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At least 181 records · Page 10

Minimal Experimental Bias on the Hydrogen Bond Greatly Improves Ab Initio Molecular Dynamics Simulations of Water

Experiment Directed Simulations (EDS) is a method within a class of techniques seeking to improve molecular simulations by minimally biasing the system Hamiltonian to reproduce certain experimental observables. In a previous application of EDS to ab initio molecular dynamics (AIMD) simulation based on electronic density functional theory (DFT), the AIMD simulations of water were biased to reproduce its experimentally derived solvation structure. In particular, by solely biasing the O-O pair correlation functions, other structural and dynamical properties that were not biased were improved. In this work, the hypothesis is tested that directly biasing the OH pair correlation (and hence the H-O∙∙∙H hydrogen bonding), will provide an even better improvement of DFT-based water properties in AIMD simulations. The logic behind this hypothesis is that for most electronic DFT descriptions of water the hydrogen bonding is known to be deficient due to anomalous charge transfer and over polarization in the DFT. Using recent advances to the EDS learning algorithm, we thus train a minimal bias on AIMD water that reproduces the O-H radial distribution function derived from the highly accurate MB-pol model of water. Finally, it is then confirmed that biasing the O-H pair correlation alone can lead to improved AIMD water properties, with structural and dynamical properties in even closer to experiment than the previous EDS-AIMD model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigating structure and dynamics of unentangled poly(dimethyl- co -diphenyl)siloxane via molecular dynamics simulation

Polysiloxane is one of the most important polymeric materials in technological use. Polydimethylsiloxane displays glass-like mechanical properties at low temperatures. Incorporation of phenyl siloxane, via copolymerization for example, improves not only the low-temperature elasticity but also enhances its performance over a wide range of temperatures. Copolymerization with the phenyl component can significantly change the microscopic properties of polysiloxanes, such as chain dynamics and relaxation. However, despite much work in the literature, the influence of such changes is still not clearly understood. In this work, we systematically study the structure and dynamics of random poly(dimethyl- co -diphenyl)siloxane via atomistic molecular dynamics simulations. As the molar ratio Φ of the diphenyl component increases, we find that the size of the linear copolymer chain expands. At the same time, the chain-diffusivity slows down by over an order of magnitudes. In conclusion, the reduced diffusivity appears to be a result of a complex interplay between the structural and dynamic changes induced by phenyl substitution.

36 MATERIALS SCIENCE↗

Comparing theoretical predictions of radiation-free velocities of edge dislocations to molecular dynamics simulations

Transonic defect motion is of interest for high strain-rate plastic deformation as well as for crack propagation. Ever since Eshelby's 1949 prediction [J. D. Eshelby, Proc. Phys. Soc. A 62, 307 (1949)] in the isotropic limit of a “radiation-free” transonic velocity $v$ RF = $\sqrt{2}$c T , where shock waves are absent, there has been speculation about the significance of radiation-free velocities (if they truly exist) for defect mobility. Here, in this work, we argue that they do not play any significant role in dislocation dynamics in metals, based on comparing theoretical predictions of radiation-free velocities for transonic edge dislocations with molecular dynamics simulations for two face-centered cubic metals: Ag, where theory predicts radiation-free states, and Cu, where it does not.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Molecular Dynamics Simulations of Supercritical Carbon Dioxide and Water using TraPPE and SWM4-NDP Force Fields

The increased levels of carbon dioxide (CO 2 ) emissions due to the combustion of fossil fuels and the consequential impact on global climate change have made CO 2 capture, storage, and utilization a significant area of focus for current research. In most electrochemical CO 2 applications, water is used as a proton donor due to its high availability and mobility and use as a polar solvent. Additionally, supercritical CO 2 is a promising avenue for electrochemical applications due to its unique chemical and physical properties. Consequently, understanding the interactions between water and supercritical CO 2 is of great importance for future electrochemical applications. Molecular dynamics (MD) simulation is a powerful tool that enables atomistic-resolution dynamics of molecular systems, which can complement and guide future experimental investigations. This study employed atomistic MD to study the cosolubilities, codiffusivities, and structure of supercritical CO 2 and water systems, with a polarizable water model (SWM4-NDP) and a nonpolarizable CO 2 model (TraPPE). Additionally, ab initio MD simulations were used to better understand how atomistic polarizable/nonpolarizable models compare to explicit modeling of electron densities. The polarizable water model exhibited substantial improvement in water-associated properties. In conclusion, we anticipate the development of a compatible polarizable CO 2 model to yield similar improvement, providing a pathway for realizing novel high-pressure electrochemical systems.

