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DOE OSTI2025

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↗

DOE OSTI2023

Structural water in amorphous carbonate minerals: ab initio molecular dynamics simulations of X-ray pair distribution experiments

Water is known to play a controlling role in directing mineralization pathways and stabilizing metastable amorphous intermediates in hydrous carbonate mineral MCO 3 ·nH 2 O systems, where M 2+ is a divalent metal cation. Despite this recognition, the nature of the controls on crystallization is poorly understood, largely owing to the difficulty in characterizing the dynamically disordered structures of amorphous intermediates at the atomic scale. Here, we present a series of atomistic models, derived from ab initio molecular dynamics simulation, across a range of experimentally relevant cations (M = Ca, Mg, Sr) and hydration levels (0 ≤ n ≤ 2). Theoretical simulations of the dependence of the X-ray pair distribution function on the hydration level n show good agreement with available experimental data and thus provide further evidence for a lack of significant nanoscale structure in amorphous carbonates. Upon dehydration, the metal coordination number does not change significantly, but the relative extent of water dissociation increases, indicating that a thermodynamic driving force exists for water dissociation to accompany dehydration. Mg strongly favors monodentate conformation of carbonate ligands and shows a marked preference to exchange monodentate carbonate O for water O upon hydration, whereas Ca and Sr exchange mono- and bidentate carbonate ligands with comparable frequency. Finally, water forms an extensive hydrogen bond network among both water and carbonate groups that exhibits frequent proton transfers for all three cations considered suggesting that proton mobility is likely predominantly due to water dissociation and proton transfer reactions rather than molecular water diffusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

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↗

DOE OSTI2023

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↗

DOE OSTI2020

Investigation of the Effect of Temperature on the Structure of SARS-CoV-2 Spike Protein by Molecular Dynamics Simulations

Statistical and epidemiological data imply temperature sensitivity of the SARS-CoV2 coronavirus. However, the molecular level understanding of the virus structure at different temperature is still not clear. Spike protein is the outermost structural protein of the SARS-CoV-2 virus which interacts with the Angiotensin Converting Enzyme 2 (ACE2), a human receptor, and enters the respiratory system. In this study, we performed an all atom molecular dynamics simulation to study the effect of temperature on the structure of the Spike protein. After 200 ns of simulation at different temperatures, we came across some interesting phenomena exhibited by the protein. We found that the solvent exposed domain of Spike protein, namely S1, is more mobile than the transmembrane domain, S2. Structural studies implied the presence of several charged residues on the surface of N-terminal Domain of S1 which are optimally oriented at 10– 30°C. Bioinformatics analyses indicated that it is capable of binding to other human receptors and should not be disregarded. Additionally, we found that receptor binding motif (RBM), present on the receptor binding domain (RBD) of S1, begins to close around temperature of 40°C and attains a completely closed conformation at 50°C. We also found that the presence of glycan moieties did not influence the observed protein dynamics. Nevertheless, the closed conformation disables its ability to bind to ACE2, due to the burying of its receptor binding residues. Our results clearly show that there are active and inactive states of the protein at different temperatures. This would not only prove beneficial for understanding the fundamental nature of the virus, but would be also useful in the development of vaccines and therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Formation and dissociation of shear-induced high-energy dislocations: insight from molecular dynamics simulations

Solid-phase processing (SPP) allows one to create complex microstructures, not achievable via thermal processing alone. The resulting structures exhibit a rich palette of defects, both thermal and non-thermal, including defect substructures, such as dislocation networks. It is essential to understand the mechanisms of deformation and defect structure formation to guide SPP towards achieving desired microstructures and material properties. In this study, large-scale molecular dynamics simulations are used to investigate the effects of inhomogeneous strain distribution, that mimics deformation conditions of tribological tests, on the evolution of defects under severe shear deformation in polycrystalline Al. Analysis of defect nucleation and reaction pathways reveals that strong geometric constraints suppress the nucleation and slide of low energy dislocation 1/2$\langle110\rangle${111} but promote the nucleation and slide of high energy dislocations, such as [$1\bar1$0] (001) and 1/2 [$1\bar1$$\bar2$]($1\bar1$1). Further, a rough contact surface, characteristic to tribological tests, imposes an inhomogeneous stress field leading to inhomogeneous defect substructures due to location-dependent activation of slip systems. The results suggest that high-energy dislocations can dominate the evolution of grain structures in highly constrained environments, which should be considered in modeling plastic deformation and grain refinement during SPP.

