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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Assessing Melting and Solid–Solid Transition Properties of Choline Chloride via Molecular Dynamics Simulations

Choline chloride (ChCl) is used extensively as a hydrogen bond donor in deep eutectic solvents (DESs). However, determining its melting properties experimentally is challenging due to decomposition upon melting, leading to widely varying literature values. Accurate melting properties are crucial for understanding the solid–liquid phase behavior of ChCl-containing DESs. Here, we employ molecular dynamics simulations to compute the phase transitions of ChCl, testing a variety of atomistic force fields. We find that the results are sensitive to the choice of force field, but a melting temperature of 627 K and a melting enthalpy of 7.8 kJ/mol seem most reasonable, in good agreement with some literature values. Furthermore, we suggest these as the likely melting properties of ChCl, though the results are tentative due to limited experimental data for the liquid ChCl phase.

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

Machine learning the metastable phase diagram of covalently bonded carbon

Abstract Conventional phase diagram generation involves experimentation to provide an initial estimate of the set of thermodynamically accessible phases and their boundaries, followed by use of phenomenological models to interpolate between the available experimental data points and extrapolate to experimentally inaccessible regions. Such an approach, combined with high throughput first-principles calculations and data-mining techniques, has led to exhaustive thermodynamic databases (e.g. compatible with the CALPHAD method), albeit focused on the reduced set of phases observed at distinct thermodynamic equilibria. In contrast, materials during their synthesis, operation, or processing, may not reach their thermodynamic equilibrium state but, instead, remain trapped in a local (metastable) free energy minimum, which may exhibit desirable properties. Here, we introduce an automated workflow that integrates first-principles physics and atomistic simulations with machine learning (ML), and high-performance computing to allow rapid exploration of the metastable phases to construct “metastable” phase diagrams for materials far-from-equilibrium. Using carbon as a prototypical system, we demonstrate automated metastable phase diagram construction to map hundreds of metastable states ranging from near equilibrium to far-from-equilibrium (400 meV/atom). We incorporate the free energy calculations into a neural-network-based learning of the equations of state that allows for efficient construction of metastable phase diagrams. We use the metastable phase diagram and identify domains of relative stability and synthesizability of metastable materials. High temperature high pressure experiments using a diamond anvil cell on graphite sample coupled with high-resolution transmission electron microscopy (HRTEM) confirm our metastable phase predictions. In particular, we identify the previously ambiguous structure of n -diamond as a cubic-analog of diaphite-like lonsdaelite phase.

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

Continuum-Level Modeling of Li-Ion Battery SEI by Upscaling Atomistically Informed Reaction Mechanisms

Understanding and controlling solid-electrolyte interphase (SEI) formation to stabilize cell performance is a significant challenge for next-generation Li-ion battery technologies. In recent years, computational modeling has become an essential tool in providing fundamental insights into SEI properties and dynamics. However, neither atomistic nor continuum-level approaches alone can capture the complexities of SEI chemistry across all relevant length and time scales. In this work, a continuum-level model is developed that is informed by reaction mechanisms obtained from first-principle calculations. The atomistically informed continuum-level model is used to understand electrolyte degradation, including the decomposition of ethylene carbonate (EC), ethyl methyl carbonate (EMC), and fluoroethylene carbonate (FEC). The model presented here is the most chemically complex continuum-level SEI model in the literature to date. The SEI model is calibrated against experimental irreversible leakage currents and shows qualitative agreement with expected SEI growth trends. The model framework is expected to accelerate fundamental understanding of SEI formation, facilitate mechanism development feedback, and dynamically interact with experimental insights.

continuum-level model↗
DOE OSTI2022

Theoretical Perspective on Operando Spectroscopy of Fluxional Nanocatalysts

Improvements in operando spectroscopy have enabled the catalysis community to investigate the dynamic nature of catalysts under operating conditions with increasing detail. Still, the highly dynamic nature of some catalysts, such as fluxional supported subnano clusters, presents a formidable challenge even for the most state-of-the-art techniques. Here, the reason is that such fluxional catalytic interfaces contain a variety of thermally accessible states. Operando spectroscopies used in catalysis generally fall into two categories: ensemble-based techniques, which provide spectra containing the signals of the entire ensemble of states of the catalyst and are not necessarily dominated by the most active species, and localized techniques, which provide atomistic-level information about the dynamics of active sites in a very small area, which might not include the most active species. Combining many different kinds of techniques can provide detailed insight; however, we propose that effective utilization of specific computational techniques and approaches within the fluxionality paradigm can fill the gap and enable atomistic characterization of the most relevant catalytic sites.

