyrolysis using "ab initio molecular dynamics" offers atomic-level detail of the reaction pathways and products formed. Herein, the most prevalent fatty-acid ester (methyl linoleate) from the most prevalent feedstock for biodiesel in the United States (soybean oil) is studied. Temperature acceleration within the atom-centered density matrix propagation formalism (Car–Parrinello) utilizing the D3-M06-2X/6-31+G(d,p) model chemistry is used to compose an ensemble of trajectories. The results are grounded in comparison to experimental studies through agreement in the following: (1) the extent of reactivity (40% in the experimental and 36.1% in this work), (2) the homology of hydrocarbon products formed (wt % of C6–C10 products), and (3) the CO/CO2 product ratio. Deoxygenation pathways are critically analyzed (as the presence of oxygen in biodiesel represents a disadvantage in its current use). Within this ensemble, deoxygenation was found to proceed through two subclasses: (1) spontaneous deoxygenation, following one of four possible pathways; or (2) induced deoxygenation, following one of three possible pathways. [ABSTRACT FROM AUTHOR]

Highlights: Surface energy and surface Pourbaix diagram reveal that ZrO2 ( 1 ¯ 11 ) is the most thermodynamically stable facet and is preferentially occupied by HO* at the equilibrium potential of oxygen evolution reaction (OER). Microkinetic modeling analyzed the OER activity of 40 single-metal doped ZrO2 and identified 16 metals exhibit improved catalytic activity, with Rh and Fe dopants showing the remarkable improvement. Thermodynamic free energy diagrams, density of states analysis, and ab initio molecular dynamics simulations further confirm that Fe–ZrO2 and Rh–ZrO2 are highly promising catalysts for OER, showcasing low ΔG for the rate-determining step, high conductivity, and exceptional stability. The design of cost-effective electrocatalysts is an open challenging for oxygen evolution reaction (OER) due to the "stable-or-active" dilemma. Zirconium dioxide (ZrO2), a versatile and low-cost material that can be stable under OER operating conditions, exhibits inherently poor OER activity from experimental observations. Herein, we doped a series of metal elements to regulate the ZrO2 catalytic activity in OER via spin-polarized density functional theory calculations with van der Waals interactions. Microkinetic modeling as a function of the OER activity descriptor (GO*-GHO*) displays that 16 metal dopants enable to enhance OER activities over a thermodynamically stable ZrO2 surface, among which Fe and Rh (in the form of single-atom dopant) reach the volcano peak (i.e. the optimal activity of OER under the potential of interest), indicating excellent OER performance. Free energy diagram calculations, density of states, and ab initio molecular dynamics simulations further showed that Fe and Rh are the effective dopants for ZrO2, leading to low OER overpotential, high conductivity, and good stability. Considering cost-effectiveness, single-atom Fe doped ZrO2 emerged as the most promising catalyst for OER. This finding offers a valuable perspective and reference for experimental researchers to design cost-effective catalysts for the industrial-scale OER production. [ABSTRACT FROM AUTHOR]

Density functional theory is the workhorse of materials simulations. Unfortunately, the quality of results often varies depending on the specific choice of the exchange-correlation functional, which significantly limits the predictive power of this approach. Coupled cluster theory, including single, double, and perturbative triple particle-hole excitation operators, is widely considered the 'gold standard' of quantum chemistry as it can achieve chemical accuracy for non-strongly correlated applications. Because of the high computational cost, the application of coupled cluster theory in materials simulations is rare, and this is particularly true if finite-temperature properties are of interest for which molecular dynamics simulations have to be performed. By combining recent progress in machine learning models with low data requirements for energy surfaces and in the implementation of coupled cluster theory for periodic materials, we show that chemically accurate simulations of materials are practical and could soon become significantly widespread. As an example of this numerical approach, we consider the calculation of the enthalpy of adsorption of CO2 in a porous material. [ABSTRACT FROM AUTHOR]

