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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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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Machine-learning interatomic potentials for interfaces in all-solid-state batteries: Perspectives on training data, model selection, and validation

Interfaces play a pivotal role in dictating the performance and reliability of all-solid-state batteries (ASSBs), where complex electro-chemo-mechanical phenomena at grain boundaries (GBs) and interfaces can lead to degradation and failure. Traditional atomistic simulation methods, such as first-principles calculations and classical molecular dynamics, face limitations in modeling these interfaces due to either high computational cost or insufficient transferability to the diverse atomic environments evolving at interfaces. Machine-learning interatomic potentials (MLIPs) have emerged as a transformative approach, enabling large-scale, high-accuracy simulations of disordered and chemically complex systems by leveraging the predictability of machine learning models trained on first-principles data. Recent applications of MLIPs have demonstrated their ability to capture intricate behaviors at ASSB interfaces, including ion transport, interfacial evolution, and degradation mechanisms, with accuracy and efficiency unattainable by conventional methods. This prospective paper presents comprehensive analysis and practical guidance for MLIP development for GBs and interfaces in ASSBs, with a focus on three key pillars: data generation, model selection, and validation. Here, we review the current state of MLIP applications for GBs and interfaces in both general and ASSB-specific materials, highlighting best practices and challenges in constructing diverse and representative datasets, choosing appropriate machine learning architectures, and rigorously validating model performance. We also discuss emerging strategies and opportunities for improved reliability and efficiency of MLIPs to simulate realistic interfaces in ASSBs.

Energy - Storage↗
DOE OSTI2021

Peridynamic Model for Single-Layer Graphene Obtained from Coarse Grained Bond Forces

An ordinary state-based peridynamic material model is proposed for single sheet graphene. The model is calibrated using coarse grained molecular dynamics simulations. The coarse graining method allows the dependence of bond force on bond length to be determined, including the horizon. The peridynamic model allows the horizon to be rescaled, providing a multiscale capability and allowing for substantial reductions in computational cost compared with molecular dynamics. The calibrated peridynamic model is compared to experimental data on the deflection and perforation of a graphene monolayer by an atomic force microscope probe.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Efficient Treatment of Large Active Spaces through Multi-GPU Parallel Implementation of Direct Configuration Interaction

In this study, we have extended our graphical processing unit (GPU)-accelerated direct configuration interaction program to multiple devices, reducing iteration times for configuration spaces of 165 million determinants to only 3 s using NVIDIA P100 GPUs. Similar improvements in the one- and two-particle reduced density matrix formation allow for fast analytical energy gradients and electronic properties. Our parallel algorithm enables the calculation of arbitrarily large configuration spaces (limited only by available system memory), with iteration times of 13 min for an active space of 18 electrons in 18 orbitals (2.4 billion determinants) using six consumer grade NVIDIA 1080Ti GPUs. These advances enable routine molecular dynamics simulations, geometry optimizations, and absorption spectrum calculations for molecules with large configuration spaces, a task that has heretofore required massive computational effort. In this work, we demonstrate the utility of our program by generating the absorption spectrum for diphenyl acetylene at the floating occupation molecular orbital complete active space configuration interaction level of theory. Lastly, several active spaces were investigated to assess the dependence of spectral features on orbital space dimension.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

How Do Ionic Liquids “Fold” Ionenes? Computational and Experimental Analysis of Imidazolium Polymers Based on Ether and Alkyl Chain Variations Dissolved in an Ionic Liquid

