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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Carbon-carbon interactions in warm dense titanium carbide

Encouraged by experimental reports of diamond precipitation in carbon-containing materials under warm dense matter conditions and in shock compression experiments, we examine the behavior of carbon in TiC using density functional theory-molecular dynamics simulations. Two polymorphs of TiC are considered, the ambient-pressure B1 ($Fm$$\overline{3}$$m$) structure in which C-C interactions are prevented by geometric constraints, and a high-pressure Cmcm structure in which C atoms condense into zigzag chains. Chemistry-inspired bonding analyses confirm the covalently bound nature of these chains and further illuminate important interatomic interactions in both structures. Upon melting of B1 TiC, new short-range C-C interactions develop in the liquid, while the pre-existing C-C interactions in Cmcm TiC persist in the liquid. Here, the resulting carbon networks in the melt provide a promising environment for eventual diamond nucleation.

Ab initio molecular dynamics↗
DOE OSTI2022

Anharmonic thermodynamic properties and phase boundary across the postperovskite transition in MgSi O 3

To address the effects of lattice anharmonicity across the perovskite to postperovskite transition in MgSiO 3 , we conduct calculations using the phonon quasiparticle (PHQ) approach. The PHQ is based on abinitio molecular dynamics and, in principle, captures full anharmonicity. Free energies in the thermodynamic limit (N → ∞) are computed using temperature-dependent quasiparticle dispersions within the phonon gas model. Systematic results on anharmonic thermodynamic properties and phase boundary are reported. Both the local density approximation and the generalized gradient approximation calculations are performed to provide confident constraints on these properties. Anharmonic effects are demonstrated by comparing results with those obtained using the quasiharmonic approximation (QHA). The inadequacy of the QHA is indicated by its overestimation of thermal expansivity and thermodynamic Grüneisen parameter and its converged isochoric heat capacity in the high-temperature limit. The PHQ phase boundary has a Clapeyron slope (dP/dT) that increases with temperature. This result contrasts with the nearly zero curvature of the QHA phase boundary. Anharmonicity bends the phase boundary to lower temperatures at high pressures. Implications for the double-crossing of the phase boundary by the mantle geotherm are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Identification of efficient and stable solid-solid electrochemical interfaces for Li-S batteries. Final Report

The objective of this work is to develop a better understanding of the interactions between battery components that drive the observed battery performance. Using computational tools at the atomistic level, we elucidate molecular, crystal, and amorphous structures, interfacial structures and reactions, and electrochemical behavior. We focus on Li metal anodes, liquid electrolytes, solid electrolytes, S cathodes, and metal-oxide cathodes, and their corresponding interfaces. Within liquid electrolytes, we study their bulk structure and dynamics, as a function of salt concentration. The analysis allows to understand the formation of localized high concentrated regions as the solvent is substituted by a weakly interacting diluent species. Analysis of the electron distribution yields the reactive behavior at interfaces. Moreover, we employ tools that allow the characterization of ion and electron transport at interfaces, during the processes of solvation and desolvation occurring while cycling. For Sulfur cathodes we elucidate synthesis processes and the role of carbon-sulfur and nitrogen-sulfur interactions not only to provide electronic conductivity but also to define alternative reaction pathways during discharge of Li-S batteries. Full-cell simulations offer new insights regarding the integration of all the battery components. Our studies also include solid electrolytes and their interfaces with Li metal, S-C, and metal-oxide electrodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Role of Dynamic Polarization Interactions in the Electrical Double Layer at Calcite (104) Interfaces with Aqueous Solutions

Reactions at mineral interfaces with aqueous solutions control many geochemical and biogeochemical processes in the Earth’s critical zone. At the molecular level, insights into important properties such as the structure of the electrical double layer (EDL) at specific mineral interfaces continue to improve due to the increasing fidelity of laboratory instrumentation and computational approaches. However, molecular simulation approaches suffer from limited reach into relevant scales of time, length, and system complexity. To span this gap, a novel hybrid approach that couples first principle plane-wave density functional theory (DFT) with classical DFT (cDFT) is demonstrated and applied to calcite (104) interfaces with various electrolytes. In this approach, a region of interest described using DFT interacts with the surrounding medium described using cDFT to arrive at a self-consistent ground state. Benchmarking against experimental observations and entirely first principle DFT simulations demonstrates that this hybrid model efficiently encompasses the key short-range and collective interactions in the EDL. Simulations of calcite (104)/solution interfaces reveal the key static and dynamic polarization interactions that give rise to structuring of ions and water. Ion hydration interactions have the strongest effect on the depth of the first minimum in the density distribution of counterions at the surface, and the position and width of the first density peak is largely determined by the strength of ion-correlation forces. Finer details of ion distributions are controlled by mutual polarization of the calcite surface and interfacial electrolyte. Finally, this new ability to efficiently and rigorously predict EDL structure at mineral surfaces in contact with complex solutions paves the way to accurately modeling sorption, nucleation, dissolution, and growth in realistic systems.

