SurGBSA: Learning Representations from Molecular Dynamics Simulations
Source code implementation for "SurgGBSA: Learning Representations From Molecular Dynamics Trajectories".
Jones, WilliamD↗
SEARCH · Engineering Papers
Results for “Molecular dynamics simulation”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Initial hydration process of calcium silicates in Portland cement: A comprehensive comparison from molecular dynamics simulations
As the main components of Portland cement, calcium silicates show substantial differences in their hydration reactivity which have not been fully explained. A comprehensive comparison of the initial hydration process of calcium silicates, namely dicalcium silicate (C{sub 2}S) and tricalcium silicate (C{sub 3}S), was conducted using molecular dynamics simulations. The initial hydration process was divided into three stages using cut-off times of 0.001 ns and 3 ns. The hydration of M{sub 3}-C{sub 3}S (010) was more evident than that of β-C{sub 2}S (100), supported by the hydroxylation degree, radial distribution function, atomic density profile, etc. The coordination number of the surface Ca atoms might be the underlying reason for such a difference. Interactions between cement surfaces and water molecules were mainly characterised by solid OH bonding and Ca-water O bonding. Dissolution of Ca atoms was observed, although quite scarce, while no dissolution of Si atoms was observed.
36 MATERIALS SCIENCE↗
Deep potential molecular dynamics simulations of low-temperature plasma-surface interactions
Machine learning approaches to potential generation for molecular dynamics (MD) simulations of low-temperature plasma-surface interactions could greatly extend the range of chemical systems that can be modeled. Empirical potentials are difficult to generalize to complex combinations of multiple elements with interactions that might include covalent, ionic, and metallic bonds. This work demonstrates that a specific machine learning approach, Deep Potential Molecular Dynamics (DeepMD), can generate potentials that provide a good model of plasma etching in the Si-Cl-Ar system. Comparisons are made between MD results using DeepMD models and empirical potentials, as well as experimental measurements. Pure Si properties predicted by the DeepMD model are in reasonable agreement with experimental results. Simulations of Si bombardment by Ar + ions demonstrate the ability of the DeepMD method to predict sputtering yields as well as the depth of the amorphous-crystalline interface. Etch yields as a function of flux ratio and ion energy for simultaneous Cl 2 and Ar + impacts are in good agreement with previous simulation results and experiment. Predictions of etch yields and etch products during plasma-assisted atomic layer etching of Si-Cl 2 -Ar are shown to be in good agreement with MD predictions using empirical potentials and with experiment. Finally, good agreement was also seen with measurements for the spontaneous etching of Si by Cl atoms at 300 K. Further, the demonstration that DeepMD can reproduce results from MD simulations using empirical potentials is a necessary condition to future efforts to extend the method to a much wider range of systems for which empirical potentials may be difficult or impossible to obtain.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Stoichiometric tuning of lattice flexibility and Na diffusion in NaAlSiO 4 : quasielastic neutron scattering experiment and ab initio molecular dynamics simulations
We have performed quasielastic neutron scattering (QENS) experiments up to 1243 K and ab initio molecular dynamics (AIMD) simulations to investigate the Na diffusion in various phases of NaAlSiO4 (NASO), namely, low-carnegieite (L-NASO; trigonal), high-carnegieite (H-NASO; cubic) and nepheline (N-NASO; hexagonal) phases. The QENS measurements reveal Na ions localized diffusion behavior in L-NASO and N-NASO, but long-range diffusion behavior in H-NASO. Furthermore, the AIMD simulation supplemented the QENS measurements and showed that excess Na ions in H-NASO enhance the host network flexibility and activate the AlO 4 /SiO 4 tetrahedra rotational modes. These framework modes enable the long-range diffusion of Na across a pathway of interstitial sites. The simulations also show Na diffusion in Na-deficient N-NASO through vacant Na sites along the hexagonal c-axis.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Molecular Dynamics Simulations of Calcite Fracture in Water
Calcite (CaCO 3 ) is one of the most common minerals in geologic and engineered systems. It is often in contact with aqueous solutions, causing chemically assisted fracture that is critical to understanding the stability of subsurface systems and manmade structures. Calcite fracture was evaluated with reactive molecular dynamics simulations, including the impacts of crack tip geometry (notch), the presence of water, and surface hydroxyl groups. Chemo-mechanical weakening was assessed by comparing the loads where fracture began to propagate. Our analyses show that in the presence of a notch, the load at which crack growth begins is lower, compared to the effect of water or surface hydroxyls. Additionally, the breaking of two adjacent Ca–O bonds is the kinetic limitation for crack initiation, since transiently broken bonds can reform, not resulting in crack growth. In aqueous environments, fresh (not hydroxylated) calcite surfaces exhibited water strengthening. Manual addition of H + and/or OH – species on the (104) calcite surface resulted in chemo-mechanical weakening of calcite by 9%. Achieving full hydroxylation of the calcite surface was thermodynamically and kinetically limited, with only 0.17–0.01 OH/nm 2 surface hydroxylation observed on the (104) surface at the end of the simulations. In conclusion, the limited reactivity of pure water with the calcite surface restricts the chemo-mechanical effects and suggests that reactions between physiosorbed water and localized structural defects may be dominating the chemo-mechanical process in the studies where water weakening has been reported.
