ABSTRACTThe sodium (Na) storage behaviour of T4,4,4-graphyne of two-dimensional porous carbon sheet is explored using the density functional theory (DFT). The energy of adsorption and barrier, storage capacity, and open-circuit voltage are calculated. The calculations predict that Na atom is extraordinary mobile on T4,4,4-graphyne monolayer as a result of the relatively slight energy barrier. The Na storage capacity is as high as Na8C9, which exceeds the values reported for graphite and some other two-dimensional carbon-based materials. The high Na mobility and theoretical capacity make T4,4,4-graphyne monolayer suitable for implementation in rechargeable ion batteries. The electronic properties are also studied to ensure that T4,4,4-graphyne is suitable for Na-ion batteries as an anode material, and they revealed that semiconductor–metal transition is induced by Na adsorption. The favourable electronic conduction is another demand for promising Na-ion batteries. These results predict that the application of T4,4,4-graphyne sheet will increase efficiency of the Na-ion batteries.

ABSTRACTNew Delhi Metallo-β-lactamase (NDM-1) is an enzyme that hydrolyses a wide range of β-lactam antibiotics, including most carbapenems, leading to antimicrobial resistance. The development of a novel NDM-1 inhibitor for use in combination with carbapenems may help to combat drug-resistant pathogens. Twenty compounds were designed based on the structural features of the NDM-1 active site to inhibit bacterial NDM-1 and protect β-lactam antibiotics from enzyme attack. The designed molecules were naphthalene, thiazole, and sulfone derivatives because they could coordinate with the zinc ions and form hydrophobic contracts with the enzyme’s active site. A molecular docking protocol was used to identify potential inhibitor(s) of the NDM-1 target protein. Furthermore, drug-likeness and pharmacokinetic properties of the designed molecules were predicted. Three compounds with the more negative ΔGbinding results were selected for further investigation using molecular dynamic (MD) simulations. T016 had a significantly more negative binding free energy than the positive control and other designed molecules, had stable MD simulations (Root-mean-square deviation < 0.5 Å), passed Lipinski’s rule of five, and had favourable physicochemical and pharmacokinetic properties. The findings can be used to inform the synthesis and in vitro testing of the selected molecules.

The reverse Monte Carlo (RMC) method is widely used in structural modelling and analysis of experimental data. More recently, RMC has been applied to the calculation of equilibrium thermodynamic pr...

ABSTRACTWe describe the equilibrium conformations of a polymer near an attractive surface for different conditions in solvent quality and polymer stiffness. Using molecular dynamics techniques in a canonical ensemble, we show the evolution of the phase diagrams as function of temperature and surface interaction strength. Phase diagrams show an ampler variety of possible conformations due to changes in solvent quality compared to stiffness for which variations in conformations appear mainly in the degree of adsorption. We show that the adsorption transition is independent of solvent quality and stiffness. When both parameters change simultaneously, solvent effects are stronger than the stiffness secluding the stiff conformations to regions of low temperature and high surface attraction. A remarkable observation is that the radius of gyration perpendicular component to the surface, RgxRgxRgx, signals the adsorption transition at coincidental points for each system independently of solvent and stiffness variations in all simulations, which may be of aid in locating this transition in other systems.

ABSTRACTData implicating the mutation in penicillin-binding protein (PBP) 3 and occasionally PBP5 in the resistance of Escherichia coli to beta−lactams is intriguing. Thus, the identification of an improved class of inhibitors of PBP3 and PBP5 is imperative, and in this study, phenolics due to their promising antibacterial activities were screened using structure−based pharmacophore and molecular docking approaches against PBP3, and the ability of the lead phenolics to modulate PBP3 and PBP5 was studied using molecular dynamics simulation. The results demonstrated various inhibitory capacities of the lead phenolics, with lysidicichin (−41.66 kcal/mol) and silicristin (−31.11 kcal/mol) being the most potent against PBP3, while epicatechin 3-O-(3-O-methylgallate) (−38.97 kcal/mol) and epigallocatechin-4-benzyl thioether (−37.01 kcal/mol) had higher affinities towards PBP5. Overall, epicatechin gallate had the best broad-spectrum of activity, as the compound was able to bind favourably to both targets. Additionally, the thermodynamic information confirmed the stability of the lead phenolics with both targets. Conclusively, while these observations are suggestive of the modulatory role of the lead phenolics on the growth of E. coli, further in vitro and in vivo validation of the activity elicited by the phenolics in this study is imperative, and efforts are underway in this direction.