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

Capture efficiency and bias from the defect dynamics near grain boundaries in BCC Fe using mesoscale simulations

The capture efficiency describes the capability of a sink, such as a grain boundary (GB), dislocation, and void, to absorb point defects (PDs). The bias defines the difference in capture efficiency between the absorption of a vacancy and dumbbell at a sink. Complete kinetic information on PDs, including diffusion barriers and diffusion orientations, as well as accurate saddle points, are needed to determine the capture efficiency and bias at a sink accurately, which is computationally demanding. Here, in the present study, the Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC) method was used to investigate the defect dynamics of PDs near different types of grain boundaries (GBs) (with both $\langle$100$\rangle$ and $\langle$110$\rangle$ families) accurately in body-centered cubic (BCC) iron (Fe). The capture efficiency, sink strength, and bias factor of different types of GBs were determined in Fe, which, different from traditional rate theory estimation, showed a distinct capture efficiency, sink strength, and bias in different GBs. The results demonstrate a strong positive correlation between the capture efficiency and the GB strain width, instead of the GB misorientation, GB energy, or GB-PD binding energy, which have been investigated previously. This work provides valuable insight into the radiation-induced microstructural evolution of GBs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Vibronic and Environmental Effects in Simulations of Optical Spectroscopy

Including both environmental and vibronic effects is important for accurate simulation of optical spectra, but combining these effects remains computationally challenging. We outline two approaches that consider both the explicit atomistic environment and the vibronic transitions. Both phenomena are responsible for spectral shapes in linear spectroscopy and the electronic evolution measured in nonlinear spectroscopy. The first approach utilizes snapshots of chromophore-environment configurations for which chromophore normal modes are determined. We outline various approximations for this static approach that assumes harmonic potentials and ignores dynamic system-environment coupling. The second approach obtains excitation energies for a series of time-correlated snapshots. This dynamic approach relies on the accurate truncation of the cumulant expansion but treats the dynamics of the chromophore and the environment on equal footing. Both approaches show significant potential for making strides toward more accurate optical spectroscopy simulations of complex condensed phase systems.

Chemistry↗
DOE OSTI2021

Self-Healing Ceramics and Mechanical Metamaterials

We performed large scale molecular dynamics (MD) simulations and reactive & quantum molecular dynamics simulations to investigate: (1) faceting, grain growth, and crack healing in ceramics; (2) stress-release mechanism and healing in fibers; and (3) mechanical properties of two-dimensional metamaterials. We also designed highly accurate interatomic potentials and forces using artificial neural networks (ANN) and first-principles molecular dynamics simulation data for use in our MD and reactive MD simulations. We demonstrated the efficacy of modeling quantum materials atomistic simulation data using unsupervised deep learning approaches on a quantum computer. These achievements are elaborated in the following sections.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-scale modeling of wastage layer formation in metallic fuel cladding

Fuel-cladding chemical interaction (FCCI) is a major concern for U-Zr metallic fuels' performance, primarily due to the formation of a brittle layer (wastage) in the cladding. This brittle layer, resulting from intermetallic compounds between cladding constituents Fe, Cr, and lanthanide fission products, significantly impacts the cladding's mechanical integrity. Recent efforts focus on developing a mechanistic modeling framework to understand lanthanide production, transport to the fuel-cladding interface, and phase transformation to intermetallic phases. A multi-scale computational approach has been used to calculate lanthanide transport rates, with atomistic calculations determining Nd diffusivities through the solid fuel matrix and along pore surfaces. These diffusivities inform a mesoscale model to determine an effective diffusion coefficient, accounting for porosity and infiltration with bond sodium. This effective diffusivity is used in engineering-scale simulations via the BISON fuel performance code, which has been validated against EBR-II and FFTF reactor experiments.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Computational Methods in Heterogeneous Catalysis

