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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

New Nonreactive Force Field for Accurate Molecular Dynamics Simulations of TATB at Extreme Conditions

Insensitive high explosives based on TATB (1,3,5-triamino-2,4,6-trinitrobenzene) are needed in applications when safety is of paramount importance, but the basic material properties that give rise to its insensitivity are not fully understood. Molecular dynamics modeling using empirical force fields (FFs) has been the main route to characterize many complicated dynamical properties of TATB single crystal, but these FFs have not been comprehensively tested at extreme conditions typical of detonation. We collect a benchmark data set of (quasi)static TATB physical properties as determined by experiments and electronic structure calculations and apply this data set to validate four existing TATB FFs along with a new TATB FF that we develop here and denote as the CEA-LLNL-Missouri (CLM) FF. Benchmark data include vibrational spectra, the TATB crystal temperature–pressure–volume equation of state and lattice parameters, properties of TATB crystal polymorphs and transitions to the gaseous and liquid states, dimer energy landscapes, the pressure-dependent elastic tensor, and the energy landscape for inelastic deformation via sliding of TATB crystal layers. As a general assessment, we find that the two existing nonreactive FFs are more accurate in describing TATB’s physical properties compared to the two variants of the ReaxFF reactive FF considered. The new CLM FF is found to consistently yield similar or better agreement with experiments and electronic structure theory than any of the existing FF models, and it presents a distinct improvement in accurately modeling TATB elasticity and equation of state. So this work is expected to help improve the accuracy of FF-based modeling of complicated dynamic responses that ultimately govern the safety and performance characteristics of this material.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data

Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Quantum-Based Approach to Predict Primary Radiation Damage in Polymeric Networks

Initial atomistic-level radiation damage in chemically reactive materials is thought to induce reaction cascades that can result in undesirable degradation of macroscale properties. Ensembles of quantum-based molecular dynamics (QMD) simulations can accurately predict these cascades, but extracting chemical insights from the many underlying trajectories is a labor-intensive process that can require substantial a priori intuition. We develop here a general and automated graph-based approach to extract all chemically distinct structures sampled in QMD simulations and apply our approach to predict primary radiation damage of polydimethylsiloxane (PDMS), the main constituent of silicones. A postprocessing protocol is developed to identify underlying polymer backbone structures as connected components in QMD trajectories. Furthermore, these backbones form a repository of radiation-damaged structures. A scheme for extracting and updating a library of isomorphically distinct structures is proposed to identify the spanning set and aid chemical interpretation of the repository. The analyses are applied to ensembles of cascade QMD simulations in which the four element types in PDMS are selectively excited in primary knock-on atom events. Our approach reveals a much higher degree of combinatorial complexity in this system than was inferred through radiolysis experiments. Probabilities are extracted for radiation-induced network changes including formation of branch points, carbon linkages, cycles, bond scissions, and carbon uptake into the Si–O siloxane backbone network. The general analysis framework presented here is readily extendable to modeling chemical degradation of other polymers and molecular materials and provides a basis for future quantum-informed multiscale modeling of radiation damage.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Graph-EAM: An Interpretable and Efficient Graph Neural Network Potential Framework

The development of deep learning interatomic potentials has enabled efficient and accurate computations in quantum chemistry and materials science, circumventing computationally expensive ab initio calculations. However, the huge number of learnable parameters in deep learning models and their complex architectures hinder physical interpretability and affect the robustness of the derived potential. In this work, we propose graph-EAM, a lightweight graph neural network (GNN) inspired by the empirical embedded atom method to model the interatomic potential of single-element structures. Four material systems: platinum, niobium, silicon, and amorphous-carbon, for which quantum simulation data sets are publicly available, are examined to demonstrate that graph-EAM can achieve high energy and force prediction accuracy-comparable or better than existing state-of-the-art machine learning models-with much fewer parameters. It is also shown that the explicit inclusion of the angular information via three-body atomic density increases the prediction accuracy. In conclusion, the accuracy and efficiency of potentials obtained from graph-EAM can help accelerate the molecular dynamics simulation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Photosynthesis of a Photocatalyst: Single Atom Platinum Captured and Stabilized by an Iron(III) Engineered Defect