ABSTRACTIn this study, we designed four pyrone-based hole transport materials (HTMs) P1-P4 in perovskite solar cells (PSCs) and studied the effects of the benzene and thiophene groups on their performance. Based on density functional theory (DFT), we investigated the geometry, frontier molecular orbitals (FMOs), density of states (DOS), solvation free energy (ΔGsol), absolute hardness, electrostatic potential (ESP), and hole transport rates of all designed molecules. Time-dependent density functional theory (TD-DFT) was used to analyse the absorption spectra, charge density difference diagrams (CDD), heat map, D index, H index, Sr index, and exciton binding energy (Ecoul) of HTMs P1-P4 to examine their optical and electronic excitation features. The simulation findings demonstrate that the HTMs P1-P4 molecular energy levels match with the energy level of perovskite (MAPbI3). Additionally, all designed molecules have good stability and high hole transport rates. The UV-visible absorption spectra show that the designed HTMs can broaden the optical absorption range of PSCs in the visible light region. In addition, by increasing the length of π-linker can significantly improve the photoelectric properties of the HTMs. The designed molecules exhibit great electronic character, optical character, hole transport rates, and stability, which provide ideas for the future design of high-efficiency HTMs.

ABSTRACTThis paper proposes simulation protocols in terms of an auto-calibration strategy for the parameterisation of Gibbs ensemble Monte Carlo simulations for Lennard–Jones fluids. The proposed simulation protocols have been deduced from various approaches proposed in literature and have been tested against pure LJ fluids and their mixtures. These simulation protocols are intended to reduce or avoid time-consuming pre-simulations by adjusting the trial move limits, the number of attempted transfers, or the probability of attempted transfer during the equilibration phase, and can serve as a starting point for simulating more complex molecules, beyond LJ-fluids. This new approach aims to adjust simulation parameters to ensure a sufficient amount of successful trial moves as suggested in literature. It is similar to a previously proposed trial move adjustment and can easily be implemented in existing simulation code.Abbreviations: BWR EoS: Benedict–Webb–Rubin equation of state; CBMC: Configurational-bias Monte Carlo; EoS: Equation of state; GEMC: Gibbs ensemble Monte Carlo; LJ: Lennard–Jones; M1; M2; M3: Abbreviations for the three simulated mixtures; MC: Monte Carlo; PAT: Probability of attempted transfer; TL: Translation within a box (GEMC move); TR: Transfer to the other box (GEMC move); t-PR EoS: Volume-translated Peng-Robinson equation of state

ABSTRACTThe introduction of the hierarchical structure into face-centered cubic (FCC) nanotwinned (NT) metals can improve strength without losing plasticity. In present work, molecular dynamics (MD) simulations have been performed to investigate the effect of the hierarchical structure on NT copper under tensile and shear loading by comparing the differences between the hierarchical nanotwinned (HNT) and perfect nanotwinned (PNT) specimens. The results show that the hierarchical structure will alter the twin boundaries (TBs) migration mode under shear loading. The hardening process of HNT copper is dependent on the geometric structure of the grain boundary and loading direction. There is a stress gradient and additional hardening in HNT copper under tensile loading due to the hierarchical structure. This work may shed light on the role of hierarchical structure in the multiscale structure design of NT materials.