Calcite↗
Molecular dynamics simulations of fission gas xenon (Xe) diffusion at UO 2 grain-boundaries (Rev.1)
The diffusivity of fission gas xenon (Xe) at UO 2 grain-boundaries is one of the most important parameters in mechanistic modeling of fission gas diffusion in UO 2 based nuclear fuels. In this report, we use molecular dynamics simulations to investigate the Xe diffusivity in UO 2 grain-boundaries, employing the many-body potential developed by Cooper, Rushton and Grimes for UO 2 . Three different types of grain-boundaries are investigated, twist Σ5, tilt Σ5, and a random grain-boundary. Diffusion activation energies in the range of 0.39 – 1.46 eV are obtained for the Xe diffusivity. Comparison to results for the uranium vacancy diffusivity from MD simulations employing the same methodology suggests a weak to moderate attractive Xe-uranium vacancy binding energy depending on the grain-boundary type.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Assessing Melting and Solid–Solid Transition Properties of Choline Chloride via Molecular Dynamics Simulations
Choline chloride (ChCl) is used extensively as a hydrogen bond donor in deep eutectic solvents (DESs). However, determining its melting properties experimentally is challenging due to decomposition upon melting, leading to widely varying literature values. Accurate melting properties are crucial for understanding the solid–liquid phase behavior of ChCl-containing DESs. Here, we employ molecular dynamics simulations to compute the phase transitions of ChCl, testing a variety of atomistic force fields. We find that the results are sensitive to the choice of force field, but a melting temperature of 627 K and a melting enthalpy of 7.8 kJ/mol seem most reasonable, in good agreement with some literature values. Furthermore, we suggest these as the likely melting properties of ChCl, though the results are tentative due to limited experimental data for the liquid ChCl phase.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Evaluation of Force Fields for Molecular Dynamics Simulations of Platinum in Bulk and Nanoparticle Forms
Here, understanding the size- and shape-dependent properties of platinum nanoparticles is critical for enabling the design of nanoparticle-based applications with optimal and potentially tunable functionality. Toward this goal, we evaluated nine different empirical potentials with the purpose of accurately modeling faceted platinum nanoparticles using molecular dynamics simulation. First, the potentials were evaluated by computing bulk and surface properties - surface energy, lattice constant, stiffness constants, and the equation of state - and comparing these to prior experimental measurements and quantum mechanics calculations. Then, the potentials were assessed in terms of the stability of cubic and icosahedral nanoparticles with faces in the {100} and {111} planes, respectively. Although none of the force fields predicts all the evaluated properties with perfect accuracy, one potential - the embedded atom method formalism with a specific parameter set - was identified as best able to model platinum in both bulk and nanoparticle forms.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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↗
Capacitance of Carbon Nanotube/Graphene Composite Electrodes with [BMIM + ][BF$_4^–$]/Acetonitrile: Fixed Voltage Molecular Dynamics Simulations
The capacitance of nanoporous carbon electrode materials is dictated by the physical interactions with electrolyte ions and molecules at the accessible interior electrode surface. While significant progress has been made in designing and synthesizing carbon materials with well-defined and relatively homogeneous nanoporosity, the majority of materials remain heterogeneous, and the resulting properties reflect an average over this distribution. In this regard, computer simulations can be a valuable tool to predict or validate structure/property relationships by systematically investigating well-defined, model electrode morphologies. In this work, we utilize fixed-voltage molecular dynamics simulations