Force Field Molecular Dynamics Research Articles

Ab Initio Characterization of the CO2-Water Interface Using Unsupervised Machine Learning for Dimensionality Reduction.

Precise characterization of the supercritical CO2-water interface under high pressure and temperature conditions is crucial for the geological storage of carbon dioxide (CO2) in deep saline aquifers. Molecular dynamics (MD) simulations offer a valuable approach to gaining insight into the CO2-water interface at a microscopic level. However, no attempt has been made to characterize the CO2-water interface with the accuracy afforded by ab initio calculations. In this study, we performed ab initio MD (AIMD) simulations to investigate the structural and dynamical properties of the CO2-water interface, comparing the results with those obtained from classical force-field MD (FF-MD) simulations. Molecular orientation at the interface was well reproduced in both AIMD and FF-MD simulations. Characteristic structural fluctuations of water at the interface were unveiled by applying multidimensional scaling and time-dependent principal component analysis to the AIMD trajectories; however, they were not prominent in the FF-MD simulations. Furthermore, our study demonstrated a marked difference in the residence time of molecules in the interface region between AIMD and FF-MD simulations, indicating that time-dependent properties of the CO2-water interface strongly depend on the description of the intermolecular forces.

Novel full-scale model verified by atomic surface and developed composite microfiber and slurry polishing system

Polishing mechanisms between fibers of a polishing pad and slurry are elusive, rising a challenge to develop high-performance composite polishing system. To solve this challenge, a novel full-scale model is proposed from mm to nm, consisting of macro, meso, micro and nanoscale. The model is verified by atomic surface and developed composite microfiber and slurry polishing system. Prior to chemical mechanical polishing, fused silica was polished by ceria slurry. A novel polishing pad was prepared using microfibers with a diameter of 2.5 μm, and a novel green slurry contained silica abrasives, hydrogen peroxide, sodium carbonate, sorbitol and xanthan gum. After CMP, an atomic surface with Ra of 0.108 nm was achieved, and the thickness of damaged layer is 1.95 nm. In terms of the macroscale model suggested, the maximum stress on the microfiber pad decreased 417.7 %, and the direct contact area increased 41.23 % compared with those of a commercial nonwoven pad. The peak stress exceeded 1 MPa on the commercial pad, while it reduced to about one fourth on the developed microfiber pad, according to the mesoscale fiber-slurry model proposed. Reactive force field molecular dynamics simulations, i.e. nanoscale model, reveal that a slurry layer existing at interface effectively impedes direct contact between abrasives and fused silica. With increasing the polishing load, material removal mode transformed from an atom to atomic chains. The constructed full-scale model and developed composite polishing system provide new insights to analyze, design and manufacture high-performance polishing pads, slurry and system.

Raman Spectra of Amino Acids and Peptides from Machine Learning Polarizabilities.

Raman spectroscopy is an important tool in the study of vibrational properties and composition of molecules, peptides, and even proteins. Raman spectra can be simulated based on the change of the electronic polarizability with vibrations, which can nowadays be efficiently obtained via machine learning models trained on first-principles data. However, the transferability of the models trained on small molecules to larger structures is unclear, and direct training on large structures is prohibitively expensive. In this work, we first train two machine learning models to predict the polarizabilities of all 20 amino acids. Both models are carefully benchmarked and compared to density functional theory (DFT) calculations, with the neural network method being found to offer better transferability. By combination of machine learning models with classical force field molecular dynamics, Raman spectra of all amino acids are also obtained and investigated, showing good agreement with experiments. The models are further extended to small peptides. We find that adding structures containing peptide bonds to the training set greatly improves predictions, even for peptides not included in training sets.