25 ENERGY STORAGE↗

Deformation behavior of annealed Cu64Zr36 metallic glass via molecular dynamics simulations

In the present work, we investigate the isothermal annealing process of Cu 64 Zr 36 metallic glass (MG) by means of molecular dynamics (MD) simulations, and characterize the compression properties under different temperatures and compressive rates. The pair distribution functions, the bond-orientational order, and the cluster-type index method are modeled and analyzed to characterize changes in the structure. Results of the modeling and analysis reveal that the MgZn 2 -type Laves, MgCu 2 -type Laves and five-fold local symmetry structures can be formed during the isothermal holding at 950 K. Study on the compression properties shows that at a fixed strain rate, the yield strength and yield drop all increase with decreasing temperature. At a fixed temperature, however, the increase of the strain rate leads to a noticeable increase in the yield strength at 600 K, but has little effect on yield strength at 10 K. Moreover, the modeling and analysis of the structure at a temperature of 10 K and strain-rate of 5 × 10 7 s -1 demonstrate that the order-disorder transformation initiates the shear band.

36 MATERIALS SCIENCE↗

A coarse-grain force field based on quantum mechanics (CGq FF) for molecular dynamics simulation of poly(ethylene glycol)- block -poly(ε-caprolactone) (PEG- b -PCL) micelles

In order to provide the means to predict from molecular dynamics (MD) simulations the structures of copolymer-based micelles in solution, we developed coarse grain force field (CGq FF) parameters for poly(ethylene glycol) (PEG) and for poly(ε-caprolactone) (PCL). A key advance here is the use of quantum mechanics to train the parameters describing the non-bonded (NB) interactions between the CG beads. The functional forms are the same as the MARTINI CG FF so standard MD codes can be used. Our CGq FF describes well the experimentally observed properties for the polymer–air and polymer–water interfaces, indicating the accuracy of the NB interactions. Additionally, the structural properties (density, radius of gyration ( R g ), and end-to-end distance ( h )) match both experiment and all atom (AA) simulations. We illustrate the application of this CGq FF by following the formation of a spherical micelle from 250 chains of PEG 23 - b -PCL 9 diblock copolymer, each block with molecular weight of 1000 Daltons (10 500 beads, corresponding to 123 250 atoms), in a water box with 119 139 water beads (426 553 water molecules).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energy-efficient, Large-scale Molecular Dynamics Simulations via Hardware- and Algorithm-level Optimization

This work aims to develop a framework for energy-efficient computing that will enable molecular dynamics (MD) simulations of large-scale phenomena with atomic precision and simultaneously remove computational bottlenecks limiting the speed of MD simulations. We seek to implement such an approach through the development of surrogate models for the interatomic force calculation combined with the use of mixed numerical precision formats. For a model system of neutral atoms (only pairwise interactions), significant force calculation efficiency improvements were achieved, without detrimental effects on atomic structures or average energies, using single precision, by developing a surrogate model (deep neural network), and by quantizing this surrogate model. For a model system of charged atoms, the reciprocal-space calculation of electrostatic interactions was identified as the main bottleneck, and the development of a surrogate model should be pursued to achieve an estimated one-order-of-magnitude additional speedup.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Comparison of Chain Conformation of Poly(vinyl alcohol) in Solutions and Melts from Quantum Chemistry Based Molecular Dynamics Simulations

Confirmations of 2,4-dihydroxypentane (DHP), a model molecule for poly(vinyl alcohol), have been studied by quantum chemistry (QC) calculations and molecular dynamics (MD) simulations. QC calculations at the 6-311G MP2 level show the meso tt conformer to be lowest in energy followed by the racemic tg, due to intramolecular hydrogen bond between the hydroxy groups. The Dreiding force field has been modified to reproduce the QC conformer energies for DHP. MD simulations using this force field have been carried out for DHP molecules in the gas phase, melt, and CHCl3 and water solutions. Extensive intramolecular hydrogen bonding is observed for the gas phase and CHCl3 solution, but not for the melt or aqueous solution, Such a condensed phase effect due to intermolecular interactions results in a drastic change in chain conformations, in agreement with experiments.