42 ENGINEERING↗

DOE OSTI2022

Predicting the Mechanical Response of Polyhydroxyalkanoate Biopolymers Using Molecular Dynamics Simulations

Polyhydroxyalkanoates (PHAs) have emerged as a promising class of biosynthesizable, biocompatible, and biodegradable polymers to replace petroleum-based plastics for addressing the global plastic pollution problem. Although PHAs offer a wide range of chemical diversity, the structure–property relationships in this class of polymers remain poorly established. In particular, the available experimental data on the mechanical properties is scarce. In this contribution, we have used molecular dynamics simulations employing a recently developed forcefield to predict chemical trends in mechanical properties of PHAs. Specifically, we make predictions for Young’s modulus, and yield stress for a wide range of PHAs that exhibit varying lengths of backbone and side chains as well as different side chain functional groups. Deformation simulations were performed at six different strain rates and six different temperatures to elucidate their influence on the mechanical properties. Our results indicate that Young’s modulus and yield stress decrease systematically with increase in the number of carbon atoms in the side chain as well as in the polymer backbone. In addition, we find that the mechanical properties were strongly correlated with the chemical nature of the functional group. The functional groups that enhance the interchain interactions lead to an enhancement in both the Young’s modulus and yield stress. Finally, we applied the developed methodology to study composition-dependence of the mechanical properties for a selected set of binary and ternary copolymers. Overall, our work not only provides insights into rational design rules for tailoring mechanical properties in PHAs, but also opens up avenues for future high throughput atomistic simulation studies geared towards identifying functional PHA polymer candidates for targeted applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Computing virtual dark-field X-ray microscopy images of complex discrete dislocation structures from large-scale molecular dynamics simulations

Dark-field X-ray microscopy (DFXM) is a novel diffraction-based imaging technique that non-destructively maps the local deformation from crystalline defects in bulk materials. While studies have demonstrated that DFXM can spatially map 3D defect geometries, it is still challenging to interpret DFXM images of the high-dislocation-density systems relevant to macroscopic crystal plasticity. This work develops a scalable forward model to calculate virtual DFXM images for complex discrete dislocation structure(s) (DDS) obtained from atomistic simulations. Our new DDS-DFXM model integrates a non-singular formulation for calculating the local strain from the DDS and an efficient geometrical optics algorithm for computing the DFXM image from the strain field. We apply the model to complex DDS obtained from a large-scale molecular dynamics simulation of compressive loading on single-crystal silicon. Simulated DFXM images exhibit prominent contrast for dislocation features between the multiple slip systems, demonstrating the potential of DFXM to resolve features from dislocation multiplication. In conclusion, the integrated DDS-DFXM model provides a toolbox for DFXM experimental design and image interpretation in the context of bulk crystal plasticity for a range of measurements across shock plasticity and the broader materials science community.

X-ray imaging↗

DOE OSTI2022

Effect of Tethering Anions in Block Copolymer Electrolytes via Molecular Dynamics Simulations

Ion-containing block copolymers (BCPs) are promising solid-state electrolytes as they can combine ion conduction and mechanical robustness via multiple microphases. However, salt-doped BCPs can have low ion conduction and transference number. One strategy to increase transference number is to tether anions to the polymer backbone (creating a single-ion conductor), though this may impact cation mobility. Leveraging coarse-grained molecular dynamics simulations, we compare the effects of ion concentration and polymer dielectric constant on BCPs with and without bonding anions to the chain (without changing any other chemical properties). We find that single-ion BCPs have higher cation conductivity than analogous salt-doped BCPs, especially at moderate ion concentrations. Furthermore, we also compare several structural features of these systems; notably, tethering anions causes the ions to spread more evenly throughout the conducting phase, which is related to improved cation conduction.