The unprecedented ability of computations to probe atomic-level details of catalytic systems holds immense promise for the fundamentals-based bottom-up design of novel heterogeneous catalysts, which are at the heart of the chemical and energy sectors of industry. Here, we critically analyze recent advances in computational heterogeneous catalysis. First, we will survey the progress in electronic structure methods and atomistic catalyst models employed, which have enabled the catalysis community to build increasingly intricate, realistic, and accurate models of the active sites of supported transition-metal catalysts. We then review developments in microkinetic modeling, specifically mean-field microkinetic models and kinetic Monte Carlo simulations, which bridge the gap between nanoscale computational insights and macroscale experimental kinetics data with increasing fidelity. Here, we finally review the advancements in theoretical methods for accelerating catalyst design and discovery. Throughout the review, we provide ample examples of applications, discuss remaining challenges, and provide our outlook for the near future.

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

Insights into the Properties of MXenes and MXene Analogs from Atomistic Simulation

We review the properties that have been predicted for MXenes and MXene analogs from computational simulation with a focus on structural and electronic properties, energy storage, and ion transport. Methods considered range from quantum mechanical approaches to classical molecular dynamics. We conclude by reviewing current limitations and outstanding questions for simulation and MXene properties that have been little explored to-date.

Muraleedharan, Murali Gopal↗
DOE OSTI2022

An Eulerian crystal plasticity framework for modeling large anisotropic deformations in energetic materials under shocks

Here, this paper demonstrates a novel Eulerian computational framework for modeling anisotropic elastoplastic deformations of organic crystalline energetic materials (EM) under shocks. While Eulerian formulations are advantageous for handling large deformations, constitutive laws in such formulations have been limited to isotropic elastoplastic models, which may not fully capture the shock response of crystalline EM. The present Eulerian framework for high-strain rates, large deformation material dynamics of EM incorporates anisotropic isochoric elasticity via a hypo-elastic constitutive law and visco-plastic single-crystal models. The calculations are validated against atomistic calculations and experimental data and benchmarked against Lagrangian (finite element) crystal plasticity computations for shock-propagation in a monoclinic organic crystal, octahydro-1,3,5,7-tetranitro-1,3,5,7 tetrazocine (β-HMX). The Cauchy stress components and the resolved shear stresses calculated using the present Eulerian approach are shown to be in good agreement with the Lagrangian computations for different crystal orientations. The Eulerian framework is then used for computations of shock-induced inert void collapse in β-HMX to study the effects of crystal orientations on hotspot formation under different loading intensities. The computations show that the hotspot temperature distributions and the collapse profiles are sensitive to the crystal orientations at lower impact velocities (viz., 500 m/s); when the impact velocity is increased to 1000 m/s, the collapse is predominantly hydrodynamic and the role of anisotropy is modest. The present methodology will be useful to simulate energy localization in shocked porous energetic material microstructures and other situations where large deformations of single and polycrystals govern the thermomechanical response.

42 ENGINEERING↗
DOE OSTI2020

Comparative modeling of the disregistry and Peierls stress for dissociated edge and screw dislocations in Al

Many elementary deformation processes in metals involve the motion of dislocations. The planes of glide and specific processes dislocations prefer depend heavily on their atomic core structures. Atomistic simulations are desirable for dislocation modeling but their application to even sub-micron scale problems is in general computationally costly. Accordingly, continuum-based approaches, such as the phase-field microelasticity, phase-field dislocation dynamics (PFDD), generalized Peierls–Nabarro (GPN) models, and the concurrent atomistic–continuum (CAC) method, have attracted increasing attention in the field of dislocation modeling because they well represent both short-range cores interactions and long-range stress fields of dislocations. To better understand their similarities and differences, it is useful to compare these methods in the context of benchmark simulations and predictions. In this paper, we apply the CAC method and different PFDD variants – one of them is equivalent to a GPN model – to simulate an extended (i.e., dissociated) dislocation in Al with initially pure edge or pure screw character in terms of the disregistry. CAC and discrete forms of PFDD are also employed to calculate the Peierls stress. By conducting comprehensive convergence studies, we quantify the dependence of these measures on time/grid resolution and simulation cell size. Several important but often overlooked differences between PFDD/GPN variants are clarified. In conclusion, our work sheds light on the advantages and limitations of each method, as well as the path towards enabling them to effectively model complex dislocation processes at larger length scales.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Multiscale analysis of large twist ferroelectricity and swirling dislocations in bilayer hexagonal boron nitride

