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At least 235 records · Page 13

Molecular Dynamic Simulations of Interaction of an AFM Probe with the Surface of an SCN Sample

Molecular dynamic (MD) simulations is conducted in order to estimate forces of probe-substrate interaction in the Atomic Force Microscope (AFM). First a review of available molecular dynamic techniques is given. Implementation of MD simulation is based on an object-oriented code developed at the University of Delft. Modeling of the sample material - succinonitrile (SCN) - is based on the Lennard-Jones potentials. For the polystyrene probe an atomic interaction potential is used. Due to object-oriented structure of the code modification of an atomic interaction potential is straight forward. Calculation of melting temperature is used for validation of the code and of the interaction potentials. Various fitting parameters of the probe-substrate interaction potentials are considered, as potentials fitted to certain properties and temperature ranges may not be reliable for the others. This research provides theoretical foundation for an interpretation of actual measurements of an interaction forces using AFM.

Bune, Adris↗

Molecular Dynamics Simulations of Laser Powered Carbon Nanotube Gears

Dynamics of laser powered carbon nanotube gears is investigated by molecular dynamics simulations with Brenner's hydrocarbon potential. We find that when the frequency of the laser electric field is much less than the intrinsic frequency of the carbon nanotube, the tube exhibits an oscillatory pendulam behavior. However, a unidirectional rotation of the gear with oscillating frequency is observed under conditions of resonance between the laser field and intrinsic gear frequencies. The operating conditions for stable rotations of the nanotube gears, powered by laser electric fields are explored, in these simulations.

Srivastava, Deepak↗

Stochastic symplectic reduced-order modeling for model-form uncertainty quantification in molecular dynamics simulations in various statistical ensembles

Here, this work focuses on the representation of model-form uncertainties in molecular dynamics simulations in various statistical ensembles. In prior contributions, the modeling of such uncertainties was formalized and applied to quantify the impact of, and the error generated by, pair-potential selection in the microcanonical ensemble (NVE). In this work, we extend this formulation and present a linear-subspace reduced-order model for the canonical (NVT) and isobaric (NPT) ensembles. The symplectic reduced-order basis is randomized on the tangent space of the Stiefel manifold to provide topological relationships and capture model-form uncertainty. Using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), we assess the relevance of these stochastic reduced-order atomistic models on canonical problems involving a Lennard-Jones fluid and an argon crystal melt.

42 ENGINEERING↗

Data from "Deep Potential Molecular Dynamics Simulations of Low-Temperature Plasma-Surface Interactions"

Data and input files related to the paper "Deep Potential Molecular Dynamics Simulations of Low-Temperature Plasma-Surface Interactions" (https://doi.org/10.1116/6.0004027). This includes the final DP model used in all simulations, training data set, example input files to run DeepMD (with LAMMPS), and data tables summarizing the results obtained from the simulations.

machine learning models↗

Constant-potential molecular dynamics simulations of molten salt double layers for FLiBe and FLiNaK

We report the results of constant-potential molecular dynamics simulations of the double layer interface between molten 2LiF–BeF 2 (FLiBe) and 23LiF–6NaF–21KF (FLiNaK) fluoride mixtures and idealized solid electrodes. Employing methods similar to those used in studies of chloride double layers, we compute the structure and differential capacitance of molten fluoride electric double layers as a function of applied voltage. The role of molten salt structure is probed through comparisons between FLiBe and FLiNaK, which serve as models for strong and weak associate-forming salts, respectively. In FLiBe, screening involves changes in Be–F–Be angles and alignment of the oligomers parallel to the electrode, while in FLiNaK, the electric field is screened mainly by rearrangement of individual ions, predominantly the polarizable potassium cation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation

Classical molecular dynamics simulates the time evolution of molecular systems through the phase space spanned by the positions and velocities of the constituent atoms. Molecular-level thermodynamic, kinetic, and structural data extracted from the resulting trajectories provide valuable information for the understanding, engineering, and design of biological and molecular materials. The cost of simulating many-body atomic systems makes simulations of large molecules prohibitively expensive, and the high-dimensionality of the resulting trajectories presents a challenge for analysis. Driven by advances in algorithms, hardware, and data availability, there has been a flare of interest in recent years in the applications of machine learning – especially deep learning – to molecular simulation. Furthermore, these techniques have demonstrated great power and flexibility in both extracting mechanistic understanding of the important nonlinear collective variables governing the dynamics of a molecular system, and in furnishing good low-dimensional system representations with which to perform enhanced sampling or develop long-timescale dynamical models. It is the purpose of this article to introduce the key machine learning approaches, describe how they are married with statistical mechanical theory into domain-specific tools, and detail applications of these approaches in understanding and accelerating biomolecular simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗

A classical molecular dynamics simulation method for the formation of “dry” gels from boro-aluminosilicate glass structures

In contact with water, glass transforms into amorphous and porous structures called gels. A simulation method based on classical molecular dynamics is proposed here to mimic “dry” gels forming from initial oxide glass structures. Six glass compositions were investigated. Two behaviours were evidenced depending on the initial glass composition, and in particular on the quantity of elements removed. If a large quantity of soluble elements (B, Na) was removed, it induced an increase in the average pore size within the gels, and the time needed to stabilise the gel structure increased because more local atomic rearrangements occurred. The gel network displayed a higher proportion of Si-Q4 at the expense of Si-Q3 and a lower average ring size compared to the glass network, irrespective of the glass composition. Surface effects were also highlighted in the dry gels, such as the presence of 3-coordinated Al and a decrease in the average angle Si-O-Si and Al-O-Al. Our findings will be compared to both wet gels and experimental data in further studies, to help find the best procedure to simulate such structures.

36 MATERIALS SCIENCE↗

High-temperature chromium diffusion in austenitic stainless steel: Ab initio molecular dynamics simulations

Chromium self-diffusion through stainless steel (SS) matrix and along grain boundaries is an important mechanism controlling SS structural materials corrosion. For this work, Cr diffusion in austenitic SS was simulated using canonical ab initio molecular dynamics with realistic models of type-316 SS bulk, with and without Cr vacancies, and a low-energy Σ3 twin boundary typically observed at active corrosion sites. Cr self-diffusion coefficients at 750 and 850 °C calculated using Einstein’s diffusion equation are 4.2 × 10 –6 and 8.1 × 10 –6 Å 2 ps –1 in pristine bulk, 3.8 × 10 –3 and 5.5 × 10 –3 Å 2 ps –1 in bulk including Cr vacancies, and 9.5 × 10 –2 and 1.0 × 10 –1 Å 2 ps –1 at a Σ3[1 1 1]60° twin boundary.

36 MATERIALS SCIENCE↗

A high-dimensional neural network potential for molecular dynamics simulations of condensed phase nickel and phase transitions

A high-dimensional neural network interatomic potential was developed and used in molecular dynamics simulations of condensed phase Ni and Ni systems with liquid–solid phase coexistence. The reference data set was generated by sampling the potential energy surface over a broad temperature-pressure domain using ab initio MD simulations to train a unified potential. Excellent agreement was achieved between bulk face-centered cubic nickel thermal expansion simulations and relevant experimental data. The same potential also yields accurate structures and diffusivities in the liquid state. The phase transition between liquid and solid phases was simulated using the two-phase interface method. The predicted melting point temperature is within a few kelvins of the literature value. Here, the general methodology could be applied to describe crystals with much more complex phase behaviors.

74 ATOMIC AND MOLECULAR PHYSICS↗

Phase equilibrium of liquid water and hexagonal ice from enhanced sampling molecular dynamics simulations

We study the phase equilibrium between liquid water and ice Ih modeled by the TIP4P/Ice interatomic potential using enhanced sampling molecular dynamics simulations. Our approach is based on the calculation of ice Ih-liquid free energy differences from simulations that visit reversibly both phases. The reversible interconversion is achieved by introducing a static bias potential as a function of an order parameter. The order parameter was tailored to crystallize the hexagonal diamond structure of oxygen in ice Ih. Furthermore, we analyze the effect of the system size on the ice Ih-liquid free energy differences, and we obtain a melting temperature of 270 K in the thermodynamic limit. This result is in agreement with estimates from thermodynamic integration (272 K) and coexistence simulations (270 K). Since the order parameter does not include information about the coordinates of the protons, the spontaneously formed solid configurations contain proton disorder as expected for ice Ih.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure, dynamics, and electrochemistry of choline chloride/ethylene glycol eutectic solvents at an electrode surface explored by molecular dynamics simulations

Choline chloride and ethylene glycol mixtures with 1:2, 1:4, and 1:6 molar ratios on the surfaces of graphite and gold electrodes were studied using classical molecular dynamics simulations. Both neutral and charged electrodes were considered. The liquid composition, solvation structure, molecular orientation, and dynamics at the electrode surface are significantly different from those of the bulk liquid. These properties strongly depend on the electrode material and charge density, whereas they are less sensitive to the overall solvent composition. The effect of the electrode on the composition, structure, and orientation of the liquid fades beyond ∼10 Å from the surface of the electrode. This distance corresponds to about two layers of the structured solvent, despite the fact that the layered structure extends to at least five layers or about 25 Å. However, the electrode influences solvent dynamics over a longer distance. The electrochemical properties of the eutectic solvent at both electrode surfaces were also studied. The simulations captured the experimental differential capacitance shapes for both electrode systems, although the magnitudes and exact shapes differ. The simulations further revealed that the solvent in the first solvation layer can both overscreen and underscreen the electrode charges depending on the electrode material and electrode potential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Dynamics Simulation of Hygroscopic Aging Effects in Epoxy Polymer