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

Complex Structure of Molten FLiBe (2 Li F – Be F 2 ) Examined by Experimental Neutron Scattering, X-Ray Scattering, and Deep-Neural-Network Based Molecular Dynamics

The use of molten salts as coolants, fuels, and tritium breeding blankets in the next generation of fission and fusion nuclear reactors benefits from furthering the characterization of the molecular structure of molten halide salts, paving the way to predictive capability of the chemical and thermophysical properties of molten salts. Due to its neutronic, chemical, and thermochemical properties, 2 Li F - Be F 2 is a candidate molten salt for several fusion- and fission-reactor designs. We performed neutron and x-ray total-scattering measurements to determine the atomic structure of liquid 2 Li F - Be F 2 . We also performed and neural-network molecular-dynamics simulations to predict the structure obtained by neutron- and x-ray-diffraction experiments. The use of machine learning provides improvements to the efficiency in predicting the structure at a longer length scales than is achievable with simulations at significantly lower computational expense while retaining near accuracy. We found that the NNMD simulations accurately predicted the Be F 4 2 − oligomer formations seen in the experimental first-structure-factor peak. Our combination of high-resolution measurements with large-scale molecular dynamics provided an avenue to explore and experimentally verify the intermediate-range ordering beyond the first-nearest neighbor that has posed too many experimental and computational challenges in previous works. With a deeper understanding of the salt structure and ion ordering, the evolution of salt chemistry over the lifetime of a reactor can be better predicted, which is crucial to the licensing and operation of advanced fission and fusion reactors that employ molten salts. To this end, this work will serve as a reference for future studies of salt structure and macroscopic properties with and without the addition of solutes. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

First-principles equation of state of CHON resin for inertial confinement fusion applications

A wide-range (0 to 1044.0 g/ cm 3 and 0 to 10 9 K) equation-of-state (EOS) table for a CH 1.72 O 0.37 N 0.086 quaternary compound has been constructed based on density-functional theory (DFT) molecular-dynamics (MD) calculations using a combination of Kohn-Sham DFT MD, orbital-free DFT MD, and numerical extrapolation. The first-principles EOS data are compared with predictions of simple models, including the fully ionized ideal gas and the Fermi-degenerate electron gas models, to chart their temperature-density conditions of applicability. The shock Hugoniot, thermodynamic properties, and bulk sound velocities are predicted based on the EOS table and compared to those of C-H compounds. The Hugoniot results show the maximum compression ratio of the C-H-O-N resin is larger than that of CH polystyrene due to the existence of oxygen and nitrogen; while the other properties are similar between CHON and CH. Radiation hydrodynamic simulations have been performed using the table for inertial confinement fusion targets with a CHON ablator and compared with a similar design with CH. Here, the simulations show CHON outperforms CH as the ablator for laser-direct-drive target designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Infrared spectral signatures of interfacial water at TiO 2 –electrolyte interfaces from deep potential molecular dynamics

Vibrational spectroscopy is a powerful tool for probing water at oxide–electrolyte interfaces, but its molecular interpretation can be challenging. Here, we employ deep potential long-range molecular dynamics simulations with layer-resolved spectral analysis to investigate the microscopic origins of the infrared (IR) response of water at the interface with anatase TiO 2 (101), a prototypical oxide surface. The calculated interfacial spectra exhibit characteristic modifications compared to bulk water IR spectra, including enhanced intensities, a red shifted and broadened stretching band, and a higher-frequency shoulder, in qualitative agreement with experiments. Spectral decomposition shows that these signatures originate mainly from the first interfacial water layer, dominated by surface-bound H 2 O at Ti 5C sites, with secondary contributions from the second layer. A moderate salt concentration (0.4 M NaCl) leaves both the interfacial structure and the spectra essentially unchanged, while tuning the pH strongly modulates the spectral intensity. We establish a scaling relation linking the spectral intensity to the surface water dissociation fraction and the dipole moment, both governed by interfacial electric fields. These findings provide a microscopic framework for interpreting IR spectra of oxide–electrolyte interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Switching of Hybrid Improper Ferroelectricity in Oxide Double Perovskites