In-situ enforcing molecular diffusion to functionalize hollow fiber carbon membranes enables efficient CO2 separations

Microporous carbon membranes with tunable micropores are attractive materials for CO2 separations. Tailoring the gas transport channels is an effective strategy to achieve high separation performance, while it remains challenging due to the lack of control over sub-nanopores. Herein, we present an in-situ molecular functionalization strategy wherein the confined sub-nanopore properties are designed by enforcing molecules to diffuse over pores and functionalize the pore affinity. By enforcing oxygen-functionalization, a strong CO2 affinity between the carbon matrix and CO2 molecules is generated, which facilitated CO2 transport, thereby enhancing the CO2 permeability by ∼4.7-fold and without sacrificing molecular sieving ability for gas mixtures, like CO2/N2 and CO2/CH4. The functionalization mechanism was confirmed using reactive force field molecular dynamics (ReaxFF-MD) simulations. Furthermore, this strategy, which was directly applied to hollow fiber membrane modules, provides a facile and scalable approach, and expands the currently limited library of penetrative micropore tailoring of microporous membranes.

Evaluating aliphatic CF, CF2, and CF3 groups as vibrational Stark effect reporters.

Given the extensive use of fluorination in molecular design, it is imperative to understand the solvation properties of fluorinated compounds and the impact of the C-F bond on electrostatic interactions. Vibrational spectroscopy can provide direct insights into these interactions by using the C-F bond stretching [v(C-F)] as an electric field probe through the vibrational Stark effect (VSE). In this work, we explore the VSE of the three basic patterns of aliphatic fluorination, i.e., mono-, di-, and trifluorination in CF, CF2, and CF3 groups, respectively, and compare their response to the well-studied aromatic v(C-F). Magnitudes (i.e., Stark tuning rates) and orientations of the difference dipole vectors of the v(C-F)-containing normal modes were determined using density functional theory and a molecular dynamics (MD)-assisted solvatochromic analysis of model compounds in solvents of varying polarity. We obtain Stark tuning rates of 0.2-0.8cm-1/(MV/cm), with smallest and largest electric field sensitivities for CFaliphatic and CF3,aliphatic, respectively. While average electric fields of solvation were oriented along the main symmetry axis of the CFn, and thus along its static dipole, the Stark tuning rate vectors were tilted by up to 87° potentially enabling to map electrostatics in multiple dimensions. We discuss the influence of conformational heterogeneity on spectral shifts and point out the importance of multipolar and/or polarizable MD force fields to describe the electrostatics of fluorinated molecules. The implications of this work are of direct relevance for studies of fluorinated molecules as found in pharmaceuticals, fluorinated peptides, and proteins.

Understanding the adsorption properties of CO2 and N2 by a typical MOF structure: Molecular dynamics and weak interaction visualization

An extensible molecular dynamics (MD) force field for a typical metal–organic framework (MOF) has been developed and verified in comparison with experimental data. The visualization of the important weak interactions based on density functional theory (DFT) calculations is performed. The dynamic process of CO2 and N2 adsorption by MOF was then studied by MD methods. The gas adsorption and desorption during temperature and pressure swing were also investigated. It is found that the structural features of MOF have an important effect on the regional range and strength of the weak interactions, and the region of the van der Waals potential surface of the MOF can determine the gas density distribution. The adsorption is dominated by van der Waals interactions on the whole and the variation of the total weak interaction energy can reflect that of the adsorbed amount. The sorption/desorption responds more slowly to temperature swing than to pressure swing.

Critical assessment of popular biomolecular force fields for molecular dynamics simulations of folding and enzymatic activity of main protease of coronavirus SARS-CoV-2

The main cysteine protease (Mpro) of coronavirus SARS-CoV-2 has become a promising target for computational development in anti-COVID-19 treatments. Here, we benchmarked the performance of six biomolecular molecular dynamics (MD) force fields (OPLS-AA, CHARMM27, CHARMM36, AMBER03, AMBER14SB and GROMOS G54A7) and three water models (TIP3P, TIP4P and SPC) for reproducing the native fold and the enzymatic activity of Mpro as monomeric and dimeric units. The MD sampling up to 1 μs suggested that the proper choice of the force fields and water models plays an essential role in reproducing the tertiary structure and the inter-residue distance between the catalytic dyad His41-Cys145. We found that while most benchmarked all-atom force fields reproduce well the native fold of Mpro, the CHARMM27/TIP3P and OPLS-AA/TIP4P setups revealed a good performance in reproducing the structure of the catalytic domain. In addition, these FF setups were also well-adopted for MD sampling of Mpro at the physiologic conditions by mimicking the presence of 100 mM NaCl and the elevated temperature of 310 K. Finally, both FFs were also performed well in reproducing the native fold of Mpro in a dimeric form. Therefore, comparing the preservation of the native fold of Mpro and the stability of its catalytic site architecture, our MD benchmarking suggests that the OPLS-AA/TIP4P and CHARMM27/TIP3P MD setups at the physiologic conditions may be well-suited for rapid in silico screening and developing broad-spectrum anti-coronaviral therapeutic agents.