Molecular dynamics (MD) simulations and complementary experiments are used here to understand the inter- and intramolecular structure and conformational properties of ionenes (i.e., cationic polymers formed from condensation reactions) dissolved in an ionic liquid (IL), 1-ethyl-3-methylimidazolium bistriflimide [C 2 mim + ][Tf 2 N - ]. The simulated structural properties are benchmarked against experimental analyses of these same polymers, mainly using dynamic light scattering (DLS) experiments. Four different imidazolium ionenes are considered, corresponding to variations in the chemistry and structure of the repeat units including: (1) poly (decylimidazolium) (PD 10 ); (2) poly (tetraethyleneglycolimidazolium) (PE 10 ); (3) alternating copolymer (P(ED) 5 ); and (4) a block copolymer (PE 5 D 5 ). Detailed computational analyses of the polymer structure and conformational properties were performed, including the radius of gyration, end-to-end distance, torsional distributions, and site-site and spatial distribution functions. Overall, there is a competition between intramolecular associations between the imidazolium groups and the ether sites in the polymers versus the intermolecular interactions of the polymer imidazolium groups with the surrounding anion molecules. The polymer with only ether linkages (PE 10 ) results in the most intramolecular interactions, leading to significant coiling behavior and chain contraction. These strong interactions reduce chain flexibility, but they also result in much more linear chain configurations and alignment of the imidazolium groups. The polymer structure is strongly affected as the concentration of alkyl groups is increased, and we find that the polymer architecture (alternating versus block copolymer) also has an important influence. Furthermore, these detailed observations are important for understanding the connection between the molecular design of imidazolium polymers and their emergent structural properties, which could lead to unique opportunities for creating polymer composites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Field-driven ion pairing dynamics in concentrated electrolytes

Here, we investigate ion pairing dynamics in electrolytes driven far from equilibrium using molecular simulations and nonequilibrium rate theory. Focusing on 0.5M LiPF 6 in water and acetonitrile under uniform electric fields, we compute transition path theory observables, including reactive fluxes and mean first-passage times of ion pairing. Moreover, we introduce a dynamical proxy of free-ion population, where its field-induced change is strongly correlated with the nonlinear enhancement of conductivity, yielding an increase of 40% at 50 mV/Å in acetonitrile, compared to that of less than 10% in aqueous electrolytes. Further kinetic analysis elucidates that Onsager’s classical theory substantially overestimates field-induced enhancement of ion pair dissociation in molecular electrolytes. This discrepancy arises from solvent-mediated dynamical pathways and field-induced dielectric decrement that suppress ion pair dissociation within explicit solvents, highlighting that a faithful description of molecular details is essential. Our results provide a molecular interpretation of nonlinear electrolyte transport beyond continuum theories and establish a general framework for quantifying nonequilibrium reaction kinetics in condensed phase systems.

Moon, Seokjin [University of California, Berkeley,↗
DOE OSTI2025

Bayesian prior construction for uncertainty quantification in first-principles statistical mechanics

First-principles statistical mechanics enables the prediction of thermodynamic and kinetic properties of materials, but is computationally expensive. Many approaches require surrogate models to calculate energies within Monte Carlo or molecular dynamics simulations. Inexpensive surrogates such as cluster expansions enable otherwise intractable calculations by interpolating data from higher accuracy methods, such as Density Functional Theory (DFT). Surrogate models introduce uncertainty into downstream calculations, in addition to any uncertainty inherent to DFT calculations. Bayesian frameworks address this by quantifying uncertainty and incorporating expert knowledge through priors. However, constructing effective priors remains challenging. This work introduces and describes practical strategies for building Bayesian cluster expansions, focusing on basis truncation, hyperparameter selection, and ground state replication. We analyze multiple basis truncation schemes, compare cross-validation to the evidence-approximation for hyperparameter optimization, and provide methods to find and enforce ground-state-preserving models through priors. Additionally, we compare the uncertainties between different approximations to DFT (LDA, PBE, SCAN) against the uncertainty introduced with the use of cluster expansion surrogate models. These approaches are demonstrated on the BCC Li x Mg 1-x and Li x Al 1-x alloys, which are both of interest for solid-state Li batteries. Our results provide guidelines for constructing and utilizing Bayesian cluster expansions, thereby improving the transparency of materials modeling. Furthermore, the approaches and insights developed in this work can be transferred to a wide range of cluster expansion surrogate models, including the atomic cluster expansion and related machine-learned interatomic potential architectures.