In ABO 3 -type perovskite oxides with Pnma symmetry, rotation (Q R+ , a 0 a 0 c + ) and tilt (Q T , a – a – c 0 ) of BO 6 octahedra are the two primary order parameters. These order parameters establish an inherent trilinear coupling with anti-ferroelectric A-site displacement (Q AFE ) to form the low-symmetry phase. The symmetry is further lowered in double perovskite oxides (DPOs) due to A/A' cation ordering. It in turn makes these systems polar via hybrid improper ferroelectric mechanism, primarily driven by Q R+ and Q T . Naturally, it has been believed that functionalities such as polarization can also be switched by tuning these primary order parameters. However, mystery around finding switching mechanism still remains. Our study based on density functional theory calculations combined with finite-temperature molecular dynamics simulations shows that the polarization switching is a two-step process, driven by out-of-phase rotation (Q R– , a 0 a 0 c – when Q T = 0 or, a – a – b – when Q T ≠ 0). A series of polar DPOs such as KLnFeOsO 6 [Ln = Sm, Gd, Dy, Tm (lanthanides) and Y (rare earth)], all belonging to P2 1 symmetry, are considered in this investigation. The polarization switching P ($\overrightarrow{P}$) occurs at a very high temperature of ~1150 K through a phase transition, from a polar (P2 1 ) phase with $\overrightarrow{P}$(+) to $\overrightarrow{P}$(-) via a non-polar P4/n phase. The switching itself is metastable in nature. The switching (both polarization and spin state) is only observed for a very short period of time (~23 ps) that poses limitation on using such a mechanism in memory device realization. We demonstrate a concurrent heating–cooling procedure to overcome such shortcoming. In conclusion, simulations conducted at 600 K further imply that long lasting switching can be achieved, at least for 1.2 ns for 600 K, and ideally for an infinite time, if the material is heated just above the T c followed by rapid cooling to a temperature below T c .

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

Development and transferability of neural-network models for plasma-surface interactions

Plasma-surface interactions are increasingly critical to modern technologies; yet, accurate molecular dynamics simulations remain limited by the capabilities of interatomic potentials. Deep Potentials (DPs) promise to revolutionize the field by providing a systematic method for producing accurate interatomic potentials. The primary challenge of DP development is selecting a dataset, which efficiently spans the set of atomic environments one expects to encounter in the subsequent molecular dynamics simulations. The computational cost of density functional theory calculations, which are the typical basis for DP development, makes it impossible to directly verify the quality of a given DP. To address this challenge, we explore the development of a deep-learned interatomic potential, “DeepREBO,” trained to reproduce the behavior of the REBO2 empirical potential, enabling direct validation of training methodology and transferability. Using an active learning framework, we begin with a minimal dataset and iteratively expand it to train a Deep Potential-Smooth Edition model that faithfully reproduces REBO2 results for 25 eV hydrogen bombardment of diamond (001), a particularly challenging case. We show that small, carefully curated datasets can outperform large, unguided ones, with effective models requiring fewer than 15 000 snapshots. Subsequent transferability tests demonstrate that while DeepREBO generalizes well to diamond (111) surfaces, performance degrades for amorphous carbon or higher-energy impacts, highlighting the need for use-case-specific training data. We also evaluate methods to improve short-range repulsion. This study outlines best practices for training robust deep potentials and underscores the importance of dataset design for predictive plasma simulations.

Ab-initio molecular dynamics↗
DOE OSTI2025

When more data hurts: Optimizing data coverage while mitigating diversity-induced underfitting in an ultrafast machine-learned potential

Machine-learned interatomic potentials (MLIPs) are becoming an essential tool in materials modeling. However, optimizing the generation of training data used to parametrize the MLIPs remains a significant challenge. This is because MLIPs can fail when encountering local environments too different from those present in the training data. The difficulty of determining a priori the environments that will be encountered during molecular dynamics simulation necessitates diverse, high-quality training data. Here, this study investigates how training data diversity affects the performance of MLIPs using the Ultra-Fast force field (UF 3 ) to model amorphous silicon nitride. We employ expert and autonomously generated data to create the training data and fit four force field variants to subsets of the data. Our findings reveal a critical balance in training data diversity: insufficient diversity hinders generalization, while excessive diversity can exceed the MLIP's learning capacity, reducing simulation accuracy. Specifically, we found that the UF 3 variant trained on a subset of the training data, in which nitrogen-rich structures were removed, offered vastly better prediction and simulation accuracy than any other variant. By comparing these UF 3 variants, we highlight the nuanced requirements for creating accurate MLIPs, emphasizing the importance of application-specific training data to achieve optimal performance in modeling complex material behaviors.