Theoretical investigation of (La4O6)n, (La2Ce2O7)n, and (Ce4O8)n nanoclusters (n = 10, 18): Temperature effects and O-vacancy formation.

We report a theoretical investigation of temperature, size, and composition effects on the structural, energetic, and electronic properties of the (La4O6)n, (La2Ce2O7)n, and (Ce4O8)n nanoclusters (NCs) for n = 10, 18. Furthermore, we investigated the single O vacancy formation energy as a function of the geometric location within the NC. Our calculations are based on the combination of force-field molecular dynamics (MD) simulations and density functional theory calculations. We identified a phase transition from disordered to ordered structures for all NCs via MD simulations and structural analysis, e.g., radius changes, radial distribution function, common neighbor analysis, etc. The transition is sharp for La36Ce36O126, La20Ce20O70, and Ce72O144 due to the crystalline domains in the core and less abrupt for Ce40O80, La40O60, and La72O108. As expected, radius changes are abrupt at the transition temperature, as are morphological differences between NCs located below and above the transition temperature. We found a strong dependence on the O vacancy formation energy (Evac) and its location within the NCs. For example, for La40O60, Evac decreases almost linearly as the distance from the geometric center increases; however, the same trend was not observed for Ce40O80, while there are large deviations from the linear trend for La20Ce20O70. Evac has smaller values for Ce40O80 and higher values for La40O60, that is, almost three times, while Evac has intermediate values for mixed oxides, as expected from weighted averages. Therefore, the mixture of one formula unit of La2O3 with two formula units of CeO2 has the effect of increasing the stability of CeO2 (binding energy), which increases the magnitude of the formation energy of the O vacancy.

Evaluating Polarizable Biomembrane Simulations against Experiments.

Owing to the increase of available computational capabilities and the potential for providing a more accurate description, polarizable molecular dynamics force fields are gaining popularity in modeling biomolecular systems. It is, however, crucial to evaluate how much precision is truly gained with increasing cost and complexity of the simulation. Here, we leverage the NMRlipids open collaboration and Databank to assess the performance of available polarizable lipid models─the CHARMM-Drude and the AMOEBA-based parameters─against high-fidelity experimental data and compare them to the top-performing nonpolarizable models. While some improvement in the description of ion binding to membranes is observed in the most recent CHARMM-Drude parameters, and the conformational dynamics of AMOEBA-based parameters are excellent, the best nonpolarizable models tend to outperform their polarizable counterparts for each property we explored. The identified shortcomings range from inaccuracies in describing the conformational space of lipids to excessively slow conformational dynamics. Our results provide valuable insights for the further refinement of polarizable lipid force fields and for selecting the best simulation parameters for specific applications.

Combustion characteristics and nitrogen conversion mechanism in ammonia/coal Co-firing process

The coupled combustion of coal with the carbon-free fuel NH3 is an effective technology for reducing CO2 emissions. Based on elemental analysis, proximate analysis, Fourier Transform infrared spectroscopy (FTIR), Carbon-13 Nuclear Magnetic Resonance (13C NMR), and X-ray photoelectron spectroscopy (XPS) characterizations, a coal macromolecular model was constructed. The combustion characteristics of coal/NH3 co-firing were investigated by reactive force field molecular dynamics simulations (ReaxFF MD). The transformation mechanism of elemental N was elucidated. The influence of temperature, oxygen concentration, and NH3 co-firing ratio (CR) on products was investigated. The results showed that during the non-isothermal combustion phase, the coal macromolecules decomposed more rapidly when the heating rate was low. In the isothermal phase, high temperatures promoted secondary reactions. The production of inorganic gases increased with increasing temperature. As the molar fraction of NH3 increased, the production of CO2 and CO was effectively reduced. There were three main pathways for NO formation. As NH3 decomposed to form NH2, NH2 was subsequently converted to NH, and NH reacted with O2 to form NO. The NH2 could also react with O radicals to form HNO, which was then converted to NO. Besides, both thermal NOx and prompt NOx were generated since the N2 was involved in the reaction. In addition, the production of NOx increased significantly at oxygen concentrations greater than 1.4.