The automobile industry is incorporating more lightweight content in car designs to boost fuel-economy. New structural adhesives are needed to mitigate the corrosion and thermal expansion issues associated with joining dissimilar lightweight materials, but adhesive developers lack a fundamental understanding of the chemistry that occurs in the adhesive as the joint ages. In this study, we developed structural adhesive molecular models and applied classical molecular dynamics simulations and density functional theory calculations to gain molecular insights into the influence of water molecules on the properties of epoxy-based adhesives (DGEBA + Jeffamine (JD230)). The simulations were complemented by experimental synthesis and characterization. Our work underscores the impact of water molecules on the local structure of the epoxy network as well as resulting mechanical properties. Water molecules were mainly coordinated with hydroxyls, primary amines and secondary amines, but also weakly coordinated with ether linkages, which were found most probable to be labile. Simulated stress–strain data indicates that increasing the water content deteriorates the mechanical properties. The Young’s modulus decreased by ~ 30% when the water content increased to 3 wt%. We conclude, this integration of molecular-level chemical insights with mechanical property simulations of the hydrated epoxy system and experimental validation holds the promise to advance lightweight joint technologies.

36 MATERIALS SCIENCE↗

Data and Code for Atomic Scale Etching of Diamond: Insights from Molecular Dynamics Simulations

This work investigates the effects of argon ions, hydrogen atoms, and hydrogen ions on the diamond (100) surface using classical molecular dynamics simulations. The purpose of this investigation was to asses plasma processing techniques for applications in quantum device manufacturing. The simulations suggest that combining argon ion smoothing with selective, near threshold energy H removal of amorphous C could be an effective strategy for diamond surface engineering, leading to more reliable and sensitive diamond color center devices. Results were found to differ significantly with interatomic potential, and an analysis of these differences was also carried out. Included in this repository are LAMMPS source files, input scripts, and plotting scripts required to reproduce the data. Also included are the output data required to make all the plots included in the associated publication.

Brenner↗

CO 2 Capture Characteristics of Hyperbranched Poly(alkylene imine): A Molecular Dynamics Simulation Approach

This study explores the CO 2 capture characteristics of hyperbranched poly(ethylenimine) (HB-PEI) and poly- (propyleneimine) (HB-PPI) through molecular dynamics simulations using density functional theory-calibrated force fields. Key features such as density, free volume, glass transition temperature, CO 2 /H 2 O distribution, and molecular diffusion are systematically investigated to elucidate structure−function relationships under dry and hydrated conditions. HB-PEI demonstrates a slightly higher density and lower free volume compared to HB-PPI yet shows superior CO 2 capture due to the high amine concentration. Glass transition analysis indicates a higher thermal mobility in HBPEI, enhancing the CO 2 diffusivity. Pair correlation and coordination analyses confirm a stronger affinity of CO 2 with primary and secondary amines, particularly in hydrated environments where water competes with CO 2 for binding sites. Despite its more compact structure, HB-PEI outperformed HB-PPI in CO 2 and H 2 O transport, as confirmed by higher diffusion coefficients across all hydration levels. These findings highlight a critical balance among polymer architecture, amine accessibility, and hydration in designing next-generation solid amine sorbents for efficient direct air capture applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Dynamics Simulation and Cryo-Electron Microscopy Investigation of AOT Surfactant Structure at the Hydrated Mica Surface

Structural properties of the anionic surfactant dioctyl sodium sulfosuccinate (AOT or Aerosol-OT) adsorbed on the mica surface were investigated by molecular dynamics simulation, including the effect of surface loading in the presence of monovalent and divalent cations. The simulations confirmed recent neutron reflectivity experiments that revealed the binding of anionic surfactant to the negatively charged surface via adsorbed cations. At low loading, cylindrical micelles formed on the surface, with sulfate head groups bound to the surface by water molecules or adsorbed cations. Cation bridging was observed in the presence of weakly hydrating monovalent cations, while sulfate groups interacted with strongly hydrating divalent cations through water bridges. The adsorbed micelle structure was confirmed experimentally with cryogenic electronic microscopy, which revealed micelles approximately 2 nm in diameter at the basal surface. At higher AOT loading, the simulations reveal adsorbed bilayers with similar surface binding mechanisms. Adsorbed micelles were slightly thicker (2.2–3.0 nm) than the corresponding bilayers (2.0–2.4 nm). Upon heating the low loading systems from 300 K to 350 K, the adsorbed micelles transformed to a more planar configuration resembling bilayers. The driving force for this transition is an increase in the number of sulfate head groups interacting directly with adsorbed cations.

