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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

An atomistic study connecting underlying dislocation behavior with superior mechanical properties of NiCoCr medium entropy alloy

NiCoCr-based medium-entropy alloy (MEA) with a simple face-centered cubic crystal phase exhibits excellent mechanical properties, often attributed to the synergy of multiple deformation mechanisms. However, the atomistic origin of their outstanding mechanical response, including microstructural evolution and dislocation behavior under varying strain-rates and orientation, remains unclear. In this work, we employ large-scale molecular dynamics (MD) simulations to investigate the changes in deformation mechanisms along three distinct orientations ([110], [111], [100]) under varying strain rates (1 ×10 8 /sec, 1 ×10 10 /sec, 1 ×10 12 /sec) in the NiCoCr MEA. The presence of the stair-rod and the Shockley partial dislocations under uniaxial tensile strain are found to play a key role in the formation of deformation twinning and ε-martensite, which positively correlates with strain-rate dependent dislocation analysis. These findings further establish the role of the dislocations in controlling the superior mechanical response and excellent fracture toughness of the NiCoCr MEA. Systematic transmission-electron microscopy tests performed on the [111]-oriented crystals, deformed at different strain levels, at room temperature provide clear evidence of both the extended stacking-fault and the stair rods, confirming the predicted microstructural features. Finally, this study offers key insights into the complex nucleation mechanisms of deformation twinning and ε-martensite, such as twinning – and transformation–induced plasticity (TWIP-TRIP), providing valuable guidelines for studying similar material classes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Thermal Shape Stability of fcc Metal Nanocrystals Synthesized with Faceted Nonequilibrium Shapes

Highly refined capabilities of the shape-controlled solution-phase synthesis of metal nanocrystals (NCs) allow the generation of NCs with faceted nonequilibrium shapes, which optimize properties for target applications such as catalysis and plasmonics. Often, for such applications and also for TEM analysis, the NCs are removed from the solution-phase environment. We explore the postsynthesis evolution of these metastable NCs in a high-vacuum TEM environment. Specifically, here we analyze their reshaping toward the equilibrium Wulff shapes mediated by surface diffusion, where such reshaping degrades the above-mentioned optimized properties. Typical sizes for these NCs range from 5 to 30 nm or 10 3 –10 6 atoms, and reshaping often occurs on the time scale of minutes for temperatures around, say, 400 °C. We discuss the development of predictive stochastic atomistic-level models for NC evolution with a realistic description of surface diffusion. These models, in contrast to Molecular Dynamics, can naturally address the relevant time and length scales for these systems. KMC simulation results for the stochastic models are described, focusing on the reshaping of slightly elongated nanorods and of mildly truncated octahedra and nanocubes. In addition, we review appropriate theoretical formulations for reshaping, which involves the nucleation and growth on 2D islands or layers on outer facets of the NC. We note the limitations of classical nucleation theory in some scenarios and demonstrate the successes of a more fundamental and general master equation-based analysis.

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

Atomistic characterization of hydration-dependent fuel cell ionomer nanostructure: validation by vibrational spectroscopy

The development of Nafion alternatives for fuel cells and electrolyzers requires a fundamental understanding of hydration-dependent ion-exchange site acid/base chemistry. We present here reactive force field (ReaxFF) molecular dynamics (MD) simulations of Nafion at varying molar water/ion-exchange-site ratios (λ), which we correlate to our experimental and density functional theory-based vibrational spectra. ReaxFF describes the formation and breaking of covalent bonds, enabling simulations of proton exchange between sulfonic acid/sulfonate groups and water/hydronium. Our MD simulations determine the λ-dependent equilibrium proportions of protonated and deprotonated sites. We find that protonated sites persist across all λ from 0 to 20, challenging the widely accepted notion that all sites are ionized above a threshold λ value (e.g., 3 or 4). Our simulations generate hundreds of realistic exchange site environments, the characterization of which are based on 6 Å radii sulfur-centered ‘inner-spheres’. These inner- and outer-sphere regions elucidate an interplay of stereoelectronic factors that influence protonation states, including the number of inner-sphere waters (Λ). Our simulations produce broad λ-dependent distributions of Λ values, representing non-uniform exchange site hydration. Moreover, we demonstrate that these distributions are specific to both protonated and deprotonated sites, with significant overlap between the two distributions for all non-zero λ. These distributions underpin the IR spectra of hydrated membranes, with each exchange site contributing an IR spectrum characteristic of its protonation state and Λ. We expect that these nanostructural characterizations of Nafion exchange sites will contribute to the development of new ionomers.