to predict structure/capacitance relationships for five different model morphologies of carbon nanotube/graphene (CNT/G) composite electrodes with 1-butyl-3-methylimidazolium tetrafluoroborate/acetonitrile electrolyte. The CNT/G electrode models are inspired by experimental “layer-by-layer” syntheses and strike a balance between realism and computational tractability. Comparison between different model electrode architectures elucidates important structure/property relationships. We find that CNT/graphene contact points serve as “hot spots” with significantly enhanced charge separation relative to the rest of the electrode. Furthermore, we demonstrate a specific nanoconfinement motif that provides substantial 3–4$\times$ enhancement of local capacitance, resulting in a ~40% increase of the total electrode differential capacitance. Because the accessible surface area of the model CNT/G electrodes is precisely determined, a comparison of per-area capacitance across systems is unambiguous. Our results thus complement a prior computational demonstration of capacitance enhancement in nanoconfinement while elucidating additional interaction motifs at CNT/G electrochemical interfaces.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Assessment of the impact of reactor residence time distribution on non-equilibrium product selectivity of polypropylene pyrolysis using reactive molecular dynamics simulations
Mass residence time distribution (RTD) is considered to be an important factor controlling the product selectivity in the pyrolysis of biomass and plastic wastes along with the pyrolysis chemistry. However, due to the complex pyrolysis chemistry of biomass and plastic waste, the coupling between the reaction chemistry, RTD, and product selectivity is challenging to understand. Here, we introduce a reaction molecular dynamics-based method to examine pyrolysis chemistry and species timescales to assess the impact of RTD on product selectivity and yield. To validate this method, reactive molecular dynamics simulations were conducted for polypropylene pyrolysis and its non-equilibrium product selectivity using 6 different RTDs. We find that the RTD and the reaction chemistry control the peak non-equilibrium product concentrations. The peak monomer (C 3 H 6 ) concentration during pyrolysis can be increased by up to 25 % by using a narrow RTD in the case of polypropylene pyrolysis. We also find that product selectivity is strongly affected by the average residence time and RTD. This coupling between the reaction chemistry, RTD, and product selectivity highlights the need to understand detailed reaction chemistry to control RTD and optimize non-equilibrium product selectivity during polymer and biomass pyrolysis. The present method provides a new way to design RTD for reactors to reach maximized product selectivity of plastic waste and biomass.
33 ADVANCED PROPULSION SYSTEMS↗
Molecular Origin of Nanoscale Anion Ordering of LiTFSI Electrolytes Revealed through SAXS/WAXS and Molecular Dynamics Simulations
Recent developments in “water-in-salt” electrolytes have precipitated a renewed effort to study imide-based electrolytes. While previous small-/wide-angle X-ray scattering (SAXS/WAXS) studies have attributed the emergence of a low-Q peak in the SAXS profile of aqueous LiTFSI electrolytes to nanometer-scale anion clustering, a molecular-level understanding of the root of these clusters remains unclear. Here, in this study, we combined molecular dynamics simulations and SAXS/WAXS to study the solvation structures of LiTFSI in acetonitrile, methanol, and water. We concluded that hydrogen bonding in water and MeOH stabilizes anion clusters, while nonpolar methyl groups on methanol and acetonitrile interrupt the nanoscale ordering of TFSI anions. This causes LiTFSI in water and MeOH electrolytes to exhibit two low-Q SAXS profile peaks while LiTFSI in acetonitrile exhibits only a single peak below Q = 1 Å –1 . These findings shed light on the underlying molecular origins of nanoscale anion clusters, which may help in the design of the next generation of electrolyte chemistries.
