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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

AladynPi – Adaptive Neural Network Molecular Dynamics Simulation Code with Physically Informed Potential: Computational Materials Mini-Application

This report provides an overview and description of commands used in the Computational Materials mini-application, AladynPi. AladynPi is an extension of a previously released mini-application, Aladyn (https://github.com/nasa/aladyn; Yamakov, V.I., and Glaessgen, E.H., NASA/TM-2018-220104). Aladyn and AladynPi are basic molecular dynamics codes written in FORTRAN 2003, which are designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory method. An input for the ANN is a set of structure coefficients, characterizing the local atomic environment of each atom, for which the atomic energy is obtained in the ANN inference process. In Aladyn, the ANN gives directly the energy of interatomic interactions. In AladynPi, the ANN gives optimized parameters for a predefined empirical function, known as bond-order-potential (BOP). The parameterized BOP function is then used to calculate the energy. AladynPi code is being released to serve as a training testbed for students and professors in academia to explore possible optimization algorithms for parallel computing on multicore central processing unit (CPU) computers or computers utilizing manycore architectures based on graphic processing units (GPUs). The effort is supported by the High Performance Computing incubator (HPCi) project at NASA Langley Research Center.

Yamakov, Vesselin I.↗
DOE OSTI2025

Strong adsorption of guanidinium cations to the air–water interface

Combining Deep-UV second harmonic generation spectroscopy with molecular simulations, we confirm and quantify the specific adsorption of guanidinium cations to the air–water interface. Using a Langmuir analysis of measurements at multiple concentrations, we extract the Gibbs free energy of adsorption, finding it larger than typical thermal energies. Molecular simulations clarify the role of polarizability in tuning the thermodynamics of adsorption, and establish the preferential parallel alignment of guanidinium at the air–water interface. As a polyatomic cation, guanidinium represents one of the few examples of a positively charged species to exhibit a propensity for the air-water interface. As such, these results expand on the growing body of work on specific ion adsorption.

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

Elucidating Lithium Transport Mechanisms in Disordered LiF from Machine-Learning Molecular Dynamics Simulations

Lithium fluoride (LiF) is a ubiquitous component of solid- and cathode–electrolyte interphases, yet its functional role remains unclear under the structural and chemical heterogeneity typical of cycling batteries. Here, we systematically quantify how structural disorder, off-stoichiometry, and strain govern Li-ion transport in LiF. Using a machine-learning potential to enable extensive molecular-dynamics sampling, we compare crystalline and amorphous LiF, Li 0.95 F, and LiF 0.95 , and evaluate the impact of small homogeneous deformations. Defect-free crystalline LiF is effectively ion-blocking at 300−500 K, whereas amorphization generates free-volume–assisted percolation pathways that facilitates Li-ion diffusion. At elevated temperatures, thermodynamically driven crystallization disrupts these pathways, leading to non-Arrhenius behavior. In crystalline phases, Li deficiency activates vacancy-mediated diffusion, while in amorphous LiF, transport is governed primarily by network connectivity. Strain is found to have only a marginal effect on Li mobility in both crystalline and amorphous structures.

Batteries↗
DOE OSTI2024

Microscopic Origin of Twist-Dependent Electron Transfer Rate in Bilayer Graphene

Using molecular simulation and continuum dielectric theory, we consider how electrochemical kinetics are modulated by the twist angle in bilayer graphene electrodes. By establishing a connection between the twist angle and the screening length of charge carriers within the electrode, we investigate how tunable metallicity modifies the statistics of the electron transfer energy gap. Constant potential molecular simulations show that the activation free energy for electron transfer increases with screening length, leading to a non-monotonic dependence on the twist angle. Here, the twist angle alters the density of states, tuning the number of thermally accessible channels for electron transfer and the reorganization energy by affecting the stability of the vertically excited state through attenuated image charge interactions. Understanding these effects allows us to express the Marcus rate of interfacial electron transfer as a function of the twist angle in a manner consistent with experimental observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Evaluation of δ-Phase ZrH1.4 to ZrH1.7 Thermal Neutron Scattering Laws Using Ab Initio Molecular Dynamics Simulations