Jaffe, Richard↗

Molecular Dynamics Simulation of a Multi-Walled Carbon Nanotube Based Gear

We used molecular dynamics to investigate the properties of a multi-walled carbon nanotube based gear. Previous work computationally suggested that molecular gears fashioned from (14,0) single-walled carbon nanotubes operate well at 50-100 gigahertz. The gears were formed from nanotubes with teeth added via a benzyne reaction known to occur with C60. A modified, parallelized version of Brenner's potential was used to model interatomic forces within each molecule. A Leonard-Jones 6-12 potential was used for forces between molecules. The gear in this study was based on the smallest multi-walled nanotube supported by some experimental evidence. Each gear was a (52,0) nanotube surrounding a (37,10) nanotube with approximate 20.4 and 16,8 A radii respectively. These sizes were chosen to be consistent with inter-tube spacing observed by and were slightly larger than graphite inter-layer spacings. The benzyne teeth were attached via 2+4 cycloaddition to exterior of the (52,0) tube. 2+4 bonds were used rather than the 2+2 bonds observed by Hoke since 2+4 bonds are preferred by naphthalene and quantum calculations by Jaffe suggest that 2+4 bonds are preferred on carbon nanotubes of sufficient diameter. One gear was 'powered' by forcing the atoms near the end of the outside buckytube to rotate to simulate a motor. A second gear was allowed to rotate by keeping the atoms near the end of its outside buckytube on a cylinder. The ends of both gears were constrained to stay in an approximately constant position relative to each other, simulating a casing, to insure that the gear teeth meshed. The stiff meshing aromatic gear teeth transferred angular momentum from the powered gear to the driven gear. The simulation was performed in a vacuum and with a software thermostat. Preliminary results suggest that the powered gear had trouble turning the driven gear without slip. The larger radius and greater mass of these gears relative to the (14,0) gears previously studied requires a smaller rotation rate and multiple rows of teeth to avoid excessive force on the gear teeth resulting, in slip and failure of the driven gear to turn. We hope that studies such as these will eventually lead to synthesis of components that can be assembled into atomically precise fullerene machines. These machines, in turn, may someday be used in machine-phase fullerene materials with remarkable properties.

Han, Jie↗

All-atom molecular dynamics simulations of weak polyionic brushes: influence of charge density on the properties of polyelectrolyte chains, brush-supported counterions, and water molecules

All atom molecular dynamics (MD) simulations of planar Na+-counterion-neutralized polyacrylic acid (PAA) brushes are performed for varying degrees of ionization (and thereby varying charge density) and varying grafting density. Variation in the PE charge density (or degree of ionization) and grafting density leads to massive changes of the properties of the PE molecules (quantified by the changes in the height and the mobility of the PE brushes) as well as the local arrangement and distribution of the brush-supported counterions and water molecules within the brushes. The effect on the counterions is manifested by the corresponding variation of the counterion mobility, counterion concentration, extent of counterion binding to the charged site of the PE brushes, water-in-salt-like structure formation, and counterion-water–oxygen radial distribution function within the PE brushes. On the other hand, the effect on water molecules is manifested by the corresponding variation of water–oxygen–water–oxygen RDF, local water density, water–water and water–PE functional group hydrogen bond networks, static dielectric constant of water molecules, orientational tetrahedral order parameter, and water mobility. Enforcing such varying degree of ionization of weak polyelectrolytes is possible by changing the pH of the surrounding medium. Thus, our results provide insights into the changes in microstructure (at the atomistic level) of weak polyionic brushes at varying pH. Finally, we anticipate that this knowledge will prove to be vital for the efficient design of several nano-scale systems employing PE brushes such as nanomechanical gates, current rectifiers, etc.

42 ENGINEERING↗

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↗

Deep potential molecular dynamics simulations of ion-enhanced etching of silicon by atomic chlorine

The continued development of plasma-assisted processing techniques requires a fundamental understanding of plasma-surface interactions. Molecular dynamics (MD) simulations have been employed to complement experimental studies and better understand the properties of such systems. Recently, machine learning (ML) methods have enabled the development of ab initio-based interatomic potentials, which can be generalized to complex combinations of multiple atom types. In this work, we use ML potentials developed using the Deep Potential Molecular Dynamics (DeepMD) framework to provide a model of ion-enhanced etching of Si by Cl atoms. We demonstrate the importance of proper selection of the training data set to the accuracy of the DeepMD model and compare our results to MD results using empirical potentials, as well as to experimental measurements. Exposure of undoped Si at 300 K to thermal Cl atoms yields a steady-state Cl coverage of 1.25 monolayers, which is slightly lower than the value obtained in previous experimental studies. Predictions of Si etch yields by simultaneous Cl atom and Ar + ion impacts as a function of ion energy, neutral to ion flux ratio, and angle of incidence of the ions are in reasonably good agreement with classical MD results and experimental measurements. Finally, etch yields and SiCl x mixed layer thicknesses during simultaneous bombardment of the Si(100) surface by Cl atoms and Cl + ions are in good agreement with experimental data. In conclusion, the present work is a necessary condition for the extension of the DeepMD procedure to more complex systems of interest in plasma-surface interactions.

Artificial neural networks↗

Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties

Polymer electrolytes are promising candidates for the next generation lithium-ion battery technology. Large scale screening of polymer electrolytes is hindered by the significant cost of molecular dynamics (MD) simulation in amorphous systems: the amorphous structure of polymers requires multiple, repeated sampling to reduce noise and the slow relaxation requires long simulation time for convergence. Here, we accelerate the screening with a multi-task graph neural network that learns from a large amount of noisy, unconverged, short MD data and a small number of converged, long MD data. We achieve accurate predictions of 4 different converged properties and screen a space of 6247 polymers that is orders of magnitude larger than previous computational studies. Further, we extract several design principles for polymer electrolytes and provide an open dataset for the community. Our approach could be applicable to a broad class of material discovery problems that involve the simulation of complex, amorphous materials.