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

DeePMD-kit v2: A software package for deep potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Combining machine-learned and empirical force fields with the parareal algorithm: application to the diffusion of atomistic defects

We numerically investigate an adaptive version of the parareal algorithm in the context of molecular dynamics. This adaptive variant has been originally introduced in [1]. We focus here on test cases of physical interest where the dynamics of the system is modelled by the Langevin equation and is simulated using the molecular dynamics software LAMMPS. In this work, the parareal algorithm uses a family of machine-learning spectral neighbor analysis potentials (SNAP) as fine, reference, potentials and embedded-atom method potentials (EAM) as coarse potentials. We consider a self-interstitial atom in a tungsten lattice and compute the average residence time of the system in metastable states. Our numerical results demonstrate significant computational gains using the adaptive parareal algorithm in comparison to a sequential integration of the Langevin dynamics. We also identify a large regime of numerical parameters for which statistical accuracy is reached without being a consequence of trajectorial accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Atomistic Investigation of Plastic Deformation and Dislocation Motion in Uranium Mononitride

Uranium mononitride (UN) is a promising advanced nuclear fuel due to its high thermal conductivity and high fissile density. However, many aspects of its mechanical behavior, particularly at reactor-relevant conditions, remain unclear. In this study, molecular dynamics (MD) simulations were employed to investigate the deformation behavior and dislocation motion in UN. We found that the Kocevski potential predicts the principal slip system as $\frac{1}{2}$ $\langle110\rangle${110}, aligning with experimental data. On the other hand, the Tseplyaev potential predicts slip to primarily occur on $\frac{1}{2}$ $\langle110\rangle${111}. MD simulations of stress–strain behavior were used to estimate the nanoindentation hardness, revealing that the Kocevski potential accurately predicts hardness even though it fails to model dynamic plasticity. Complete dislocation mobility functions have been fitted for the edge and screw dislocations in both the thermally activated and phonon-drag regimes. The 300 K linear mobility of the edge dislocation using the Tseplyaev potential was found to be 817 Pa -1 ·s -1 , whereas that of the screw dislocation using the Kocevski potential was found to be 4546 Pa -1 ·s -1 . At intermediate stresses, we observed that the subsonic steady-state motion of the edge dislocation in UN is intermittently interrupted by velocity jumps, reaching the average sound velocity. Finally, the threshold Schmid stress is calculated as 179–197 MPa, which gives an upper-limit estimate of the uniaxial yield stress of polycrystalline UN of 548–603 MPa. These findings, including the fitted dislocation mobility function, provide essential input for future plasticity and dislocation dynamics models of nuclear fuels.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Mechanism of Tyrosine-Driven Deprotonation in Photosystem II Revealed by Multiscale Simulations