Effect of H2O on macroscopic flame behaviors and combustion reaction mechanism of 1,1-difluoroethane (R152a)

1,1-difluoroethane (R152a) is one of the most prospective low GWP refrigerants but may trigger fires and explosions once it leaks. Understanding the flame propagation process and combustion mechanisms at different relative humidity conditions is essential to use flammable refrigerants safely. In this study, a high-speed camera has recorded the flame propagation of R152a combustion near the flammability limit. Combining with macroscopic experimental phenomena, we revealed the effect of H2O on the microscopic mechanism of R152a combustion by using reactive force field molecular dynamics simulations with a reliable force field. The promotion effects of H2O on the oxidation of R152a were revealed from an atomistic perspective. The differences of oxidation intermediates and products in different environments were analyzed for the first time. The H2O/O2 environment was the most potent promoter of R152a decomposition, followed by the O2 and the pyrolysis environment. The O2/H2O environment reduced the apparent activation energy of R152a, significantly enhanced the consumption rate of R152a, and enriched the number of species. O2 reacts with H2O or H to form OH to accelerate the reaction process. The H2O could provide more OH active fragments for the reaction. Moreover, it promotes the formation of HF and H2, H2O + F→HF + OH, H2O + H→H2 + HO. This study aims to provide a guiding theory for the safe application and disaster prevention of flammable refrigerants.

Global ranking of the sensitivity of interaction potential contributions within classical molecular dynamics force fields

Uncertainty quantification (UQ) is rapidly becoming a sine qua non for all forms of computational science out of which actionable outcomes are anticipated. Much of the microscopic world of atoms and molecules has remained immune to these developments but due to the fundamental problems of reproducibility and reliability, it is essential that practitioners pay attention to the issues concerned. Here a UQ study is undertaken of classical molecular dynamics with a particular focus on uncertainties in the high-dimensional force-field parameters, which affect key quantities of interest, including material properties and binding free energy predictions in drug discovery and personalized medicine. Using scalable UQ methods based on active subspaces that invoke machine learning and Gaussian processes, the sensitivity of the input parameters is ranked. Our analyses reveal that the prediction uncertainty is dominated by a small number of the hundreds of interaction potential parameters within the force fields employed. This ranking highlights what forms of interaction control the prediction uncertainty and enables systematic improvements to be made in future optimizations of such parameters.

Reactive Force Field Molecular Dynamics Investigation of NH3 Generation Mechanism during Protein Pyrolysis Process.

The mechanism of ammonia formation during the pyrolysis of proteins in biomass is currently unclear. To further investigate this issue, this study employed the AMS 2023.104 software to select proteins (actual proteins) as the model compounds and the amino acids contained within them (assembled amino acids) as the comparative models. ReaxFF molecular dynamics simulations were conducted to explore the nitrogen transformation and NH3 generation mechanisms in three-phase products (char, tar, and gas) during protein pyrolysis. The research results revealed several key findings. Regardless of whether the model compounds are actual proteins or assembled amino acids, NH3 is the primary nitrogen-containing product during pyrolysis. However, as the temperature rises to higher levels, such as 2000 K and 2500 K, the amount of NH3 decreases significantly in the later stages of pyrolysis, indicating that it is being converted into other nitrogen-bearing species, such as HCN and N2. Simultaneously, we also observed significant differences between the pyrolysis processes of actual proteins and assembled amino acids. Notably, at 2000 K, the amount of NH3 generated from the pyrolysis of assembled amino acids was twice that of actual proteins. This discrepancy mainly stems from the inherent structural differences between proteins and amino acids. In proteins, nitrogen is predominantly present in a network-like structure (NH-N), which shields it from direct external exposure, thus requiring more energy for nitrogen to participate in pyrolysis reactions, making it more difficult for NH3 to form. Conversely, assembled amino acids can release NH3 through a simpler deamination process, leading to a significant increase in NH3 production during their pyrolysis.