ABSTRACTCO2 sequestration (CS) into the shale formations can reduce not only carbon emissions but also enhance gas recovery (EGR). The adsorption and diffusion behaviour of CO2 and CH4 on kerogens with different maturity play a crucial role in CS-EGR as they determine the efficiency of CO2 storage and energy recovery. In this work, GCMC and MD simulations were performed to investigate the adsorption and diffusion behaviour of CO2 and CH4 on kerogen models at different grades of maturity. It indicated that, in the same maturity, the CO2 adsorption capacity was more significant than that of CH4. With increasing maturity, the adsorption capacity and diffusion rate increased. With the increase of water contents, the swelling ratio of kerogens increased, and the adsorption capacity and the diffusion coefficients of CH4 and CO2 decreased. However, the adsorption selectivity of CO2 over CH4 significantly increased. H2O and CO2 molecules both preferred to adsorb on functional groups of oxygen, nitrogen and sulfur. This study consolidated our hypothesis that an injected CO2 to shale gas and oil formations contributed positively to enhanced energy recovery owing to the difference in adsorption and diffusion behaviour of CH4 and CO2 in kerogens with different maturity in gas and oil reservoirs.

ABSTRACTGlass transition temperature (Tg) is one of the most significant thermophysical property which is hard to measure experimentally. With the development of machine learning, many molecular presentation methods and prediction algorithms have been proposed for predicting Tg. However, most descriptors of these algorithms are linear, while the values of molecular descriptors obtained from experiments or simulation software may have nonlinear relationships. General nonlinear machine learning methods are difficult to apply for the super high dimensional characteristics of molecular descriptors. In this paper, molecular descriptors are defined in manifold space and manifold learning is used for dimension reduction. Different from other linear algorithms for selecting molecular descriptors, Locally Linear Embedding (LLE) is utilised to reduce dimensionalities by extracting new features from numerous molecular descriptors. The features with dimensionality reduction are fed to the eXtreme Gradient Boosting (XGBoost) model. This ensemble algorithm is suitable for predicting glass transition temperature due to its high adaptability and nonlinear approximation ability. Genetic algorithm (GA) is adopted for optimising the parameters of XGBoost. The combinatorial approach consists of dimensionality reduction, prediction and optimisation. Experimental results show that the proposed machine learning approach LLE-XGBoost-GA has higher accuracy in Tg prediction of polymers.

AbstractThe curcumin is a well-known antioxidant that can scavenge free radicals efficiently. The methyl free radicals, generated by the metabolism of various genotoxic compounds such as hydrazines and peroxides, can methylate various sites in DNA. Herein, we have carried out density functional theory calculations to investigate the scavenging activity of curcumin toward the methyl and ethyl radicals through radical adduct formation (RAF), hydrogen atom transfer (HAT) and single electron transfer (SET) mechanisms. The SET mechanism is found to be highly endergonic and so not viable. Our calculations show that the curcumin can scavenge methyl radicals through both RAF and HAT mechanisms but RAF would be preferred over the HAT. Further, it is found that the curcumin can scavenge methyl radicals more efficiently as compared to ethyl radicals through RAF mechanism.

ABSTRACTThis study is devoted to the physicochemical properties of CeF3 – FLiNaK molten mixture with various CeF3 concentrations. Density, local structure, mean ion pair lifetimes, heat capacity, self-diffusion coefficients and viscosity were calculated using the classical molecular dynamics method. Most of the properties were studied in the temperature range of 950–1200 K. Taking into consideration data obtained both in this study and in the previous ab initio simulations we quantitatively describe the local structure dynamics. Specifically, the stability of [CeFn] groupings is discussed in detail. To ensure the reliability of the results obtained, the pair potentials for the Ce3+-Ce3+ and Ce3+-F− pairs were carefully fitted through the two-stage algorithm consisting of ab initio energy calculation and fine stochastic optimization.