Zirconium hydride is commonly used for next-generation reactor designs due to its excellent hydrogen retention capacity at temperatures below 1000 K. These types of reactors operate at thermal neutron energies and require accurate representation of thermal scattering laws (TSLs) to optimize moderator performance and evaluate the safety indicators for reactor design. In this work, we present an atomic-scale representation of sub-stoichiometric ZrH2−x(0.3≤x≤0.6), which relies on ab initio molecular dynamics (AIMD) in tandem with velocity auto-correlation (VAC) analysis to generate phonon density of states (DOS) for TSL development. The novel NJOY+NCrystal tool, developed by the European Spallation Source community, was utilized to generate the TSL formulations in the A Compact ENDF (ACE) format for its utility in neutron transport software. First, stoichiometric zirconium hydride cross sections were benchmarked with experiments. Then sub-stoichiometric zirconium hydride TSLs were developed. Significant deviations were observed between the new δ-phase ZrH2−x TSLs and the TSLs in the current ENDF release. It was also observed that varying the hydrogen vacancy defect concentration and sites did not cause as significant a change in the TSLs (e.g., ZrH1.4 vs. ZrH1.7) as was caused by the lattice transformation from ϵ- to δ-phase.

42 ENGINEERING↗
DOE OSTI2026

Molecular dynamics simulations of reflection and sputtering behavior of boron under deuterium ion irradiation

Boronization is a commonly used method of wall conditioning in fusion reactors. The application of boron films to the plasma-facing materials results in enhanced plasma performance due to the reduction of intrinsic impurities. This is primarily driven by a reduction in oxygen content that is chemically trapped in the boron film. The reactive nature of these boron films also raises questions concerning interactions with hydrogen isotopes. In this work, boron-deuterium interactions were studied using molecular dynamics (MD). Reactive force field potentials were used to model the chemical interactions between B and D. An amorphous boron substrate was irradiated by D atoms at varying incident energies, 10 eV < E i < 150 eV and angles, 0° < α < 85°. The reflection probability was calculated and compared to results from the commonly-used binary collision approximation (BCA) method. This comparison found that the BCA underestimated the reflection probability at E i < 35 eV and α > 45 ∘ . The source of this discrepancy was found to be the surface binding energy model. The BCA calculation with an isotropic surface binding energy model was more closely aligned to the MD result. This, in combination with a correction function based on the MD results allows for corrections to the reflection probability of deuterium impinging on boron surfaces. The sputtering of the substrate material was also studied. While this study did not contain sufficient events to quantitatively describe the sputtering behavior, some qualitative results emerged: namely, chemical sputtering of B and D-containing molecules (BD, BD 2 , BD 3 ) at low ( < 20 eV) incident deuterium energies. This result suggests that chemical sputtering could be a significant factor in limiting boron coating lifetime when exposed to lower ion energies, such as those in detached plasmas. The results show that chemical interactions should be taken into account when modeling the interactions between D ions and B surfaces.

Boron↗
NASA NTRS2000

Molecular Dynamics Simulations of the Thermal Conductivity of Single-Wall Carbon Nanotubes

Carbon nanotubes (CNT) have very attractive electronic, mechanical. and thermal properties. Recently, measurements of thermal conductivity in single wall CNT mats showed estimated thermal conductivity magnitudes ranging from 17.5 to 58 W/cm-K at room temperature. which are better than bulk graphite. The cylinderical symmetry of CNT leads to large thermal conductivity along the tube axis, additionally, unlike graphite. CNTs can be made into ropes that can be used as heat conducting pipes for nanoscale applications. The thermal conductivity of several single wall carbon nanotubes has been calculated over temperature range from l00 K to 600 K using non-equilibrium molecular dynamics using Tersoff-Brenner potential for C-C interactions. Thermal conductivity of single wall CNTs shows a peaking behavior as a function of temperature. Dependence of the peak position on the chirality and radius of the tube will be discussed and explained in this presentation.