We introduce a machine learning-based approach called ab initio generalized Langevin equation (AIGLE) to model the dynamics of slow collective variables (CVs) in materials and molecules. In this scheme, the parameters are learned from atomistic simulations based on ab initio quantum mechanical models. Force field, memory kernel, and noise generator are constructed in the context of the Mori-Zwanzig formalism, under the constraint of the fluctuation-dissipation theorem. Combined with deep potential molecular dynamics and electronic density functional theory, this approach opens the way to multiscale modeling in a variety of situations. Here, we demonstrate this capability with a study of two mesoscale processes in crystalline lead titanate, namely the field-driven dynamics of a planar ferroelectric domain wall, and the dynamics of an extensive lattice of coarse-grained electric dipoles. In the first case, AIGLE extends the reach of ab initio simulations to a regime of noise-driven motions not accessible to molecular dynamics. In the second case, AIGLE deals with an extensive set of CVs by adopting a local approximation for the memory kernel and retaining only shortrange noise correlations. The scheme is computationally more efficient than molecular dynamics by several orders of magnitude and mimics the microscopic dynamics at low frequencies where it reproduces accurately the dominant far-infrared absorption frequency. [ABSTRACT FROM AUTHOR]

[Display omitted] • Interatomic potential for AlN was developed based on deep learning method. • Deep potential predicts mechanical and thermal properties with quantum-level accuracy. • Deep potential predicts defect properties with quantum-level accuracy. • DP predicted thermal conductivity is in high agreement with experimental values. Due to its exceptional physical properties, such as high thermal conductivity and mechanical strength, AlN has been widely used in high-power, high-temperature electronic, and optoelectronic devices. Molecular dynamics simulation is a powerful tool to study its thermal and defect properties. The selection of interatomic potentials plays an important role in the accuracy of calculation results. However, molecular dynamics simulations with various interatomic potentials have yielded different results when investigating the thermal and defect properties of AlN over the last few decades. In this paper, an interatomic potential (DP-IAP) model is developed using a deep potential (DP) methodology for AlN, with the training model's datasets derived from density functional theory (DFT) calculations. The DP-IAP demonstrates quantum-level accuracy in the calculation of the mechanical properties, thermal transport properties, and the defects formation and defects migration for AlN. The developed DP model paves the way for modeling thermal transport and defect evolution in AlN-based devices. [ABSTRACT FROM AUTHOR]

Aqueous two-phase systems are environmentally friendlier alternatives for hydrometallurgical processing and purification of metals. However, the viability of application of those systems in such processes is still under investigation, in which the comprehension of the fundamental aspects that govern the metal extraction is essential and can be further constructed using computational approaches. This research paper presents a comprehensive computational study on the fundamental nature of metal extraction in polymer-salt aqueous two-phase systems (ATPS), comparing the results of modeling and simulation work to the theoretical and experimental data available in the literature. Specifically, the mechanisms underlying the extraction of Co2+, Ni2+, and Fe3+, in ATPS formed by poly(ethylene oxide) (PEO) and thiocyanate salt are investigated, using quantum chemical calculations and molecular dynamics simulations. The formation of pseudo-polycations (PPCs) and thiocyanate metalates (complexes formed by a metal cation bonded to one or more anions) and the interaction of PEO fragments, thiocyanate, and aquo ligands with metal cations are explored. The binding affinity of these species is evaluated from various perspectives, including structural, electronic, and thermodynamic considerations. The solvation behavior of the species in solvents with different polarities is also examined. The findings elucidate the mechanisms governing metal cations partitioning behavior in PEO/thiocyanate ATPS, confirming the mechanisms proposed previously in the literature, involving charge transfer between metal-thiocyanate complexes and polyethylene oxide ether groups as well as interactions between metalate and PPCs. This study represents the first-ever computational investigation into the molecular driving forces behind metal extraction in polymer-salt ATPS, providing valuable insights for optimizing extraction processes and paving the way for future research in this field. [Display omitted] • Computational investigation of metal partitioning mechanism in PEO/SCN salt Aqueous Two-Phase Systems is done; • DFT and MDS are used to assess the three main mechanisms described in the literature; • Nexus between simulations and literature data was found; • Polymer pseudo-polycation and metallate complexes interaction were demonstrated; • Electrostatics, charge transfer and differential solvation contribute to extraction. [ABSTRACT FROM AUTHOR]