ABSTRACTInter-macromolecular interaction between uncharged polymers in aqueous solutions can be influenced by concentration of polymer, solvent quality, molecular weight, solution pH, temperature, salt concentration and type of salt. Atomistic molecular dynamics simulations of aqueous NaCl solution containing poly(acrylic acid) and poly(ethylene oxide) are presented. The size of the polymer chains decreases with an increase in salt concentration resulting from water becoming a poor solvent which enhances compositing of polymers. A close pair is formed between carboxylic hydrogen (−COOH) and ether oxygen (−O−) of the polymer at high salt concentration. The change in structure of the PAA/PEO complex is analysed using simulated SAXS and SANS profiles. The solubility of chains decreases and attains the minimum energy conformation at a particular salt concentration. The solvent accessible surface area (SASA) of the complex at higher salt concentration is less as compared to the lower. Increase in salt concentration enhances the cooperative interaction via hydrogen bonding between PAA and PEO and weakens the polymer-water-hydrogen bonding. The net result is a decrease in solubility of these polymers and thermodynamically stable polymer-polymer complex is formed at higher salt concentrations. Simulation results are in agreement with available experimental data in literature.

ABSTRACTMachine learning methods are increasingly used in research to save time and computational expenses. The data-driven approach relies on existing data for predictions based on statistical inference and interpolation. Liquids, in particular, benefit from machine learning due to their higher computational requirements. In this study, we propose a simple data-driven strategy that employs classical molecular dynamics simulations to generate potential energy spatial distribution data. This data is then used to train a machine learning model by using topologically similar scaled-down systems. The trained model is subsequently employed to predict force field behaviour for complex full-scale systems, resulting in time and computational cost savings. During training, the potential energy pseudo field serves as a model descriptor, while the final predictions are generated using multidimensional regression-based learning (Gaussian Process) and neural architecture learning (Artificial Neural Network), which are integrated into the simulation as lookup tables. Comparing the data-driven and conventional approaches reveals a significant acceleration in overall simulation runtime when appropriately trained machine learning models are utilised. Although the initial training phase of the machine learning models is time-consuming, retraining is unnecessary for future simulations with the same setup. Thus, this approach offers a straightforward means of conducting complex simulations in less time.

ABSTRACTIn molecular dynamics simulation, it is quite common to calculate a precise temperature profile with an atomic or sub-angstrom resolution. While this calculation typically requires the degrees of freedom (DOF) of individual atoms, those in a molecule subject to geometric constraints is undefined in general. Conventionally, the approximation of subtracting from the atom DOF by 1/2 per one distance constraint has been used, but this approximation is valid for spatially homogeneous systems only. In the present study, on the basis of statistical mechanics, we derived more general expressions for the DOF of atoms in fully or partially rigid molecules. The expressions ensure that in an equilibrium state, all constrained atoms have the same temperature as the equilibrium temperature of the whole system and are also applicable to inhomogeneous systems.

ABSTRACTInitially, density approximations and generalised gradient approximations (GGA) functional of DFT were executed to determine the electronic structure where the non-local functionals of GGA obtained more close value of reference value, so that GGA method was used to calculate the band structures, DOS, PDOS and optical properties of ZrO2, Zr0.93Si0.07O2 and Zr0.86Si0.14O2 using the Perdew–Burke–Ernzerhof (PBE), Revised Perdew–Burke–Ernzerhof (RPBE), Perdew Wang (PW91), and Wu-Cohen. The transferability of electrons is completely related to PseudoPotential (PP), where four methods, such as OTFG ultra-soft, OTFG norm-conserving, ultra-soft, and norm-conserving, were used in this study. Finally, the norm-conserving PP has been selected as the most accurate method for determination of electronic structure. In addition, to assess the nature of orbital, the DOS and PDOS were additionally simulated and even the optical properties of crystals were calculated. Furthermore, the chemical reactivity, such as HOMO and LUMO, quantum properties, is justified where doping can have a vast effect as well as the open circuit voltage (Voc) is increased after doping. Finally, the toxicity data from in silico study refers to us that these are non-toxic or non-carcinogenic materials with not readily biodegradable status.