Photosystem II (PSII) drives light-induced water oxidation via stepwise redox transitions of its oxygen-evolving complex (OEC), a Mn 4 Ca cluster advancing through five intermediate S-states (S 0 –S 4 ). The S 2 → S 3 transition involves a redox event in which a Mn ion donates an electron to the redox-active tyrosine YZ, coupled to deprotonation of an OEC-bound water ligand─yet the underlying coupling mechanism remains unresolved. Time-resolved serial femtosecond crystallography (TR-SFX) has revealed transient electron density shifts near the redox-active tyrosine Y Z , interpreted as sequential oxidation and reduction, with reduction initiating ∼1 μs after excitation and substantially progressed by 30 μs. However, this interpretation conflicts with kinetics from photothermal beam deflection (PBD), time-resolved X-ray absorption spectroscopy (TR-XAS), and electron paramagnetic resonance (EPR), which place electron transfer at 190–400 μs and proton transfer around 30 μs. Here, we reconcile these discrepancies using quantum mechanics/molecular mechanics (QM/MM) and molecular dynamics (MD) simulations. We show that oxidation of P680 and Y Z breaks the symmetry of the nearby hydrogen bonds involving water molecule W4, displacing Y Z and replicating the TR-SFX features of Y Z and Q165 observed at 1 μs. This local perturbation propagates through a hydrogen-bond network, transmitting the electrostatic signal from Y Z to the E65-E312 dyad and triggering redox-coupled deprotonation via the Cl1 channel. By 30 μs, the hydrogen-bond symmetry is restored through deprotonation of W2 (or alternatively W1), reproducing the disappearance of TR-SFX density differences around Y Z and Q165 without requiring Y Z reduction. Our proposed mechanism also gives molecular insights into the O6* density, assigning it to water reorganization rather than a discrete Ca-bound hydroxide species. Here, our results reveal a detailed atomistic mechanism linking Y Z oxidation to long-range proton release and suggest a functional role for the nearby Cl – ion in proton transfer. More broadly, this study underscores the importance of hydrogen-bond dynamics in mediating redox-driven proton transport and demonstrates how integrative simulations can resolve mechanistic ambiguities.

Deprotonation↗
DOE OSTI2021

Shape Stability of Truncated Octahedral fcc Metal Nanocrystals

Metallic nanocrystals (NCs) can be synthesized with tailored nonequilibrium shapes to enhance desired properties, e.g., octahedral fcc metal NCs optimize catalytic activity associated with {111} facets. However, maintenance of optimized properties requires stability against thermal reshaping. Thus, we analyze the reshaping of truncated fcc metal octahedra mediated by surface diffusion using a stochastic atomistic-level model with energetic input parameters for Pd. Furthermore, the model describes NC thermodynamics by an effective nearest-neighbor interaction and includes a realistic treatment of diffusive hopping for undercoordinated surface atoms. Kinetic Monte Carlo simulation reveals that the effective barrier, E eff , for the initial stage of reshaping is strongly tied to the degree of truncation of the vertices in the synthesized initial octahedral shapes. This feature is elucidated via exact analytic determination of the energy variation along the optimal reshaping pathway at low-temperature (T), which involves transfer of atoms from truncated {100} vertex facets to form new layers on {111} side facets. Deviations from predictions of the low-T analysis due to entropic effects are more prominent for higher T and larger NC sizes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

JARVIS-Leaderboard: a large scale benchmark of materials design methods

Abstract Lack of rigorous reproducibility and validation are significant hurdles for scientific development across many fields. Materials science, in particular, encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC), and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboard/