Alloy theory↗
DOE OSTI2021

Elucidating the Mechanical Energy for Cyclization of a DNA Origami Tile

DNA origami has emerged as a versatile method to synthesize nanostructures with high precision. This bottom-up self-assembly approach can produce not only complex static architectures, but also dynamic reconfigurable structures with tunable properties. While DNA origami has been explored increasingly for diverse applications, such as biomedical and biophysical tools, related mechanics are also under active investigation. Here we studied the structural properties of DNA origami and investigated the energy needed to deform the DNA structures. We used a single-layer rectangular DNA origami tile as a model system and studied its cyclization process. This origami tile was designed with an inherent twist by placing crossovers every 16 base-pairs (bp), corresponding to a helical pitch of 10.67 bp/turn, which is slightly different from that of native B-form DNA (~10.5 bp/turn). We used molecular dynamics (MD) simulations based on a coarse-grained model on an open-source computational platform, oxDNA. We calculated the energies needed to overcome the initial curvature and induce mechanical deformation by applying linear spring forces. We found that the initial curvature may be overcome gradually during cyclization and a total of ~33.1 kcal/mol is required to complete the deformation. These results provide insights into the DNA origami mechanics and should be useful for diverse applications such as adaptive reconfiguration and energy absorption.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Structure and dynamics of SARS-CoV-2 proofreading exoribonuclease ExoN

High-fidelity replication of the large RNA genome of coronaviruses (CoVs) is mediated by a 3'-to-5' exoribonuclease (ExoN) in nonstructural protein 14 (nsp14), which excises nucleotides including antiviral drugs misincorporated by the low-fidelity viral RNA-dependent RNA polymerase (RdRp) and has also been implicated in viral RNA recombination and resistance to innate immunity. Here, we determined a 1.6-Å resolution crystal structure of severe acute respiratory syndrome CoV 2 (SARS-CoV-2) ExoN in complex with its essential cofactor, nsp10. The structure shows a highly basic and concave surface flanking the active site, comprising several Lys residues of nsp14 and the N-terminal amino group of nsp10. Modeling suggests that this basic patch binds to the template strand of double-stranded RNA substrates to position the 3' end of the nascent strand in the ExoN active site, which is corroborated by mutational and computational analyses. We also show that the ExoN activity can rescue a stalled RNA primer poisoned with sofosbuvir and allow RdRp to continue its extension in the presence of the chain-terminating drug, biochemically recapitulating proofreading in SARS-CoV-2 replication. Molecular dynamics simulations further show remarkable flexibility of multidomain nsp14 and suggest that nsp10 stabilizes ExoN for substrate RNA binding to support its exonuclease activity. Our high-resolution structure of the SARS-CoV-2 ExoN–nsp10 complex serves as a platform for future development of anticoronaviral drugs or strategies to attenuate the viral virulence.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2002

Collaborative Simulation Grid: Multiscale Quantum-Mechanical/Classical Atomistic Simulations on Distributed PC Clusters in the US and Japan

A multidisciplinary, collaborative simulation has been performed on a Grid of geographically distributed PC clusters. The multiscale simulation approach seamlessly combines i) atomistic simulation backed on the molecular dynamics (MD) method and ii) quantum mechanical (QM) calculation based on the density functional theory (DFT), so that accurate but less scalable computations are performed only where they are needed. The multiscale MD/QM simulation code has been Grid-enabled using i) a modular, additive hybridization scheme, ii) multiple QM clustering, and iii) computation/communication overlapping. The Gridified MD/QM simulation code has been used to study environmental effects of water molecules on fracture in silicon. A preliminary run of the code has achieved a parallel efficiency of 94% on 25 PCs distributed over 3 PC clusters in the US and Japan, and a larger test involving 154 processors on 5 distributed PC clusters is in progress.