25 ENERGY STORAGE↗

NASA NTRS2010

Implementing and Simulating Dynamic Traffic Assignment with Intelligent Transportation Systems in Cube Avenue

As urban populations and traffic congestion levels increase, effective use of information and communication tools and intelligent transportation systems as becoming increasingly important in order to maximize the efficiency of transportation networks. The appropriate placement and employment of these tools within a network is critical to their effectiveness. This presentation proposes and demonstrates the use of a commercial transportation simulation tool to simulate dynamic traffic assignment and rerouting to model route modifications as a result of traffic information.

Foytik, Peter↗

DOE OSTI2021

Molecular dynamics simulations of radiation cascade evolution near cellular dislocation structures in additively manufactured stainless steels

The dislocation dense cellular structures observed in additively manufactured (AM) stainless steels can allow these materials to have enhanced strength and ductility compared to conventionally manufactured materials. Effective design of radiation resistant materials often necessitates creating microstructures containing of a high density of dislocations that act as sinks for radiation induced defects. This work uses molecular dynamics simulations to study the impact of pre-existing defects on radiation damage in stainless steel 316L fabricated by the laser powder bed fusion process. The evolution of synthetically generated dislocations in a crystal system in response to multiple radiation collision cascades suggest that dislocation dense regions reduce the probability of surviving point defects forming clusters. This finding seems to result from the dislocation cores’ ability to absorb point defects, thereby limiting the formation of clusters during the recombination phase. However, after successive cascades, the ability of the dislocation entanglement to prevent defect formation is diminished and defect cluster formation trends to an equilibrium. Accordingly, it is hypothesized that in an experimental setting the dislocation cells will initially act as neutral sinks for point defects, potentially delaying the onset of radiation damage effects; but, these structures will be degraded due to radiation-enhanced diffusion and lose their effectiveness at doses above 1.5–2 displacements per atom. Nevertheless, the ability to produce complex and feature-specific microstructures suggests promise for the design of radiation tolerant materials using AM methods.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Fast neutrino cooling of nuclear pasta in neutron stars: Molecular dynamics simulations

The direct Urca process of rapid neutrino emission can occur in nonuniform nuclear pasta phases that are expected in the inner crusts of neutron stars. Here, the periodic potential for a nucleon in nuclear pasta allows momentum conservation to be satisfied for direct Urca reactions. We improve on earlier work by modeling a rich variety of pasta phases (gnocchi, waffle, lasagna, and anti-spaghetti) with large-scale molecular dynamics simulations. We find that the neutrino luminosity due to direct Urca reactions in nuclear pasta can be 3 to 4 orders of magnitude larger than that from the modified Urca process in the NS core. Thus neutrino radiation from pasta could dominate radiation from the core and this could significantly impact the cooling of neutron stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

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↗

DOE OSTI2025

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, ↗

DOE OSTI2025

Ab-initio informed cluster dynamics simulation of self- and Xe diffusivity in uranium mononitride under irradiation

Uranium mononitride (UN) is one of the ceramic nuclear fuel alternatives to oxide fuels considered for light water reactor and advanced reactor designs, as it presents significant advantages such as high uranium density (better economics) and high thermal conductivity and melting point (increased safety). Self- and fission gas diffusivities need to be better understood, given that they influence key fuel performance phenomena like swelling and fission gas release. Recently, radiation enhanced diffusivity was investigated in UN by means of cluster dynamics simulations relying on empirical potential-based parameterizations, the reliability of which highly depends on the interatomic potential accuracy. Here, in this work, we refine this approach by determining, using ab-initio calculations, the properties of defect clusters containing vacancies, self-interstitials and Xe impurities. We also consider larger clusters than previous studies. The obtained dataset (formation enthalpies, entropies, and migration barriers) is used to parameterize a cluster dynamics model of mobile clusters, and to calculate the defect cluster concentrations under irradiation. This gives us access to the radiation enhanced self- and fission gas diffusivities. Although the resulting diffusivities are close to the values reported in the literature, we find important qualitative differences in the diffusion mechanisms. Capturing the correct mechanisms is crucial to properly describe the chemistry and fission rate dependence of the model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Effect of Solvents on Lignin–Surface Interactions via Molecular Dynamics Simulations