36 MATERIALS SCIENCE↗
DOE OSTI2023

A First Principles Approach to Spectral Phonon Transport in Heterostructures

Understanding thermal transport across interfaces which give rise to a thermal resistance (also known as Kapitza resistance) is a critical issue affecting the development of nanotechnologies. Much modern and emergent nanotechnology consist of adjacent materials, and phonon mediated heat transfer governs thermal behavior across internal interfaces in these devices. The physics of thermal transport in solids are governed both by phenomena occurring at the atomic scale and interactions with the material's microstructure. The forecasting of fundamental quantities such as temperature, heat flux and thermal conductivity typically employs the semi-classical Boltzmann transport equation to predict the macroscopic behavior of materials in terms of the microscopic dynamics of its heat carriers. Kapitza resistance was first discovered in liquid helium experiments and has led to a fundamental research thrust in micro and nano-scale heat transport, the behavior of thermal carriers across internal interfaces. Thermal interfacial resistance (TIR) is a widely studied phenomenon, first engaged by Swartz and Pohl through their development of the acoustic and diffuse mismatch methods, then continued through myriad efforts with varying methods and approaches in an attempt to resolve carrier behavior at thermal interfaces. Many of the fundamental approaches to TIR have been at the nanoscale, and research is conducted with molecular dynamics (MD) and density functional theory (DFT) methods. The limitations of these methods is system size; atomistic methods tend to be limited to system sizes of 100,000 atoms or less. Larger length-scale methods have also been pursued, based on the principles of acoustic or diffuse mismatch, but not all include simulation of TIR using a full phonon band spectrum, or temperature dependent methods. Our approach to enabling phonon transport in layered materials draws upon our previous work of demonstrating spectrally coupled phonon transport in homogeneous and heterogeneous materials. We use a semi-analytical approach in which the Bose-Einstein (B-E) statistics set the strength of the phonon radiance in a frequency group, but the B-E statistics are informed with information from the transport system. The B-E statistics in a single frequency group feels the influence of all the groups through the spatial temperature. We also include a new field term which is an indicator of the amount of non-equilibrium behavior of the phonon spectrum---this is added to the phonon source term in all groups to ensure closure and conservation of energy, as the phonon groups in the transport system and the analytical systems are coupled. This work builds upon our previous approach by adding a phonon coupling term at an internal interface, using the principles of the DMM through transmission and reflection coefficients. In this work, the coefficients are determined through computing a common temperature at the interface, influenced by the phonon band structure of both materials, in effect, providing mixing between the two material systems and using the common temperature to set the strength of the phonon radiance at the boundaries on either side of the interface. Our approach uses material properties computed along various crystallographic orientations, and while some isotropy is built into the interface condition, the material properties weight the phonon distributions in the proper crystalline direction. Greater resolution of phonon behavior in proximity to an interface, and more accurate predictions of TIR are obtained. While it is true the assumption of diffuse mismatch can yield inconsistent results compared to experiment especially at low temperatures, this work focuses on room temperature and beyond effects, for future applications in nuclear fuel, or thermoelectric devices; a modified mismatch approach may be feasible if applied properly. Additionally, our methods focus on bridging mesoscale to engineering scale

36 MATERIALS SCIENCE↗
DOE OSTI2025

Atomistic Origin of Microsecond Carrier Lifetimes at Perovskite Grain Boundaries: Machine Learning-Assisted Nonadiabatic Molecular Dynamics

The polycrystalline nature of perovskites, stemming from their facile solution-based fabrication, leads to a high density of grain boundaries (GBs) and point defects. However, the impact of GBs on perovskite performance remains uncertain, with contradictory statements found in the literature. We developed a machine learning force field, sampled GB structures on a nanosecond time scale, and performed nonadiabatic (NA) molecular dynamics simulations of charge carrier trapping and recombination in stoichiometric and doped GBs. The simulations reveal long, microsecond carrier lifetimes, approaching experimental data, stemming from charge separation at the GBs and small NA coupling, 0.01–0.1 meV. Stoichiometric GBs exhibit transient trap states, which, however, are not particularly detrimental to the carrier lifetime. Halide dopants form interstitial defects in the bulk, but have a stabilizing influence on the GB structure by passivating undersaturated Pb atoms and reducing the transient trap state formation. On the contrary, excess Pb destabilizes GBs, allowing formation of persistent midgap states that trap charges. Still, the charge carrier lifetime reduces relatively little, because the midgap states decouple from the bands, and charges are more likely to escape back into bands upon a GB structural fluctuation. The atomistic study into the structural dynamics of perovskite GBs and its influence on charge carrier trapping and recombination provides valuable insights into the complex properties of perovskites and the intricate role of GBs in the material performance.