Kikuchi, Hideaki↗
DOE OSTI2025

Field-Driven Simulations to Probe the Impact of Ionic Correlations on Solution Transport Coefficients in Binary, Ternary, and Reciprocal Quaternary Aqueous Electrolytes

Ionic correlations play a critical role in governing transport properties of mixed-salt aqueous electrolyte solutions, yet their quantitative characterization remains challenging, particularly for multicomponent aqueous systems. Here, we develop a general nonequilibrium molecular dynamics framework to efficiently compute Onsager transport coefficients and ionic correlations in mixed-salt aqueous solutions. Using field-driven simulations, we obtain accurate Onsager matrices for LiCl/ KCl, KCl/KBr, and LiBr/KCl electrolyte solutions with significantly reduced computational cost relative to equilibrium Green−Kubo methods. The framework enables direct assessment of how attractive cation−anion and repulsive like-ion interactions contribute to conductivity and salt diffusivity across compositions. While static ion pairing exhibits strong composition dependence, dynamic ion correlations remain nearly invariant, leading to constant deviations from Nernst−Einstein predictions. These results highlight the disconnect between static ion association and dynamic transport correlations, and they establish a transferable approach for analyzing ion transport in complex electrolyte environments relevant to separation processes and electrochemical systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Materials genome innovation for computational software (magics) center

Functional layered material (LM) architectures will dominate nanomaterials science in this century. We have developed theory, modeling, simulation, and software and data tools that enhance understanding and AI guide synthesis, enable characterization of complex structures, and improve capabilities in the predictive design and growth of LMs. Research at the Center has focused on: Computational synthesis and characterization: AI guided synthesis and experimental synthesis of stacked LMs with tailored properties via optimized chemical vapor deposition (CVD) growth and liquid-phase exfoliation; study defects, edges, grain boundaries, wrinkling of atomic layers and their effects on chemical, mechanical, electrical, and optical properties. Far-from-equilibrium processes: Joint experimental and simulation based probe of electronic processes with NAQMD and ultrafast X-ray free-electron laser (XFEL) and ultrafast electron diffraction (UED) facilities at Stanford. Experimentally validate NAQMD by ultrafast electron diffraction and X-ray spectroscopy studies of structural and excited state dynamics, shape fluctuations, and phonon dynamics. Scalable software: Simulation engines for desktop-to-exascale platforms using low-overhead, linear-scaling QMD algorithms; divide-conquer-recombine NAQMD with electronic excitations; extended-Lagrangian reactive molecular dynamics (RMD), machine learning (ML) based neural-network quantum molecular dynamics (NNQMD), and super-state accelerated molecular dynamics (AMD) and kinetic Monte Carlo codes; thermal and electrical transport software; and design 3D architectures of LMs with desired functionality using scalable software. Distribution of software and data, and training: Software and simulation-experimental data generated within the Center are distributed to the materials science community via Berkeley Materials Project (MP) framework. We have also organized three workshops for software distribution and training at USC (Nov. 2017, Mar. 2018) and Gaithersburg, MD (Nov. 2018) to train researchers, with the last one in focused on underrepresented groups, in collaboration with Howard University which is one of the largest HBCUs. The Center supported a total of 46 personnel and 6 undergraduate students. These include 14 faculty, 11 postdoctoral research associates, 20 graduate research assistants, and mentored 6 undergraduate students. This resulted in the publications of 63 research papers that include 46 publications on Reactive and Quantum Dynamics Simulations, 13 publications on Machine Learning for Quantum Materials, and 4 publications on Quantum Computing.