Single atom (SA), noble metal catalysts are of interest due to high projected catalytic activity while minimizing cost. Common issues facing many synthesis methodologies include complicated processes, low yields of SA product, and production of mixtures of SA and nanoparticles (NPs). Herein we report a simple, room-temperature synthesis of single Pt-atom decorated, anatase Fe-doped TiO 2 particles that leverages the Fe dopant as an engineered defect site to photodeposit and stabilize atomically dispersed Pt. Both particle morphology and Fe dopant location are based on thermodynamic principles (Gibbs-Wulff construction). CO-DRIFTS (diffuse reflectance infrared Fourier transform spectroscopy) reveals absence of bridge-bonded CO signal, confirming atomically dispersed Pt. XAS (x-ray absorption spectroscopy) of both Pt and Fe indicates Fe-O-Pt bonding that persists through catalytic cycling. Mass balance indicates Pt loading on single particles is 2.5 wt% Pt; single Pt-atom decorated nanoparticle yield is 17%. Pt containing particles show more than an order-of-magnitude increased photo-oxidation efficiency relative to particles containing only Fe. High single-atom-Pt yield, ease of synthesis, and high catalytic activity demonstrate the utility and promise of this method. In conclusion, the principles of this photodeposition synthesis allow for its generalizability towards other SA metals of catalytic interest.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Creation of an Fe 3 P Schreibersite Density Functional Tight Binding Model for Astrobiological Simulations

The mineral schreibersite, e.g., Fe 3 P, is commonly found in iron-rich meteorites and could have served as an abiotic phosphorus source for prebiotic chemistry. However, atomistic calculations of its degradation chemistry generally require quantum simulation approaches, which can be too computationally cumbersome to study sufficient time and length scales for this process. In this regard, we have created a computationally efficient semiempirical quantum density functional tight binding (DFTB) model for iron and phosphorus-containing materials by adopting an existing semiautomated workflow that represents many-body interactions by linear combinations of Chebyshev polynomials. Here, we have utilized a relatively small training set to optimize a DFTB model that is accurate for schreibersite physical and chemical properties, including its bulk properties, surface energies, and water absorption. We then show that our model shows strong transferability to several iron phosphide solids as well as multiple allotropes of iron metal. Our resulting DFTB parametrization will allow us to interrogate schreibersite aqueous decomposition at longer time and length scales than standard quantum approaches, providing for more detailed investigations of its role in prebiotic chemistry on early Earth.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Recent Developments in DFTB+, a Software Package for Efficient Atomistic Quantum Mechanical Simulations

DFTB+ is a flexible, open-source software package developed by its community, designed for fast and efficient atomistic quantum mechanical simulations. It employs various methods that approximate density functional theory (DFT), such as density functional-based tight binding (DFTB) and the extended tight binding (xTB) approach allowing simulations of large systems over extended time scales with reasonable accuracy, while being significantly faster than traditional ab initio methods. In recent years, several new extensions of the DFTB method have been developed and implemented in the DFTB+ program package in order to improve the accuracy and generality of the available simulation results. In this paper, we review those enhancements, show several use case examples and discuss the strengths and limitations of its features.

36 MATERIALS SCIENCE↗
DOE OSTI2020

On the Network Topology of Cross-Linked Acrylate Photopolymers: A Molecular Dynamics Case Study

A reactive molecular dynamics approach is used to simulate cross-linking of acrylate polymer networks. By employing the same force field and reactive scheme and studying three representative multifunctional acrylate monomers, we isolate the importance of the nonreactive moieties within these model monomers. Analyses of reactive trajectories benchmark the estimated gel points, cyclomatic character, and spatially resolved cross-linking tendencies of the acrylates as a function of conversion. The insights into the similarities and differences of the polymerization and resulting networks presented here suggest molecular mechanics as a useful tool in the rational design of photopolymerization resins.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Molecular Origins of the Barriers to Proton Transport in Acidic Aqueous Solutions

The self-consistent iterative multistate empirical valence bond (SCI-MS-EVB) method is used to analyze the structure, thermodynamics, and dynamics of hydrochloric acid solutions. The reorientation timescales of irreversible proton transport are elucidated by simulating 0.43 M, 0.85 M, 1.68 M, and 3.26 M HCl solutions at 270 K, 285 K, 300 K, 315 K, and 330 K. The results indicate increased counter-ion pairing with increasing concentration, which manifests itself via a reduced hydronium oxygen–chloride (O*-Cl) structuring in the radial distribution functions. Increasing ionic concentration also reduces the diffusion of the hydrated excess protons, principally by reducing the contribution of the Grotthuss proton hopping (shuttling) mechanism to the overall diffusion process. In agreement with prior experimental findings, a decrease in the activation energy of reorientation timescales was also observed, which is explicitly explained using activated rate theory and an energy-entropy decomposition of the state-averaged radial distribution functions. Furthermore, these results provide atomistic verification of suggestions from recent two-dimensional infrared spectroscopy experiments that chloride anions (as opposed to hydrated excess protons) create entropic barriers to proton transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Effects of Intercalating Molecules on the Polymer Properties of DNA