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

CHARMM-GUI Bicelle Builder : An Extension of Membrane Builder for Modeling and Simulation of Bicelle Systems

Membrane mimetics, such as detergent micelles, nanodiscs, and amphipol complexes, which can provide membrane-like environments while retaining small and soluble features, have been utilized to study membrane proteins. A bicelle, composed of varying lipids and detergents, is a useful membrane mimetic because the lipid-to-detergent ratio, the q-value, can be adjusted to alter the properties of the aggregate, including the thickness and size of the bicelle. However, building a bicelle model for modeling and simulation studies requires nontrivial efforts, even for experts. We introduce CHARMM-GUI Bicelle Builder, a web-based platform that can generate various all-atom bicelle systems via a graphical user interface with all available lipids and detergents in Membrane Builder. To illustrate and validate Bicelle Builder with practical systems, we have modeled and simulated pure bicelles consisting of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) lipids with 1,2-dihexanoyl-sn-glycero-3-phosphocholine (C6DHPC) detergents and protein–bicelle complexes, composed of DMPC with C6DHPC, foscholine-10 (FOS10), and lysophosphatidylcholine-12 (LPC12) detergents. Our simulation results indicate that Bicelle Builder can generate reliable and robust bicelle models with and without proteins that retain DMPC bilayer characteristics. Bicelle Builder is expected to help researchers better understand not only bicelles themselves but also atomistic-level structures of protein–bicelle complexes that are often difficult to access through experimental approaches.

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

Bridging the gap between NMR measured mean silicate chain length and nano-scale silicate polymorphism of calcium silicate hydrates

Variable stoichiometry and silicate polymorphism in calcium-silicate-hydrates (C-S-H) has impeded the revelation of point defects distribution in the silicate tetrahedral network of C-S-H, which resembles tobermorite crystal structure with some bridging tetrahedra (BT) and paired tetrahedra (PT) vacancies in dreierketten chains. Here we use a computational approach to characterize silicate polymorphism by introducing the vacancy ratio of BT to PT (α) and establishing a three-term empirical mean chain length (MCL) formula for different calcium-to‑silicon ratios (Ca/Si) ranging from 1.2 to 2.3. The formula identifies BT and PT controls at low and high α respectively and allows an inverse mapping of polymorphic range based on NMR experiments. The proposed computational framework quantitatively describes silicate polymorphs and links NMR-measured MCL to C-S-H atomistic configurations at the molecular level.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Atomic-scale understanding of oxide growth and dissolution kinetics of Ni-Cr alloys

Aqueous corrosion of metals is governed by formation and dissolution of a passivating, multi-component surface oxide. Unfortunately, a detailed atomistic description is challenging due to the compositional complexity and the need to consider multiple kinetic factors simultaneously. To this end, we combine experiments with a first-principles-derived, multiscale computational framework that transcends thermodynamic descriptions to explicitly simulate the kinetic evolution of surface oxides of Ni-Cr alloys as a function of composition, temperature, pH, and applied voltage. In the absence of pitting, we identify three distinct voltage regimes, which are kinetically dominated by oxide growth, dissolution, and competitive dissolution and reprecipitation. Evolving compositional gradients and oxide thickness are revealed, including a transition between a metastable Ni-Cr mixed oxide and a thick, porous Ni-dominated oxide. Beyond elucidating the underlying physics, we highlight the need for competing kinetics in models to properly predict the transition from passivation to corrosion. Our results provide a key step towards co-design of alloy composition alongside environmental conditions for sustainable use across a variety of critical energy and infrastructure applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dislocation loop evolution in Kr-irradiated ThO 2