2D Materials↗
NASA NTRS1990

DNA dynamics in aqueous solution: opening the double helix

The opening of a DNA base pair is a simple reaction that is a prerequisite for replication, transcription, and other vital biological functions. Understanding the molecular mechanisms of biological reactions is crucial for predicting and, ultimately, controlling them. Realistic computer simulations of the reactions can provide the needed understanding. To model even the simplest reaction in aqueous solution requires hundreds of hours of supercomputing time. We have used molecular dynamics techniques to simulate fraying of the ends of a six base pair double strand of DNA, [TCGCGA]2, where the four bases of DNA are denoted by T (thymine), C (cytosine), G (guanine), and A (adenine), and to estimate the free energy barrier to this process. The calculations, in which the DNA was surrounded by 2,594 water molecules, required 50 hours of CRAY-2 CPU time for every simulated 100 picoseconds. A free energy barrier to fraying, which is mainly characterized by the movement of adenine away from thymine into aqueous environment, was estimated to be 4 kcal/mol. Another fraying pathway, which leads to stacking between terminal adenine and thymine, was also observed. These detailed pictures of the motions and energetics of DNA base pair opening in water are a first step toward understanding how DNA will interact with any molecule.

NASA Discipline Number 52-20↗
DOE OSTI2026

Dynamic compression and spallation behavior of NbTaTiVZr high-entropy alloy

High-entropy alloys are a new class of materials with promising properties for aerospace and defense applications. The unique behavior of these materials is driven by the complex interactions between dissimilar atoms in a crystal and requires combined theoretical and experimental efforts to unlock their full potential. Here, we evaluate the relationship between the microstructure and the dynamic response of the equiatomic NbTaTiVZr alloy. Specifically, the shock Hugoniot, or equation of state, was measured up to a particle velocity of 0.5 mm μs −1 using gas gun plate impacts. Shock wave profile and incipient spallation experiments were used to characterize wave propagation and damage formation with post-mortem recovery experiments. Molecular dynamics simulations confirm the experimental findings and extend them up to 2.1 mm μs −1 particle velocity. Computational thermodynamic calculation of phase diagram simulations explain details of the material microstructure, which explains the measured strength and experimental damage patterns. Overall, this work provides detailed high-strain-rate characterization of a refractory high-entropy alloy, and more importantly, a framework and demonstration of the utility and necessity of a combined theoretical and experimental approach, outlining the importance of considering processing and manufacturing conditions when evaluating the performance of new materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

$\mathrm{DRAGON}$: A multi-GPU orbital-free density functional theory molecular dynamics simulation package for modeling of warm dense matter

As progress in electronic structure theoretical methods is made, ab initio molecular dynamics (MD) based on orbital-free density functional theory (OF-DFT) is becoming increasingly more successful at substituting the traditional, very accurate but computationally costly Kohn–Sham (KS) approach for simulations of matter at the challenging warm dense matter (WDM) regime. However, despite the significant cost alleviation of eliminating the dependence on the KS orbitals, OF-DFT MD runs require ~10 2 to 10 3 CPU cores running for days, or even weeks, for simulations of systems comprised of 10 2 to 10 3 atoms, depending on thermodynamic conditions. Here we present DRAGON, a multi-GPU OF-DFT MD code for fast and efficient simulations of WDM. With a relatively small allocation of resources (4 to 8 GPU devices) it can provide an order of magnitude speedup for simulations containing $\mathscr{O}$(10 4 ) atoms and target systems composed of $\mathscr{O}$(10 5 ) atoms at conditions within the WDM regime, which is currently outside the capabilities of CPU codes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Post-Marcus Theory and Simulation of Interfacial Charge Transfer Dynamics in Organic Semiconducting Materials (Final Report)

The research program developed, validated and applies predictive computational protocols for calculating charge transfer (CT) rates in complex molecular systems, including molecular dyads and triads in liquid solution and solid-state organic semiconducting (OSC) materials. We have established a transformative computational scheme that goes beyond widely used simplifications, to achieve realistic descriptions of CT processes. The approach properly addresses the contribution of molecular environment at ambient conditions to CT processes. Our approach achieves unique insight on investigated CT processes in relevant experimental efforts. The collaborative team included three principal investigators (PIs), with complimentary expertise in classical molecular dynamics simulations and data science (Cheung), state-of-the-art electronic structure calculations (Dunietz), and cutting-edge theory and simulation techniques for modeling energy, charge and coherence transfer dynamics in molecular systems (Geva).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