Atomic force microscopy (AFM) enables determination of physical properties from single DNA molecules. Insertion of aromatic molecules into the structure of DNA results in morphological changes. However, the accompanying changes to elastic properties due to this insertion are not fully understood. AFM was used to examine the morphological effects of intercalator binding and report changes in the elastic properties of intrinsically straight DNA molecules. The persistence length and polymer extension were characterized in the presence of three intercalating molecules: ethidium bromide and the less well studied chloroquine and acridine. It was found that all three intercalators significantly increased the bending persistence length. In addition, an analysis of the normal bending modes of the static molecules corroborated these results. Furthermore, this approach of measuring binding effects of intercalators on DNA physical properties using a model system of intrinsically straight DNA is applicable to other DNA binding ligands and other modes of DNA interaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Anharmonic phonon dispersion in polyethylene

The second-order Green's function method for anharmonic crystals has been applied to an infinite, periodic chain of polyethylene taking into account up to quartic force constants. The frequency-independent approximation to the Dyson self-energy gives rise to numerous divergent resonances, which are fortuitous. Instead, solving the Dyson equation self-consistently with a frequency-dependent self-energy resists divergences from resonances or zero-frequency acoustic vibrations. Here, the calculated anharmonic phonon dispersion, which nonetheless displays many true resonances, and anharmonic phonon density of states furnish hitherto unknown details that explain smaller features of observed vibrational spectra.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Active-Site Environmental Factors Customize the Photophysics of Photoenzymatic Old Yellow Enzymes

The development of non-natural photoenzymatic systems has reinvigorated the study of photoinduced electron transfer (ET) within protein active sites, providing new and unique platforms for understanding how biological environments affect photochemical processes. Here, we use ultrafast spectroscopy to compare the photoinduced electron transfer in known photoenzymes. 12-Oxophytodienoate reductase 1 (OPR1) is compared to Old Yellow Enzyme 1 (OYE1) and morphinone reductase (MR). The latter enzymes are structurally homologous to OPR1. We find that slight differences in the amino acid composition of the active sites of these proteins determine their distinct electron-transfer dynamics. Our work suggests that the inside of a protein active site is a complex/heterogeneous dielectric network where genetically programmed heterogeneity near the site of biological ET can significantly affect the presence and lifetime of various intermediate states. Our work motivates additional tunability of Old Yellow Enzyme active-site reorganization energy and electron-transfer energetics that could be leveraged for photoenzymatic redox approaches.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Deconstructing the Local Intermolecular Ordering and Dynamics of Liquid Chloroform and Bromoform

Local intermolecular structure and dynamics of the polar molecular liquids chloroform and bromoform are studied by molecular dynamics simulation. Structural distribution functions, including 1- and 2-D pair correlations and dipole contour plots allow direct comparison and show agreement with recent analyses of diffraction experiments. Studies of the haloforms’ reorientational dynamics and longevity of structural features resulting from intermolecular interaction extend previous work toward deeper understanding of the factors controlling these features. Analyses of ensemble average structures and dynamical properties isolate mass, electrostatics, and steric packing as driving forces or contributing factors for the observed ordering and dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Prediction of Self-Diffusion in Binary Fluid Mixtures Using Artificial Neural Networks

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for individual components in binary fluid mixtures. The ANNs were tested on an experimental database of 4328 self-diffusion constants from 131 mixtures containing 75 unique compounds. The presence of strong hydrogen bonding molecules may lead to clustering or dimerization resulting in non-linear diffusive behavior. To address this, self- and binary association energies were calculated for each molecule and mixture to provide information on intermolecular interaction strength and were used as input features to the ANN. An accurate, generalized ANN model was developed with an overall average absolute deviation of 4.1%. Forward input feature selection reveals the importance of critical properties and self-association energies along with other fluid properties. Additional ANNs were developed with subsets of the full input feature set to further investigate the impact of various properties on model performance. The results from two specific mixtures are discussed in additional detail: one providing an example of strong hydrogen bonding and the other an example of extreme pressure changes, with the ANN models predicting self-diffusion well in both cases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Development of a Reactive Force Field for Simulating Photoinitiated Acrylate Polymerization