Osman, M.↗
NASA NTRS1995

CARES/LIFE Software Commercialization

The NASA Lewis Research Center has entered into a letter agreement with BIOSYM Technologies Inc. (now merged with Molecular Simulations Inc. (MSI)). Under this agreement, NASA will provide a developmental copy of the CARES/LIFE computer program to BIOSYM for evaluation. This computer code predicts the time-dependent reliability of a thermomechanically loaded component. BIOSYM will become familiar with CARES/LIFE, provide results of computations useful in validating the code, evaluate it for potential commercialization, and submit suggestions for improvements or extensions to the code or its documentation. If BIOSYM/Molecular Simulations reaches a favorable evaluation of CARES/LIFE, NASA will enter into negotiations for a cooperative agreement with BIOSYM/Molecular Simulations to further develop the code--adding features such as a user-friendly interface and other improvements. This agreement would give BIOSYM intellectual property rights in the modified codes, which they could protect and then commercialize. NASA would provide BIOSYM with the NASA-developed source codes and would agree to cooperate with BIOSYM in further developing the code. In return, NASA would receive certain use rights in the modified CARES/LIFE program. Presently BIOSYM Technologies Inc. has been involved with integration issues concerning its merger with Molecular Simulations Inc., since both companies used to compete in the computational chemistry market, and to some degree, in the materials market. Consequently, evaluation of the CARES/LIFE software is on hold for a month or two while the merger is finalized. Their interest in CARES continues, however, and they expect to get back to the evaluation by early November 1995.

Source record↗
DOE OSTI2024

Exploration of Tertiary Structure in Sequence-Defined Polymers Using Molecular Dynamics Simulations

Peptoids are a class of sequence-defined biomimetic polymers with peptide-like backbones and side chains located on backbone nitrogens rather than alpha carbons. These materials demonstrate a strong ability for precise control of single-chain structure, multiunit self-assembly, and macromolecular assembly through careful tuning of sequence due to the diversity of available side chains, although the driving forces behind these assemblies are often not understood. Prior experimental work has shown that linked 15mer peptoids can mimic the protein helical hairpin structure by leveraging the chirality-inducing nature of bulky side chains and hydrophobicity, but there are still gaps in our understanding of the relationship between sequence, stability, and particular secondary or tertiary structure. Here, we present a molecular dynamics (MD) study on the folding behavior of these polymers into hairpins, discussing the differences in structure from sequences with various characteristics in water and acetonitrile, and then compare the handedness preference of common helical motifs between solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Origin of Heating-Induced Softening and Enthalpic Reinforcement in Elastomeric Nanocomposites

Molecular simulations demonstrate that the enthalpic softening of elastomeric nanocomposites upon heating can arise naturally from a Poisson’s ratio mismatch between elastomer and nanoparticle networks, providing a more parsimonious explanation for this phenomenon than the widely accepted interpretation based on glassy interparticle bridging. Despite a century of use, the mechanism of nanoparticle-driven mechanical reinforcement of elastomers is unresolved. Here, a major hypothesis attributes it to glassy interparticle bridges, supported by an observed inversion of the variation of the modulus E(T) on heating – from entropic stiffening in elastomers to enthalpic softening in nanocomposites. Here, molecular simulations reveal that elastomer enthalpic softening can instead emerge from a competition over the preferred volumes between elastomer and nanoparticulate networks. A theory for this competition accounting for softening of the bulk modulus on heating predicts the simulated E(T) inversion, suggesting that reinforcement is driven by a volume-competition mechanism unique to cocontinuous systems of soft and rigid networks.