58 GEOSCIENCES↗

Molecular Modeling and Molecular Dynamics Simulation of a Packed and Intact Bacterial Microcompartment

Bacterial microcompartments (BMCs) are protein-bound organelles found in some bacteria which encapsulate enzymes for enhanced catalytic activity. These compartments spatially sequester enzymes within semipermeable shell proteins and are packed full of enzyme cargoes and metabolites as they fulfill their function. Coupling together recent SAXS and proteomics work, it is possible to develop molecular models for these microcompartments and interrogate enzyme and metabolite dynamics within. Our primary goal of this study is to quantify the permeability of metabolite glyceraldehyde-3-phosphate (G3P) and dihydroxyacetone phosphate (DHAP) across the BMC shell through classical molecular dynamics simulation. The Haliangium ochraceum model of BMC shell (PDB: 6MZX) was used to model an intact BMC of approximately 10 million atoms. Working at this scale presented its own challenges in managing large data sets, with multiple challenges and hardware advances discussed that facilitated this work. Over approximately 750 ns of aggregate simulation, we see multiple permeation events for these metabolites that were added at high concentration through the pores present within BMC shell tiles. When compared to independent permeability estimates for the same metabolites determined through replica exchange umbrella sampling simulations, the permeabilities varied by approximately 3 orders of magnitude. Regardless, the permeability coefficients for both G3P and DHAP are highly similar and very high, such that only very small concentration gradients can be maintained across the BMC shell between the cytosol and BMC interior. The large simulation systems also facilitated comparisons for molecular diffusivity in the crowded environment within the BMC shell. By our estimates, the viscosity within a packed BMC shell is at least 10-fold higher than it would be in neat solution and is the real driver for varying permeability estimates we obtained through simulation. These findings will be used as design inputs for future bioengineering efforts to make products from BMCs, highlighting how permeable BMC shells can be.

Diffusion↗

Collective Vibrational Strong Coupling Effects on Molecular Vibrational Relaxation and Energy Transfer: Numerical Insights via Cavity Molecular Dynamics Simulations**

Abstract For a small fraction of hot CO 2 molecules immersed in a liquid‐phase CO 2 thermal bath, classical cavity molecular dynamics simulations show that forming collective vibrational strong coupling (VSC) between the C=O asymmetric stretch of CO 2 molecules and a cavity mode accelerates hot‐molecule relaxation. This acceleration stems from the fact that polaritons can be transiently excited during the nonequilibrium process, which facilitates intermolecular vibrational energy transfer. The VSC effects on these rates 1) resonantly depend on the cavity mode detuning, 2) cooperatively depend on Rabi splitting, and 3) collectively scale with the number of hot molecules. For larger cavity volumes, the average VSC effect per molecule can remain meaningful for up to N ≈10 4 molecules forming VSC. Moreover, the transiently excited lower polariton prefers to relax by transferring its energy to the tail of the molecular energy distribution rather than distributing it equally to all thermal molecules. As far as the parameter dependence is concerned, the vibrational relaxation data presented here appear analogous to VSC catalysis in Fabry–Pérot microcavities.

Li, Tao E.↗

Collective Vibrational Strong Coupling Effects on Molecular Vibrational Relaxation and Energy Transfer: Numerical Insights via Cavity Molecular Dynamics Simulations**

Abstract For a small fraction of hot CO 2 molecules immersed in a liquid‐phase CO 2 thermal bath, classical cavity molecular dynamics simulations show that forming collective vibrational strong coupling (VSC) between the C=O asymmetric stretch of CO 2 molecules and a cavity mode accelerates hot‐molecule relaxation. This acceleration stems from the fact that polaritons can be transiently excited during the nonequilibrium process, which facilitates intermolecular vibrational energy transfer. The VSC effects on these rates 1) resonantly depend on the cavity mode detuning, 2) cooperatively depend on Rabi splitting, and 3) collectively scale with the number of hot molecules. For larger cavity volumes, the average VSC effect per molecule can remain meaningful for up to N ≈10 4 molecules forming VSC. Moreover, the transiently excited lower polariton prefers to relax by transferring its energy to the tail of the molecular energy distribution rather than distributing it equally to all thermal molecules. As far as the parameter dependence is concerned, the vibrational relaxation data presented here appear analogous to VSC catalysis in Fabry–Pérot microcavities.

Li, Tao E.↗