The Catalytic Effect of Pt on Lignin Pyrolysis: A Reactive Molecular Dynamics Study

Lignin is the second-largest renewable resource in nature, second only to cellulose. Lignin is one of the most significant components of biomass, and it determines the behaviour of biomass in many thermochemical processes. However, limited studies have focused on the influence of metal catalysts on lignin pyrolysis. This study aims to develop a sustainable lignin catalytic pyrolysis technology to improve biomass energy-conversion efficiency, reduce dependence on fossil fuels, and promote the development of clean energy. In this study, the impact of Pt catalyst on the pyrolysis process of hardwood lignin was simulated by using reactive force field (ReaxFF) molecular dynamics. Through the comparison of the system without catalysts, the catalyst exhibited evident attraction to lignin macromolecules, prompting their decomposition at lower temperatures. Additionally, the catalyst has the strongest adsorption capacity for H radical. The activation energy of the reaction was calculated by kinetic analysis. It was found that the addition of catalysts significantly reduced the activation energy of the reaction. By revealing the effect of Pt catalyst on the lignin pyrolysis process, it provides a theoretical basis for biomass pyrolysis and the utilization of metal catalysts in industry.

Inhibition mechanism of CHF3 on hydrogen–oxygen combustion: Insights from reactive force field molecular dynamics simulations

To mitigate the risks linked to hydrogen and oxygen (H2–O2) combustion through CHF3 additives, Reactive Force Field Molecular Dynamics (ReaxFF MD) simulations are performed in this study. The primary objective is to investigate the inhibition mechanism of CHF3 on H2–O2 combustion from 2000 K to 2800 K. The simulation results demonstrate that the reaction pathways of hydrogen combustion are changed under the extended second explosion limit, and the main radicals involved in elementary reactions transform from H, OH, and O to H, OH, and HO2. CHF3 predominantly engages in reactions with H radicals to impede the continuation of chain reactions by forming stable HF molecules. OH radicals react with modest amounts of secondary fluorides such as CHF2OH, CH2F, and so on, while HO2 radicals are combined with even fewer intermediates like CHF2O and CHFOH to prevent chain propagations. Moreover, comprehensive and novel reaction pathways are proposed for the inhibition of H2–O2 combustion by CHF3. The parameters of the reaction kinetics indicate that the ignition delay is advanced and the activation energy for the combustion process is increased under the influence of CHF3. This study is expected to provide practical guidance on the inhibition of H2–O2 combustion by CHF3.

Direct Evidence of Reversible Changes in Electrolyte and its Interplay with LiO2 Intermediate in Li-O2 Batteries.

Lithium-oxygen batteries show promising energy storage potential with high theoretical energy density; however, further investigation of chemical reactions is required. In this study, experimental Raman and theoretical analyzes are performed for a Li-O2 battery with LiClO4/dimethyl sulfoxide (DMSO) electrolyte and carbon cathode to understand the role of intermediate species in the reactional mechanism of the cell using a high donor number solvent. Operando Raman results reveal reversible changes in the DMSO bands, in addition to the formation and decomposition of Li2O2. On discharge, a decrease in DMSO polarizability is observed and bands of DMSO-Li+-anion interactions are evidenced and supported by abinitio density functional theory (DFT) calculations. Molecular dynamics (MD) force field simulations and operando Raman show that DMSO interacts with LiO2(sol), highlighting the stability of the electrolyte compared to the interaction with reactive . On charging, the presence of Li+ indicates the formation of a lithium-deficient phase, followed by the release of Li+ and oxygen. Therefore, this study contributes to understanding the discharge/charge chemistry of a Li-O2 cell, employing a common carbon cathode and DMSO electrolyte. The combination of a simple characterization technique in operando mode and theoretical studies provides essential information on the mechanism of Li-O2system.