[Display omitted] • The MD + DFT complementarity method is used. • The adsorption activation behavior of activated molecules on the surfaces of the six catalysts occurs in the first adsorption layer. • The electrostatic interaction between catalyst and activated molecules and van der Waals interaction have significant effects on the adsorption process of both, and the electrostatic interaction is greater than the van der Waals interaction. • Compared with other heteroatom-doped graphene, BGR and NGR have better catalytic properties, in which BGR has better catalytic activation properties for H 2 O 2 , while NGR has better catalytic activation properties for PMS. • It is speculated that -BC 2 O and -NC 2 functional groups are the main functional regions of H 2 O 2 activation by BGR and PMS activation by NGR, respectively. As an green and efficient metal-free catalyst, heteroatom-doped graphene has gradually become a research topic in the catalytic field, but the active sites and mechanisms of the catalytic reactions are still not thorough enough. In this paper, the adsorption-activation properties of two activated molecules, H 2 O 2 and peroxymonosulfate (PMS), on graphene (GR) and heteroatom (N, P, B, Si, F) doped graphene were investigated by means of computational methods. Molecular dynamics (MD) simulation results showed that the adsorption activation process of activated molecules on the surface of the six catalysts occurs in their first adsorption layer, in which B-doped graphene (BGR) has better catalytic activation performance for H 2 O 2 , while N -doped graphene (NGR) has better catalytic activation performance for PMS. Density function theory (DFT) revealed that the lowest molecular orbital gap of H 2 O 2 at -BCO 2 (0.691 eV), PMS at -NC 2 has the lowest gap (0.432 eV). It is inferred that -BCO 2 and -NC 2 functional groups are the main functional regions of H 2 O 2 activation by BGR and PMS activation by NGR, respectively. This work provides useful guidance for the design and optimization of high-performance metal-free catalysts, and the realization of green remediation for wastewater in the electrocatalytic oxidation process. [ABSTRACT FROM AUTHOR]

The widespread use and impervious nature of per- and polyfluorinated alkyl substances (PFASs) is leading to potentially harmful exposure in numerous environments. One avenue to explore remediation of PFAS-contaminated environments involves investigating how well PFASs adsorb onto various substrates. In the current review, we focus on summarizing recent computational research, largely involving density functional theory (DFT) and molecular dynamics (MD), into the adsorption and interaction of PFASs with a variety of substrates with an aim to provide insight and inspire further research that may lead to solutions to this critical problem that impacts the environment and human health. [ABSTRACT FROM AUTHOR]

Magnetic thin-film modeling stands as a dynamic nexus of scientific inquiry and technological advancement, poised at the vanguard of materials science exploration. Leveraging a diverse suite of computational methodologies, including Monte Carlo simulations and molecular dynamics, researchers meticulously dissect the intricate interplay governing magnetism and thin-film growth across heterogeneous substrates. Recent strides, notably in multiscale modeling and machine learning paradigms, have engendered a paradigm shift in predictive capabilities, facilitating a nuanced understanding of thin-film dynamics spanning disparate spatiotemporal regimes. This interdisciplinary synergy, complemented by avantgarde experimental modalities such as in situ microscopy, promises a tapestry of transformative advancements in magnetic materials with far-reaching implications across multifaceted domains including magnetic data storage, spintronics, and magnetic sensing technologies. The confluence of computational modeling and experimental validation heralds a new era of scientific rigor, affording unparalleled insights into the real-time dynamics of magnetic films and bolstering the fidelity of predictive models. As researchers chart an ambitiously uncharted trajectory, the burgeoning realm of magnetic thin-film modeling burgeons with promise, poised to unlock novel paradigms in materials science and engineering. Through this intricate nexus of theoretical elucidation and empirical validation, magnetic thin-film modeling heralds a future replete with innovation, catalyzing a renaissance in technological possibilities across diverse industrial landscapes. [ABSTRACT FROM AUTHOR]