ab initio molecular dynamics↗
DOE OSTI2024

Critical Role of Framework Flexibility and Disorder in Driving High Ionic Conductivity in LiNbOCl 4

Understanding Li-ion transport is key for the rational design of superionic solid electrolytes with exceptional ionic conductivities. LiNbOCl 4 is reported to be one of the most highly conducting materials in the recently realized new class of soft oxyhalide solid electrolytes, exhibiting an ionic conductivity of ~11 mS·cm -1 . Here, we apply X-ray/neutron diffraction and pair distribution function analysis - coupled with density functional theory/ab-initio molecular dynamics - to determine a structural model that provides a rationale for the high conductivity that we observe experimentally in this nanocrystalline solid. We show that it arises from unusually high framework flexibility at room temperature. This owes to isolated 1-D [NbOCl 4 ] - anionic chains which exhibit energetically favorable orientational disorder that is - in turn - correlated to multiple, disordered and equi-energetic Li + sites in the lattice. As the Li-ions sample the 3-D energy landscape with a fast predicted diffusion coefficient of 5.1 x 10 -7 cm 2 /s at room temperature (σ i calc = 17.4 mS·cm -1 ), the inorganic polymer chains can reorient or vice versa. The activation energy barrier for Li migration through the frustrated energy landscape is especially reduced by the elastic nature of the NbO 2 Cl 4 octahedra evident from very widely dispersed Cl-Nb-Cl bond angles in AIMD snapshots at 300 K. The phonon spectra are predominantly influenced by Cl vibrations in the low energy range, and there is strong overlap between the framework (Cl, Nb) and Li partial pDOS in the region between 1.2 - 4.0 THz. The framework flexibility is also reflected in a relatively low bulk modulus of 22 GPa. In conclusion, our findings pave the way for investigation of future “flex-ion” inorganic solids and open up a new direction for the design of high conductivity, soft solid electrolytes for all-solid-state batteries.

AIMD↗
DOE OSTI2021

Paradigms of frustration in superionic solid electrolytes

Superionic solid electrolytes have widespread use in energy devices, but the fundamental motivations for fast ion conduction are often elusive. In this Perspective, we draw upon atomistic simulations of a wide range of superionic conductors to illustrate some ways frustration can lower diffusion cation barriers in solids. Based on our studies of halides, oxides, sulfides and hydroborates and a survey of published reports, we classify three types of frustration that create competition between different local atomic preferences, thereby flattening the diffusive energy landscape. These include chemical frustration, which derives from competing factors in the anion–cation interaction; structural frustration, which arises from lattice arrangements that induce site distortion or prevent cation ordering; and dynamical frustration, which is associated with temporary fluctuations in the energy landscape due to anion reorientation or cation reconfiguration. For each class of frustration, we provide detailed simulation analyses of various materials to show how ion mobility is facilitated, resulting in stabilizing factors that are both entropic and enthalpic in origin. We propose the use of these categories as a general construct for classifying frustration in superionic conductors and discuss implications for future development of suitable descriptors and improvement strategies.

25 ENERGY STORAGE↗
DOE OSTI2020

Visualizing Anisotropic Oxygen Diffusion in Ceria under Activated Conditions

Oxygen reactivity plays a key role in the performance of ceria-based catalysts. Aberration-corrected transmission electron microscopy and molecular dynamics simulations were used to study the oxygen atom diffusion in ceria under activated conditions. Reactive oxygen atom and its real-time diffusion were visualized. Additionally, the interplay between cerium and oxygen atoms originating from a Coulomb interaction was revealed by the out-of-plane buckling of cerium atoms associated with oxygen transport. Anisotropic oxygen atom diffusion that depends on crystal orientations was discovered, demonstrating a preferential [001] crystallographic diffusion pathway. These findings reveal prospects for applications of anisotropic orientation-relevant fluorite-structured oxides.