ABSTRACTIn this work, theoretical and experimental studies of a tubular reactor where methyl methacrylate was polymerised were presented. This study focused on the rheological characterisation of the mixture in the various reactor lengths. Three different rheological models for the viscosity of the mixture (i.e. Power-law, Bingham-plastic, Herschel–Bulkley) were studied and the axial velocity distribution of these three models was determined. Unlike the Power-law and Bingham-plastic models, the Herschel–Bulkley model does not have the velocity distribution equation in the literature. Therefore, this equation was derived (This calculation was described in the appendix). The reactor was modelled based on these velocity profiles. Results from this study indicate that models with more adjustable parameters provide the best viscosity prediction for the mixture. Furthermore, the behaviour of the mixture in the reactor inlet is quasi-Newtonian fluid and as the conversion develops, the mixture has a shear-thinning behaviour. In addition, the velocity profile begins from the parabolic profile and as the conversion develops, it approaches the plug mode. Finally, by comparing the conversion rate between these three models with experiments, it is concluded that Herschel–Bulkley’s modelling is the most reliable.

ABSTRACTThe equilibrium thermodynamic properties of binary Lennard–Jones mixtures are determined by means of a Monte Carlo-based perturbation theory for an effective single-component fluid. The results for the equation of state and the excess energy are compared with simulation data obtained for two equimolar binary Lennard–Jones fluid mixtures at different temperatures along a wide range of densities. The satisfactory accuracy achieved seems to suggest that this approach might be a useful tool to deal with mixtures with a wide variety of intermolecular interactions including mixtures of real fluids.

ABSTRACTIn this paper, the CH4 combustion characteristics in CO2/O2/N2 atmosphere subjected to electric field were studied by the molecular dynamics simulation method. Conventional and unique pathways were obtained. The evolution law of reactants and main products and the first reaction time of main intermediates under the influence of different electric field intensities were analysed. Results showed that the addition of external electric fields increased conventional responses and species diversity. The generation of new pathways induced the production of new species, and the further reactions of new species produced other new pathways, thus accelerating the generation of new pathways and species in the electric field. It was noteworthy that, the applied external electric field could advance the reaction start time and reinforce the combustion process, but its effect on the reaction rate was highly nonlinear. The CH4 reaction with CO2 was significantly intensified at E ≥ 105 V/m, while suppressed at E = 104 V/m. Furthermore, electric fields could promote the oxidation degree of CH4, especially at E = 106 V/m. The studies provide theoretical guidance for revealing the mechanism of methane combustion under a high concentration CO2 atmosphere and promoting the efficient capture of CO2.

ABSTRACTTwin boundary (TB) plays an important role in the deformation process of materials. In this paper, molecular dynamics (MD) simulation was used to investigate the nanoindentation deformation behaviour of single-crystal FeCoCrNiCu high entropy alloy (SC-HEA) and nano-twinned FeCoCrNiCu high entropy alloy (NT-HEA) with different twin spacings. It is found that the main characteristic of plastic deformation of SC-HEA is the dislocation loop emission. The dislocation movement and distribution of NT-HEA are very different from that of SC-HEA. We found that partial dislocation slip parallel to the twin boundary (PSPTB) and twin partial slip (TPS) can lead to alloy softening. The hindrance of the TB causes the dislocation to slip within a single layer (known as confined layer slip, CLS), which strengthens the material. In the process of nanoindentation, the softening and strengthening mechanisms are constantly competing. When the twin spacing is larger than 1.23 nm, CLS dominates the competition with the hardening mechanism, and the hardness of the material increases with the decrease of the twin spacing. When the twin spacing is less than 1.23 nm, the dominant mechanism of plastic deformation changes to the softening mechanism controlled by TPS, and the hardness thus decreases as twin spacing increases.