With its atomically thin structure and intrinsic ferroelectric properties, heterodeformed bilayer hexagonal boron nitride (hBN) has gained prominence in next-generation non-volatile memory applications. However, studies to date have focused almost exclusively on small-twist bilayer hBN, leaving the question of whether ferroelectricity can persist under small heterostrain and large heterodeformation entirely unexplored. In this work, we establish the crystallographic origin of ferroelectricity in bilayer hBN configurations heterodeformed relative to high-symmetry configurations such as AA-stacking and 21.786789° twisted configurations (Σ7), using Smith normal form bicrystallography. We then demonstrate out-of-plane ferroelectricity in bilayer hBN across configurations vicinal to both the AA and Σ7 stackings. Atomistic simulations reveal that AA-vicinal systems support ferroelectricity under both small twist and small strain, with polarization switching in the latter governed by the deformation of swirling dislocations rather than the straight interface dislocations seen in the former. For Σ7-vicinal systems, where existing interatomic potentials underperform particularly under extreme out-of-plane compression, we develop a density-functional-theory-informed continuum framework—the bicrystallography-informed frame-invariant multiscale (BFIM) model, which captures out-of-plane ferroelectricity in heterodeformed configurations vicinal to Σ7 stacking. Interface dislocations in these large heterodeformed bilayer configurations exhibit markedly smaller Burgers vectors compared to interface dislocations in small-twist and small-strain bilayer hBN. The BFIM model reproduces experimental results and provides a powerful, computationally efficient framework for predicting ferroelectricity in large-unit-cell heterostructures where atomistic simulations are prohibitively expensive.

Ahmed, Md Tusher [Univ. of Illinois at Urbana-Cham↗
DOE OSTI2025

CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback

The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided computational screening framework unifying linguistic reasoning with quantum-chemistry based feedback from 3D atomistic representations. Our approach formulates catalyst discovery as an uncertain environment where an agent actively searches for highly effective catalysts via the iterative combination of large language model (LLM)-derived hypotheses and atomistic graph neural network (GNN)-derived feedback. Identified catalysts in intermediate search steps undergo structural evaluation based on spatial orientation, reaction pathways, and stability. Scoring functions based on adsorption energies and barriers steer the exploration in the LLM's knowledge space toward energetically favorable, high-efficiency catalysts. We introduce planning methods that automatically guide the exploration without human input, providing competitive performance against expert-enumerated chemical descriptor-based implementations. By integrating language-guided reasoning with computational chemistry feedback, our work pioneers AI-accelerated, trustworthy catalyst discovery.

artificial intelligence↗
DOE OSTI2023

Engineering the formation of spin-defects from first principles

The full realization of spin qubits for quantum technologies relies on the ability to control and design the formation processes of spin defects in semiconductors and insulators. We present a computational protocol to investigate the synthesis of point-defects at the atomistic level, and we apply it to the study of a promising spin-qubit in silicon carbide, the divacancy (VV). Our strategy combines electronic structure calculations based on density functional theory and enhanced sampling techniques coupled with first principles molecular dynamics. We predict the optimal annealing temperatures for the formation of VVs at high temperature and show how to engineer the Fermi level of the material to optimize the defect’s yield for several polytypes of silicon carbide. Our results are in excellent agreement with available experimental data and provide novel atomistic insights into point defect formation and annihilation processes as a function of temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

GeSn-on-GaAs with photoconductive carrier lifetime >400 ns: role of substrate orientation and atomistic simulation