The computational study of the van der Waals hetero (vdW) bilayer GeI2/InTe has been carried out in present study. The isolated monolayer GeI2 and InTe have been studied first and the results were compared to the previous studies. The possible stackings are considered after the vdW interaction correction is applied in the structure relaxation. The vdW hetero bilayer stability has been checked from the phonon dispersion and ab initio Molecular Dynamics calculations. The charge transfer from InTe to GeI2 monolayer. Type-II indirect band gap (1.98, 2.01 eV) is verified by the projected band structure and band alignment calculations. The vdW hetero bilayer is a superior photocatalyst for the pH value up to pH = 0 to 11. The optical properties are calculated from the complex dielectric constant. The absorption coefficient shows the enhance absorption of light in the visible and ultraviolet regions. The vdW hetero bilayer has shown low reflectivity (37%) and a high refractive index (2.80) in the visible region. The enhanced optical properties have shown its possible applications in optoelectronic devices. [ABSTRACT FROM AUTHOR]

The ferroelectric phase transition of the perovskite barium titanate as well as its technical importance regarding the switching of respective polar properties is well known and has been thoroughly studied, both experimentally and on theoretical grounds. While details about the phase diagram as well as transition temperatures are experimentally well known, the theoretical approaches still face difficulties in contributing a detailed description of these phase transitions. Within this work, a new methodological approach is introduced to revisit the ferroelectric phase transition with first-principles methods. With the chosen ab initio molecular dynamics (AIMD) method in combination with the applied NpT ensemble, we are able to join the accuracy of density functional theory (DFT) with ambient conditions, realized using a thermostat and barostat in an MD simulation. The derived phase diagram confirms recent corrections in the theoretical models and reproduces the phase boundary pressure dependence of TC. In conclusion of the statistical atomistic dynamics, the nature of the transition can be described in a more detailed way. In addition, this work paves the way towards locally patterned piezoelectrica by means of acoustic standing waves as well as piezoelectrically induced acoustic resonators. [ABSTRACT FROM AUTHOR]

A thymol-based molecule was synthesized and characterized. The anti-proliferative activity of molecule 4 was tested in vitro in three cancer cell lines and a healthy human cell line. The results showed that this molecule had cytotoxic effects on the human cell lines studied. Images of the cells were taken using the Leica inverted microscope. Molecular docking, molecular dynamics simulation, density functional theory calculations, and computational pharmacokinetics analysis of molecule 4 were carried out. The binding mode of the molecule with ABL1 was revealed through molecular docking. The stability of the complexes procured from the docking was assessed through molecular dynamics simulation. The computational analysis revealed that the antiproliferative effect of molecule 4 on the cancer cell lines might result from its potential to inhibit ABL1. In addition, molecule 4 was found to have ideal pharmacokinetic properties to be used as a drug candidate molecule. Hence, the experimental and computational studies indicated its derivatives might have promising antiproliferative activity. [ABSTRACT FROM AUTHOR]

Vitrimers are an innovative class of polymers that boast a remarkable fusion of mechanical and dynamic features, complemented by the added benefit of end‐of‐life recyclability. This extraordinary blend of properties makes them highly attractive for a variety of applications, such as the automotive sector, soft robotics, and the aerospace industry. At their core, vitrimer materials consist of crosslinked covalent networks that have the ability to dynamically reorganize in response to external factors, including temperature changes, pressure variations, or shifts in pH levels. In this review, the aim is to delve into the latest advancements in the theoretical understanding and computational design of vitrimers. The review begins by offering an overview of the fundamental principles that underlie the behavior of these materials, encompassing their structures, dynamic behavior, and reaction mechanisms. Subsequently, recent progress in the computational design of vitrimers is explored, with a focus on the employment of molecular dynamics (MD)/Monte Carlo (MC) simulations and density functional theory (DFT) calculations. Last, the existing challenges and prospective directions for this field are critically analyzed, emphasizing the necessity for additional theoretical and computational advancements, coupled with experimental validation. [ABSTRACT FROM AUTHOR]