Light-driven and photo-curable polymer based additive manufacturing (AM) has enormous potential due to its excellent resolution and precision. Acrylated radical chain-growth polymerized resins are widely used in photopolymer AM due to their fast kinetics, and often serve as a departure point for developing other resin materials for photopolymer-based AM technologies. For successful control of the photopolymer resins, the molecular basis of the acrylate free-radical polymerization has to be understood in detail. We present an optimized reactive force field (ReaxFF) for molecular dynamics (MD) simulations of acrylate polymer resins that captures radical polymerization thermodynamics and kinetics. The force field is trained against an extensive training set including density functional theory (DFT) calculations of reaction pathways along the radical polymerization from methyl acrylate to methyl butyrate, bond dissociation energies, and structures and partial charges of several molecules and radicals. We also found that it was critical to train the force field against an incorrect, nonphysical reaction pathway observed in simulations that used parameters not optimized for acrylate polymerization. As a result, the parameterization process utilizes a parallelized search algorithm, and the resulting model can describe polymer resin formation, crosslinking density, conversion rate, and residual monomers of the complex acrylate mixtures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Maximum Entropy Theory of Multiscale Coarse-Graining via Matching Thermodynamic Forces: Application to a Molecular Crystal (TATB)

The MSCG/FM (multiscale coarse-graining via force-matching) approach is an efficient supervised machine learning method to develop microscopically informed coarse-grained (CG) models. Here we present a theory based on the principle of maximum entropy (PME) enveloping the existing MSCG/FM approaches. This theory views the MSCG/FM method as a special case of matching the thermodynamic forces from the extended ensemble described by the set of thermodynamic (relevant) system coordinates. This set may include CG coordinates, the stress tensor, applied external fields, and so forth, and may be characterized by nonequilibrium conditions. Following the presentation of the theory, we discuss the consistent matching of both bonded and nonbonded interactions. The proposed PME formulation is used as a starting point to extend the MSCG/FM method to the constant strain ensemble, which together with the explicit matching of the bonded forces is better suited for coarse-graining anisotropic media at a submolecular resolution. The theory is demonstrated by performing the fine coarse-graining of crystalline 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), a well-known insensitive molecular energetic material, which exhibits highly anisotropic mechanical properties.

1,3,5-triamino-2,4,6-trinitrobenzene↗
DOE OSTI2020

A Metal-on-Metal Growth Approach to Metal–Metal Oxide Core–Shell Nanostructures with Plasmonic Properties

Hybrid core–shell nanoparticles integrate the material properties from individual components; however, the synthesis of core–shell nanoparticles with dissimilar materials remains challenging. Herein, we applied a metal-on-metal thin film growth approach to control the conformal deposition of non-precious metal shells on the Cu-based metal cores to form core–shell structures of metal–metal oxide hybrids (M–M'O x , where M = AuCu 3 or Cu, M' = Fe, Mn, and Ni). The deposition kinetics were controlled by a temperature-regulated thermal decomposition of zerovalent transition metal complexes. It is predicted that the conformal deposition can be promoted by keeping the initial deposition temperature close to the thermal decomposition temperature of the zerovalent precursors. The mechanisms of strain reduction and interdiffusion facilitate conformal deposition over island growth in the synthesis with slow reaction kinetics. This study provides insightful guidance to metal-on-metal growth in solution at the nanoscale and thus the seed-mediated approach to hybrid core–shell structures. The optical properties of these metal–metal oxide hybrids were investigated experimentally and interpreted by theoretical simulations. Despite damping effects, the plasmonic properties of these Cu-based core-metal oxide shell structures may have the potential to enable plasmon-enhanced applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

High Pressure Infiltration/Expulsion of Aqueous NaCl in Planar Hydrophobic Nanopores

Pressure-driven permeation of water in a poorly wettable material results in a conversion of mechanical work into surface free energy representing a new form of energy storage, or absorption. When water is replaced by a concentrated electrolyte solution, the storage capacity of a nanoporous medium becomes comparable to high-end supercapacitors. The addition of salt can also reduce the hysteresis of the infiltration/expulsion cycle. Our molecular simulations provide a theoretical perspective into the mechanisms involved in the process, and underlying structures and interactions in compressed nanoconfined solutions. Specifically, we consider aqueous NaCl in planar confinements of widths of 1.0 nm and 1.64 nm and pressures of up to 3 kbar. Open ensemble Monte Carlo simulations utilizing fractional exchanges of molecules for efficient additions/removal of ions have been utilized in conjunction with pressure-dependent chemical potentials to model bulk phases under pressure. Confinements open to these pressurized bulk, aqueous electrolyte phases show reversibility at narrow pore sizes and irreversibility in wider ones, consistent with experiment, as well as strong hysteresis at both pore size. The addition of salt results in significant increases in the solid/liquid interfacial tension in narrower pores and associated infiltration and expulsion pressures. Furthermore, these changes are consistent with strong desalination effects at the lower pore size observed irrespective of external pressure and initial concentration.

25 ENERGY STORAGE↗