Trojanowski, Lucas [Univ. of Michigan, Ann Arbor, ↗
Non-equilibrium molecular dynamics simulation to evaluate the effect of confinement on fluid flow in silica nanopores
The flow of fluids in nano-confinement has applications in separations, water purification, medical systems and in the recovery of fluids in petroleum systems. It is believed that fluids do not obey continuum laws when flowing in nanopores (or in confinement). This paper attempts to shed light on various nano confinement effects such as fluid-wall interactions, pore size and molecular geometry, using molecular dynamic simulation. Here, water, hexane, and methanol flow behaviors were simulated for pore diameters ranging from 1 to 8 nm. In addition to the density analysis of the confined fluids, the fluid flows in saturated nanopores were simulated by the sectional flow method. Water and methanol molecules were completely stabilized in the 1 nm pore. Hexane molecules could not enter the 1 nm pore, due to geometric considerations. For the 2 – 8 nm pores, all fluids showed reduced flow rate compared to the Hagen–Poiseuille flow, due to an interfacial molecular layer stabilized at the pore surface. Flow reduction observed in these studies is contrary to significant flow enhancements observed for fluid flow in carbon nanotubes of similar dimensions. Water flow showed almost constant stick length for all the pore sizes. Methanol flow had the largest stick length. Hexane flow was reduced because of overcrowding of molecules at the pore surface. The effect of confinement diminished with an increase in pore diameter.
42 ENGINEERING↗
Effects of Composition and Oxidation States on the Structures of Chromium-Containing Sodium Silicate Glasses: Molecular Dynamics Simulations using Machine Learning Interatomic Potentials
Chromium represents a significant challenge for the vitrification of high-level nuclear waste into silicate and borosilicate glasses due to its low solubility and variable oxidation states, which can limit the waste loading due to promotion of crystallization or phase separation during processing. In this study, we modeled chromium containing silicate glasses using molecular dynamics simulations with three machine learning interatomic potentials (MLIPs), MACE, CHGNet, and PFP were employed, to gain insights on glass composition and oxidation states on the structures of these glasses. One of the goals is to evaluate their ability of these MLIPs to accurately represent the general structure of silicate glasses and chromium local environments as a function of chromium oxidation states. Density Functional Theory (DFT) based calculations and experimental data such as neutron structure factors were used to validate the structural models. It was found that the foundation models of all three MLIPs are able to reproduce general structural features of the sodium silicate glass structure consistent with experimental and DFT data, but only CHGNet and PFP can accurately capture the oxidation states and local environment of chromium: tetrahedral for Cr6+ and octahedral for Cr3+. Furthermore, we studied the effect of varying Cr3+/ Cr6+ (Cr3+/Crtotal) ratio and total chromium content using PFP. Our results show that Cr6+ enhances network polymerization by reducing non-bridging oxygens through Na? charge compensation required due to the formation of chromate (CrO42-) species, while Cr³? acts as a network modifier that disrupts connectivity. System size effects on the structural characteristics and chromium environments were also tested using the PFP potential. This work highlights the importance of careful validation on the precision, transferability, and potential of MLIPs for modeling glasses containing transition metal elements that can exist in multiple oxidation states. It is also encouraging to see the foundational models are all three MLFFs are able to reproduce the basic sodium silicate glass structures, while suggesting additional training or refining is needed to improve the description of more complex systems containing transition metals.
Puga, Christina L.↗
Unveiling the lithium-ion transport mechanism in Li{sub 2}ZrCl{sub 6} Solid-State Electrolyte {ital via} deep learning-accelerated molecular dynamics simulations.
Lithium zirconium chlorides (LZCs) present a promising class of cost-effective solid electrolytes for next-generation all-solid-state batteries. The unique crystal structure of LZCs plays a crucial role in facilitating lithium-ion mobility, which further affects the electrochemical performance. To understand the underlying mechanism governing ion transport, we employed deep learning-accelerated molecular dynamics simulation on Li2ZrCl6 (trigonal alpha- and monoclinic beta-LZC), focusing specifically on the zirconium coordination environment. Our results reveal that disordered alpha-LZC exhibits the highest ionic conductivity, while beta-LZC demonstrates significantly lower conductivity, closely aligning with experimental findings. The study confirms that across all phases, lithium migration proceeds via the site-to-site hopping mechanism, where variations in site residence times critically impact the overall ionic conductivity. In alpha-LZCs, lithium ions prefer to anisotropically diffuse across interlayers as the result of a lower energy barrier, driven primarily by collective diffusion. In contrast, lithium ions in beta-LZC primarily isotropically diffuse within the intralayer, hindered by higher energy barriers and determined by individual diffusion. The variation in ZrCl6 2- octahedral unit softening, induced by the specific layered arrangement of zirconium atoms, emerges as a critical determinant of the energy barriers across the LZC phases. These atomic-scale insights into the transport processes provide valuable guidance for the rational design and optimization of LZCs-based electrolytes, accelerating their practical application in advanced energy storage technologies.