Investigation of lubrication mechanism of phosphate ionic liquid by ReaxFF molecular dynamics simulations

The frictional characteristics of the interface between ionic liquid (IL) and metal can be significantly improved by the formation of a tribo-film, while the lubrication mechanism remains unclear. This study utilized reactive force field molecular dynamics (ReaxFF MD) simulation to investigate the tribological properties, interfacial tribochemical reactions, and formation mechanism of the tributyltetradecyl phosphonium di(2-ethylhexyl) phosphate ([P44414] [DEHP]) tribo-film. The findings indicate that the friction coefficients of ILs decrease as the normal pressure increases. The combination of normal pressure and shear force promotes the dissociation of ionic liquid chains and enhances the binding of free radicals to the end faces. The friction force is primarily influenced by the number of Fe-C bonds at the interface, which demonstrates a positive correlation with the normal pressure.

Characterizing Microheterogeneity in Liquid Mixtures via Local Density Fluctuations.

We present a novel approach to characterize and quantify microheterogeneity and microphase separation in computer simulations of complex liquid mixtures. Our post-processing method is based on local density fluctuations of the different constituents in sampling spheres of varying size. It can be easily applied to both molecular dynamics (MD) and Monte Carlo (MC) simulations, including periodic boundary conditions. Multidimensional correlation of the density distributions yields a clear picture of the domain formation due to the subtle balance of different interactions. We apply our approach to the example of force field molecular dynamics simulations of imidazolium-based ionic liquids with different side chain lengths at different temperatures, namely 1-ethyl-3-methylimidazolium chloride, 1-hexyl-3-methylimidazolium chloride, and 1-decyl-3-methylimidazolium chloride, which are known to form distinct liquid domains. We put the results into the context of existing microheterogeneity analyses and demonstrate the advantages and sensitivity of our novel method. Furthermore, we show how to estimate the configuration entropy from our analysis, and we investigate voids in the system. The analysis has been implemented into our program package TRAVIS and is thus available as free software.

Molecular motion of a nanoscopic moonlander via translations and rotations of triphenylphosphine on graphite

Mass transport at surfaces determines the kinetics of processes such as heterogeneous catalysis and thin-film growth, with the diffusivity being controlled by excitation across a translational barrier. Here, we use neutron spectroscopy to follow the nanoscopic motion of triphenylphosphine (P(C6H5)3 or PPh3) adsorbed on exfoliated graphite. Together with force-field molecular dynamics simulations, we show that the motion is similar to that of a molecular motor, i.e. PPh3 rolls over the surface with an almost negligible activation energy for rotations and motion of the phenyl groups and a comparably small activation energy for translation. While rotations and intramolecular motion dominate up to about 300 K, the molecules follow an additional translational jump-motion across the surface from 350-500 K. The unique behaviour of PPh3 is due to its three-point binding with the surface: Along with van der Waals corrected density functional theory calculations, we illustrate that the adsorption energy of PPh3 increases considerably compared to molecules with flat adsorption geometry, yet the effective diffusion barrier for translational motion increases only slightly. We rationalise these results in terms of molecular symmetry, structure and contact angle, illustrating that the molecular degrees of freedom in larger molecules are intimately connected with the diffusivity.

On-the-fly machine learned force fields for the study of warm dense matter: Application to diffusion and viscosity of CH

We develop a framework for on-the-fly machine learned force field (MLFF) molecular dynamics (MD) simulations of warm dense matter (WDM). In particular, we employ an MLFF scheme based on the kernel method and Bayesian linear regression, with the training data generated from the Kohn–Sham density functional theory (DFT) using the Gauss spectral quadrature method, within which we calculate energies, atomic forces, and stresses. We verify the accuracy of the formalism by comparing the predicted properties of warm dense carbon with recent Kohn–Sham DFT results in the literature. In so doing, we demonstrate that ab initio MD simulations of WDM can be accelerated by up to three orders of magnitude, while retaining ab initio accuracy. We apply this framework to calculate the diffusion coefficients and shear viscosity of CH at a density of 1 g/cm3 and temperatures in the range of 75 000–750 000 K. We find that the self- and inter-diffusion coefficients and the viscosity obey a power law with temperature, and that the diffusion coefficient results suggest a weak coupling between C and H in CH. In addition, we find agreement within standard deviation with previous results for C and CH but disagreement for H, demonstrating the need for ab initio calculations as presented here.