Lignin, an essential building block of lignocellulosic biomass, is a potential abundant source of aromatic monomers for the polymer and chemical industry. Reductive catalytic fractionation (RCF) is one promising process that can produce high yields of phenolic monomers and oligomers from lignin under different catalytic conditions. An important choice in optimizing RCF is the selection of solvent; however, detailed insights into solvent effects on lignin behaviors and interactions remain limited. Here, in this work, we perform all-atom molecular dynamics simulations to study the solvation of lignin, solvent-mediated conformational changes, and the interaction of solvated lignin oligomers with model surfaces. We focus on the behavior of an oligomeric lignin model compound in methanol, ethanol, a binary mixture of ethanol and water, and water at both the RCF reaction temperature (473 K) and room temperature. Analysis of structural features of lignin suggests that these three organic solvent systems favorably solvate lignin, resulting in a more extended conformation suitable for catalytic conversion to valuable chemicals. We further introduce model palladium (Pd) and carbon (C) surfaces to understand how solvent choice impacts adsorption onto a representative catalytic surface and support, and to quantify the competition among the reactant and solvent molecules for the surface. Unbiased simulations suggest strong adsorption of lignin on both Pd and C surfaces at 473 K, with notable solvent-mediated differences in adsorption energies. Additionally, our findings indicate that lignin adsorption is promoted by the entropy change resulting from the displacement of solvent molecules from the surface. This study provides a molecular perspective of adsorption of lignin onto varying surfaces, which is a step towards understanding and optimizing the catalytic conversion of lignin into valuable chemicals.

adsorption↗

DOE OSTI2020

Statistically averaged molecular dynamics simulations of hydrogen diffusion in magnesium and magnesium hydrides

Magnesium has a different crystal structure from its dihydride with hydrogenation leading to a phase transition from the hexagonal closely packed Mg into a tetragonal α-MgH 2 rutile type structure. Such materials exhibit complex hydrogen uptake and release kinetics because hydrogen diffusivities significantly change when the crystal structure changes. To provide a foundational understanding of (de)hydrogenation kinetics that is applicable to all stages of the reaction, we performed statistically averaged molecular dynamics simulations to derive hydrogen diffusivities as a function of temperature and hydrogen content for both magnesium and magnesium hydride. Furthermore, our studies confirm that hydrogen diffusivities in magnesium hydride are much lower than in magnesium, in agreement with experimental data. Additionally, we observe that in either magnesium or magnesium hydride, higher hydrogen compositions result in reduced diffusivities. The latter was not revealed by prior experiments, which were conducted at fixed hydrogen composition. Finally, we discover a non-Arrhenius behavior in magnesium hydride. The physical origin of this behavior is also discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Cell dynamics simulations of coupled charge and magnetic phase transformation in correlated oxides

In this work, we present a comprehensive numerical study on the kinetics of phase transition that is characterized by two nonconserved scalar order parameters coupled by a special linear-quadratic interaction. This particular Ginzburg-Landau theory has been proposed to describe the coupled charge and magnetic transition in nickelates and the collinear stripe phase in cuprates. The inhomogeneous state of such systems at low temperatures consists of magnetic domains separated by quasimetallic domain walls where the charge order is reduced. By performing large-scale cell dynamics simulations, we find a two-stage phase-ordering process in which a short period of independent evolution of the two order parameters is followed by a correlated coarsening process. The long-time growth and coarsening of magnetic domains is shown to follow the Allen-Cahn power law. We further show that the nucleation-and-growth dynamics during phase transformation to the ordered states is well described by the Kolmogorov-Johnson-Mehl-Avrami theory in two dimensions. On the other hand, the presence of quasimetallic magnetic domain walls in the ordered states gives rise to a very different kinetics for transformation to the high-temperature paramagnetic phase. In this scenario, the phase transformation is initiated by the decay of magnetic domain walls into two insulator-metal boundaries, which subsequently move away from each other. Implications of our findings to recent nano-imaging experiments on nickelates are also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