Biopolymers↗
DOE OSTI2024

Modeling and Optimization of Zeolites for Contaminant Removal from Coal Combustion Impoundment Leachates

Coal Combustion Residual (CCR) landfills in the U.S. can lead to elevated contaminant concentrations in groundwater and runoff, particularly of arsenic, boron, and selenium. Zeolites can be readily synthesized from materials contained within the coal combustion ash impoundments and can be cation-exchanged to enhance adsorption capacity, selectivity, and reactivity. However, the optimization of zeolites becomes a daunting task when accounting for the variety of Si:Al ratios, the species of extra-framework cations present, and the zeolite pore structure. Molecular simulations provide methods to study and guide the design of zeolites for the sorption of contaminants from aqueous solution. In this work, models that predict the sorption of arsenic, boron, and selenium from water using cation-exchanged zeolites. Because of the lack of experimental adsorption data for these species of contaminants, models were parametrized to reproduce the results of first-principles calculations and then used to predict sorption for zeolites for a dataset containing 6000 combinations of zeolites and sorption conditions. Machine learning was used to train a model to predict sorption for materials in this database based on the results of the molecular simulations. Next, a genetic algorithm was used to optimize zeolites for the removal of each contaminant from aqueous solution for individual impoundment sites based on contaminant concentrations reported by the Electric Power Research Institute.

Findley, John↗
NASA NTRS2002

Microgravity: Molecular Dynamics Simulations at the NCCS Probe the Behavior of Liquids in Low Gravity

The life of the very small, whether in something as complicated as a human cell or as simple as a drop of water, is of fundamental scientific interest: By knowing how a tiny amount of material reacts to changes in its environment, scientists maybe able to answer questions about how a bulk of material would react to comparable changes. NASA is in the forefront of computational research into a broad range of basic scientific questions about fluid dynamics and the nature of liquid boundary instability. For example, one important issue for the space program is how drops of water and other materials will behave in the low-gravity environment of space and how the low gravity will affect the transport and containment of these materials. Accurate prediction of this behavior is among the aims of a set of molecular dynamics experiments carried out on the NCCSs Cray supercomputers. In conventional computational studies of materials, matter is treated as continuous - a macroscopic whole without regard to its molecular parts - and the behavior patterns of the matter in various physical environments are studied using well-established differential equations and mathematical parameters based on physical properties such as compressibility density, heat capacity, and vapor pressure of the bulk material.

Source record↗
DOE OSTI2024

Confinement Effects on Proton Transfer in TiO 2 Nanopores from Machine Learning Potential Molecular Dynamics Simulations

Improved understanding of proton transfer in nanopores is critical for a wide range of emerging applications, yet experimentally probing mechanisms and energetics of this process remains a significant challenge. To help reveal details of this process, we developed and applied a machine learning potential derived from first-principles calculations to examine water reactivity and proton transfer in TiO 2 slit-pores. Here, we find that confinement of water within pores smaller than 0.5 nm imposes strong and complex effects on water reactivity and proton transfer. Although the proton transfer mechanism is similar to that at a TiO 2 interface with bulk water, confinement reduces the activation energy of this process, leading to more frequent proton transfer events. This enhanced proton transfer stems from the contraction of oxygen–oxygen distances dictated by the interplay between confinement and hydrophilic interactions. Our simulations also highlight the importance of the surface topology, where faster proton transport is found in the direction where a unique arrangement of surface oxygens enables the formation of an ordered water chain. In a broader context, our study demonstrates that proton transfer in hydrophilic nanopores can be enhanced by controlling pore size, surface chemistry, and topology.

36 MATERIALS SCIENCE↗
DOE OSTI2024

RASPA3

RASPA3, a molecular simulation code for computing adsorption and diffusion in nanoporous materials and thermodynamic and transport properties of fluids. It implements force field based classical Monte Carlo/molecular dynamics in various ensembles. RASPA3 is rewritten from the ground up in C++23 with speed and code readability in mind. Transition-matrix Monte Carlo is added to compute the density of states and free energies. The Monte Carlo code for rigid molecules is based on quaternions, and the atomic positions needed in the energy evaluation are recreated from the center of mass position and quaternion orientation. The expanded ensemble methodology for fractional molecules, with a scaling parameter λ between 0 and 1, now also keeps track of analytic expressions of dU/dλ, allowing independent verification of the chemical potential using thermodynamic integration. The source code is freely available under the MIT license on GitHub.

Dubbeldam, David↗
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↗