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

Development of an ab initio learned model of electron deposition range in deuterium-tritium plasmas through time-dependent density functional theory calculations and machine learning

Accurate hydrodynamic modeling for laser-direct-drive (LDD) inertial-confinement-fusion (ICF) relies on precise calculations of the electron thermal conduction in all target materials. The nonlocal stopping range of electrons in ICF plasmas directly influences thermal conduction; yet, no first principles model exists for the electron mean free path in the conduction-zone regime. This work utilized time-dependent stochastic density-functional theory (TD-sDFT) to calculate the electron stopping power in deuterium-tritium (DT) plasmas at (ρ, T) conditions relevant to the conduction zone and the compressed shell in ICF. Using a combination of our TD-sDFT data and already established analytical models, we developed and trained an artificial neural network to create a global model for the nonlocal electron deposition range, λ E . We compared our machine-learning (ML) based model for λ E to the currently-used modified-Lee-More model in LDD radiation-hydrodynamic codes, such as lilac, and saw an overall decrease in the deposition range. To understand the effects of λ E on LDD ICF implosion dynamics, we implemented the ML-based model into lilac; specifically, we looked at designs consistent with a current experiment on the OMEGA laser and for a newly designed LDD-ICF target for the future OMEGA-Next facility. In both cases, we saw an overall drop in predicted ablation pressure, peak areal density, and neutron yield due to the reduced thermal conduction (smaller λ E ) in DT plasmas. Comparisons with the experiment on OMEGA are also made.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Sulfur-enhanced dynamics of coinage metal(111) surfaces: Step edges versus terraces as locations for metal-sulfur complex formation

The propensity of trace amounts of sulfur adsorbed on coinage metal(111) surfaces to dramatically enhance surface dynamics has been demonstrated by STM observations of accelerated 2D island decay for Cu and Ag. It is generally accepted that this enhancement is due to the formation of adsorbed metal-sulfur complexes, which facilitate surface mass transport of the metal. These complexes were originally proposed to form on terraces following the extraction of metal atoms from step edges and subsequent combination with sulfur on the terraces. However, even when thermodynamically feasible, this mechanism may not be kinetically viable for some complexes due to limited coupling of the complex concentration to the surface diffusion flux of metal atoms. Focusing on the case of Cu, we assess various scenarios where complexes are formed either on terraces or instead directly at step edges, the latter being a new paradigm. In this work, a new pathway is proposed for the formation on terraces. A rich variety of structures incorporating S at step edges exist, which could provide a viable source for complexes, at least from a thermodynamic perspective. However, it is necessary to also assess the activation barrier for complex formation and detachment from step edges. This is facilitated by the nudged-elastic-band analysis of the minimum energy path for this process utilizing machine-learning derived potentials based on density functional theory energetics for the metal-sulfur system.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Insights into Acetic Acid Binding and Ketene Formation on Anatase TiO 2 (101)

Understanding the adsorption and reactivity of carboxylic acids on oxide surfaces is of great interest in catalysis for biomass upgrading via ketonization, a carbon–carbon coupling reaction. Herein, we investigate the adsorption and reaction of acetic acid on anatase TiO 2 (101) using scanning tunneling microscopy, infrared spectroscopy, temperature programmed reaction, and density functional theory calculations. We demonstrate the adsorption of acetic acid can form two intermediates: (1) dissociated, bidentate acetate with an associated bridging hydroxyl, and (2) molecular, monodentate acetic acid. The coexistence of ordered phases with increasing monolayer (ML) saturation coverages consisting of (1) pure acetate (0.5 ML), (2) mixed acetate/acetic acid (0.67 ML), (3) mixed acetate/acetic acid (1.0 ML) and (4) pure acetic acid demonstrates similar energetics for both acetate and acetic acid species. Under ultra-high vacuum conditions, the presence of both monodentate acetic acid and bidentate acetate was observed below room temperature, while solely bidentate acetate was observed up to 575 K. The deprotonation of acetic acid produces water at 280 K, while the thermal decomposition of bidentate acetate produces ketene and acetic acid at 645 K. In conclusion, this model study provides detailed insight into the stability and reactivity of carboxylic acid surface-bound intermediates, which could participate during ketonization reactions for biomass upgrading.

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

Computational Modeling of Battery Materials

This chapter provides a broad overview of the various computational modeling techniques used to gain fundamental insights into coupled electrochemical processes that occur in battery materials at electronic-to-mesoscopic scales. Furthermore, representative successes of these techniques in modeling electrodes, electrolytes, and electrode-electrolyte interfaces are highlighted to establish the current state-of-the-art in the field.

25 ENERGY STORAGE↗