Guo, Hanzeng↗
Molecular dynamics simulations of displacement cascades in LiAlO2 and LiAl5O8 ceramics
Abstract Molecular dynamics was employed to investigate the radiation damage due to collision cascades in LiAlO 2 and LiAl 5 O 8 , the latter being a secondary phase formed in the former during irradiation. Atomic displacement cascades were simulated by initiating primary knock-on atoms (PKA) with energy values = 5, 10 and 15 keV and the damage was quantified by the number of Frenkel pairs formed for each species: Li, Al and O. The primary challenges of modeling an ionic system with and without a core–shell model for oxygen atoms were addressed and new findings on the radiation resistance of these ceramics are presented. The working of a variable timestep function and the kinetics in the background of the simulations have been elaborated to highlight the novelty of the simulation approach. More importantly, the key results indicated that LiAlO 2 experiences much more radiation damage than LiAl 5 O 8 , where the number of Li Frenkel pairs in LiAlO 2 was 3–5 times higher than in LiAl 5 O 8 while the number of Frenkel pairs for Al and O in LiAlO 2 are ~ 2 times higher than in LiAl 5 O 8 . The primary reason is high displacement threshold energies (E d ) in LiAl 5 O 8 for Li cations. The greater E d for Li imparts higher resistance to damage during the collision cascade and thus inhibits amorphization in LiAl 5 O 8 . The presented results suggest that LiAl 5 O 8 is likely to maintain structural integrity better than LiAlO 2 in the irradiation conditions studied in this work.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Determination of the Diffusion Coefficients of Binary CH4 and C2H6 in a Supercritical CO2 Environment (500–2000 K and 100–1000 atm) by Molecular Dynamics Simulations
The self-diffusion coefficients of carbonaceous fuels in a supercritical CO2 environment provide transport information that can help us understand the Allam Cycle mechanism at a high pressure of 300 atm. The diffusion coefficients of pure CO2 and binary CO2/CH4 and CO2/C2H6 at high temperatures (500 K~2000 K) and high pressures (100 atm~1000 atm) are determined by molecular dynamics simulations in this study. Increasing the temperature leads to an increase in the diffusion coefficient, and increasing the pressure leads to a decrease in the diffusion coefficients for both methane and ethane. The diffusion coefficient of methane at 300 atm is approximately 0.012 cm2/s at 1000 K and 0.032 cm2/s at 1500 K. The diffusion coefficient of ethane at 300 atm is approximately 0.016 cm2/s at 1000 K and 0.045 cm2/s at 1500 K. The understanding of diffusion coefficients potentially leads to the reduction in fuel consumption and minimization of greenhouse gas emissions in the Allam Cycle.
Energy & Fuels↗
Conformational and oligomeric states of SPOP from small-angle X-ray scattering and molecular dynamics simulations
Speckle-type POZ protein (SPOP) is a substrate adaptor in the ubiquitin proteasome system, and plays important roles in cell-cycle control, development, and cancer pathogenesis. SPOP forms linear higher-order oligomers following an isodesmic self-association model. Oligomerization is essential for SPOP’s multivalent interactions with substrates, which facilitate phase separation and localization to biomolecular condensates. Structural characterization of SPOP in its oligomeric state and in solution is, however, challenging due to the inherent conformational and compositional heterogeneity of the oligomeric species. Here, we develop an approach to simultaneously and self-consistently characterize the conformational ensemble and the distribution of oligomeric states of SPOP by combining small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations. We build initial conformational ensembles of SPOP oligomers using coarse-grained molecular dynamics simulations, and use a Bayesian/maximum entropy approach to refine the ensembles, along with the distribution of oligomeric states, against a concentration series of SAXS experiments. Our results suggest that SPOP oligomers behave as rigid, helical structures in solution, and that a flexible linker region allows SPOP’s substrate-binding domains to extend away from the core of the oligomers. Additionally, our results are in good agreement with previous characterization of the isodesmic self-association of SPOP. In the future, the approach presented here can be extended to other systems to simultaneously characterize structural heterogeneity and self-assembly.
59 BASIC BIOLOGICAL SCIENCES↗