Group IV GeSn quantum material finds application in electronics and silicon-compatible photonics. Synthesizing these materials with low defect density and high carrier lifetime is a potential challenge due to lattice mismatch induced defects and tin segregation at higher growth temperature. Recent advancements in the growth of these GeSn materials on Si, Ge, GaAs, and with substrate orientations, demonstrated different properties using epitaxial and chemical deposition methods. This article addresses the effect of GaAs substrate orientation and misorientation on the materials’ properties and carrier lifetimes in epitaxial Ge 0.94 Sn 0.06 layers. With starting GaAs substrates of (100)/2°, (100)/6°, (110) and (111)A orientations, Ge 0.94 Sn 0.06 epitaxial layers were grown with an intermediate Ge buffer layer by molecular beam epitaxy and analyzed by several analytical tools. X-ray analysis displayed good crystalline quality, and Raman spectroscopy measurements showed blue shifts in phonon wavenumber due to biaxial compressive strain in Ge 0.94 Sn 0.06 epilayers. Cross-sectional transmission electron microscopy analysis confirmed the defect-free heterointerface of Ge 0.94 Sn 0.06 /Ge/GaAs heterostructure. Minority carrier lifetimes of the unintentionally doped n-type Ge 0.94 Sn 0.06 epilayers displayed photoconductive carrier lifetimes of >400 ns on (100)/6°, 319 ns on (100)/2°, and 434 ns on (110) GaAs substrate at 1500 nm excitation wavelength. On the other hand, Ge 0.94 Sn 0.06 layer showed poor carrier lifetime on (111)A GaAs substrate. The observed differences in carrier lifetimes were correlated with the formation energy of the Ge on (100)/6° and (100)/2° GaAs heterointerface using Stillinger–Weber interatomic potential model-based atomistic simulation with different heterointerfacial bonding by Synopsys QuantumATK tool. Total energy computation of 6280-atom Ge/GaAs supercell on (100)/6° leads to lower formation energy than (100)/2°, making it more thermodynamically stable. Hence, the growth of the GeSn/III–V material system using misoriented (100) substrates that are more thermodynamically stable will enhance the performances of optoelectronic devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Systematic improvement of redox potential calculation of Fe(III)/Fe(II) complexes using a three-layer micro-solvation model

Electrochemical transformations of metal ions in aqueous media are challenging to model accurately due to the dynamic solvation structure surrounding ions at different charge states. Predictive modeling at the atomistic scale is essential for understanding these solvation architectures but is often computationally prohibitive. In this contribution, we present a simple, fast, and accurate three-layer micro-solvation model to evaluate the redox potential of metal ions in aqueous solutions. Our model, developed and validated for Fe 3+ /Fe 2+ redox potentials, combines the DFT-based geometry optimizations of the octahedral Fe complex with two layers of explicit water molecules to capture solute–solvent interactions and an implicit solvation model to account for bulk solvent effects. This approach yields accurate predictions for Fe 3+ /Fe 2+ redox potentials in water, achieving errors of 0.02 V with ωB97X-V, 0.01 V with ωB97X-D3, 0.04 V with ωB97M-V, and 0.02 V with B3LYP-D3 functionals. We further demonstrate the generality of our model by applying it to additional metal complexes, including the challenging Fe(CN) 6 3−/4− system, where our model successfully achieves close agreement with experimental values, with an error of 0.07 V and an average error of 0.21 V for all five systems. In summary, the presented simple solvation model has broad applicability and potential for enhancing computational efficiency in redox potential predictions across various chemical and industrial processes of metal ions.

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

A density-functional theory study of the Al/AlOx/Al tunnel junction

The aluminum oxide tunnel junction is a key component of the majority of superconducting quantum devices. For high-quality, reproducible, and scalably manufacturable qubits, the ability to fabricate Josephson junctions (JJs) with a targeted critical current and high uniformity is essential. In this study, we use first-principles modeling to assess fundamental aspects of the atomic structure of both amorphous and crystalline aluminum oxide tunnel junctions and relate the structure to predicted performance metrics. We use modified ab initio molecular dynamics to develop realistic models of the tunnel junction, from which interface roughness and local thickness fluctuations are analyzed in an unbiased manner by training a neural network to identify the boundary between metal and oxide. We show that the effective thickness of the insulating part of the junction can be different from the apparent physical thickness. We calculate the rate of Cooper pair tunneling for the atomically resolved electrostatic potential using direct numerical solution in 3D, which shows a channeling effect that impacts the junction critical current. The predicted critical current is a useful JJ design parameter that can be accessed from the ab initio calculations without fitting parameters. To assess the limits of uniformity and fabrication choices (e.g., oxidation vs epitaxy), we compare the amorphous junctions to crystalline models, which show order of magnitude more efficient tunneling compared to the amorphous case, underlining the connection between atomistic structure and Cooper pair tunneling efficiency. Further, this work provides a foundation for ab initio materials design and evaluation to help accelerate future development of improved tunnel junctions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