36 MATERIALS SCIENCE↗

Understanding the structural mechanics of ligated DNA crystals via molecular dynamics simulation

DNA self-assembly is a highly programmable method to construct arbitrary architectures based on sequence complementarity. Among various constructs, DNA crystals are macroscopic crystalline materials formed by assembling motifs via sticky end association. Due to their high structural integrity and size ranging from tens to hundreds of micrometers, DNA crystals offer unique opportunities to study the structural properties and deformation behaviors of DNA assemblies. For example, enzymatic ligation of sticky ends can selectively seal nicks resulting in more robust structures with enhanced mechanical properties. However, the research efforts have been mostly on experiments involving different motif designs, structural optimization, or new synthesis methods, while their mechanics are not yet fully understood. The complex properties of DNA crystals are difficult to study via experiments alone, and numerical simulation can complement and aid the experiments. The coarse-grained molecular dynamics (MD) simulation is a powerful tool that can probe the mechanics of DNA assemblies. Here, we investigate DNA crystals made of four different motif lengths with various ligation patterns (full ligation, major directions, connectors, and in-plane) using oxDNA, an open-source, coarse-grained MD platform. We found that several distinct deformation stages emerge in response to mechanical loading and that the number and the location of ligated nucleotides can significantly modulate structural behaviors. These findings should be useful for predicting crystal properties and thus improving the design.

DNA crystal↗

Linear Discriminant Analysis-Based Machine Learning and All-Atom Molecular Dynamics Simulations for Probing Electro-Osmotic Transport in Cationic-Polyelectrolyte-Brush-Grafted Nanochannels

Deciphering the correct mechanisms governing certain phenomena in polyelectrolyte (PE) brush grafted systems, revealed through atomistic simulations, is an extremely challenging problem. In a recent study, our all-atom molecular dynamics (MD) simulations revealed a non-linearly large electroosmotic (EOS) flow (in the presence of an applied electric field) in nanochannels grafted with PMETAC [Poly(2-(methacryloyloxy)ethyl trimethylammonium chloride] brushes. Given the lack of any formal procedure that would have directed us to identify the correct factors responsible for such an occurrence, we needed to spend several months and devote significant analyses to unravel the involved mechanisms. In this paper, we propose a Linear Discriminant Analysis (LDA) based Machine Learning (ML) approach to address this gap. At first, we obtain data on certain basic features from the all-atom MD data. These basic features represent the number of atoms of certain species around one atom of another (or same) species. Here, we obtain such data on basic features for a reference case (case of an EOS flow in PMETAC-brush-grafted nanochannels with a smaller electric field) and a perturbed case (case of an EOS flow in PMETAC-brush-grafted nanochannels with a larger electric field) in bins in which the nanochannel half height has been divided into. These datasets are high-dimensional dataset, to which the LDA is applied. This leads to the projection of the data (between the reference and the perturbed states) in a highly separated form on a 1D line. From such LDA calculations, we are able to identify the relative importance of the different basic features in ensuring this separation of the data (between the reference and the perturbed states) on the 1D line. This relative importance of the different basic features is quantified as “importance scores” for the different features, which in turn tell us what to study and where to study. Such knowledge enables us to rapidly identify the key factors responsible for the non-linearly large EOS transport in PMETAC-brush-grafted nanochannels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Si–Cl 2 –Ar + Atomic Layer Etching Window: A Fundamental Study Using Molecular Dynamics Simulations and a Reduced Order Model

Silicon (Si) atomic layer etching (ALE) by alternating exposure to chlorine gas (Cl 2 ) and argon ions (Ar + ) is studied by using molecular dynamics (MD) simulations and a reduced order model (ROM). Here, the purpose of this study is to elucidate the properties of the ALE window, a range of ion energies where the amount of Si etched over a series of cycles is nonzero and nearly independent of ion energy. Experimental studies of the Si–Cl 2 –Ar + ALE system report contradictory results related to the ALE window’s ion energy range. Both MD simulations and the ROM show that there is an ALE window present from approximately 15 to 20 eV for normal incidence argon ions. The Si–Cl 2 –Ar + system, therefore, exhibits a narrow ALE window. The amount of Si etched per cycle is less than one atomic layer because of the higher etch yield of Cl atoms relative to atomic Si and silicon chlorides. A modified version of the ROM with an artificially increased Si physical sputtering threshold energy expands the ALE window, illustrating the importance of the difference in chemical and physical sputtering threshold energies in the ALE window energy range. The ROM is also used to examine the dependence of the EPC on the Ar + ion fluence.

energy↗