Here, the early stage of microstructural evolution of ThO 2 , under krypton irradiation at 600, 800, and 1000°C, was investigated using in situ transmission electron microscopy (TEM). Dislocation loops grew faster, whereas their number density decreased with increasing irradiation temperature. Loop density was found to decrease with ion dose. Interstitial dislocation loops, including Frank loops with Burgers vector of $\textit{a}/3\langle111\rangle$ and perfect loops with Burgers vector of $\textit{a}/2\langle110\rangle$, were determined by traditional TEM and atomic resolution–scanning TEM techniques. Atomistic and mesoscale level modeling are performed to interpret experimental observations. The migration energy barriers of defects in ThO 2 were calculated using density-functional theory. The energetics of different dislocation loop types were studied using molecular dynamics simulations. Loop density and diameter were analyzed using a kinetic rate theory model that considers stoichiometric loop evolution. This analysis reveals that loop growth is governed by the mobility of cation interstitials, whereas loop nucleation is determined by the mobility of anion defects. Lastly, a rate theory model was used to extract the diffusion coefficients of thorium interstitials, oxygen interstitials, and vacancies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Deciphering atomistic mechanisms of the gas-solid interfacial reaction during alloy oxidation

Gas-solid interfacial reaction is critical to many technological applications from heterogeneous catalysis to stress corrosion cracking. A prominent question that remains unclear is how gas and solid interact beyond chemisorption to form a stable interphase for bridging subsequent gas-solid reactions. Here, we report real-time atomic-scale observations of Ni-Al alloy oxidation reaction from initial surface adsorption to interfacial reaction into the bulk. We found distinct atomistic mechanisms for oxide growth in O 2 and H 2 O vapor, featuring a “step-edge” mechanism with severe interfacial strain in O 2 , and a “subsurface” one in H 2 O. Ab initio density functional theory simulations rationalize the H 2 O dissociation to favor the formation of a disordered oxide, which promotes ion diffusion to the oxide-metal interface and leads to an eased interfacial strain, therefore enhancing inward oxidation. Our findings depict a complete pathway for the Ni-Al surface oxidation reaction and delineate the delicate coupling of chemomechanical effect on gas-solid interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Phase instability-coupled fracture behavior in garnet LLZO solid electrolytes: a machine learning-enabled atomistic study

Fracture in the garnet-type solid electrolyte Li 7 La 3 Zr 2 O 12 (LLZO) poses a critical threat to both the performance and safety of solid-state batteries. To unravel the coupled chemomechanical processes that govern fracture in LLZO under external loading, we carry out large-scale molecular-dynamics simulations with a validated machine-learning force field. Our results demonstrate that triaxial stresses at crack flanks trigger a localized cubic-to-tetragonal phase transformation, which is accompanied by Li-ion rearrangement. The emergent tetragonal domains feature lattice contraction normal to the fracture plane, imposing coherent misfit strains that provide an additional driving force for further crack propagation. Crucially, introducing Li deficiencies stabilizes the cubic phase, postponing the phase transition and thereby delaying fracture initiation. These findings highlight the role of intrinsic phase instability in dictating LLZO's fracture resistance and its critical connection to local Li concentration. This chemomechanical coupling points toward targeted strategies to enhance the mechanical robustness of garnet electrolytes, including tuning Li content, ensuring dopant homogeneity, and refining processing protocols.

Materials science↗
DOE OSTI2023

Hybrid physics-based and machine learning tools for materials assessment

In this work, we develop novel physics-based and machine learning computational techniques to predict fundamental properties of metallic systems that affect radiation damage behavior in reactor structural materials. Oftentimes, atomistic predictions of engineering alloys simplify chemical compositions to a single element to reduce computational cost and complexity, introducing large sources of uncertainty and potentially missing important behavior. In addition, engineering alloys such as SS 316 are particularly challenging to simulate with first principles methods because of the additional degrees of freedom introduced by magnetic natures of the constituent elements, and very little data of this type exists within the literature. These novel methods aim to improve the qualitative prediction of radiation damage in engineering alloys by more accurately simulating their compositions, both by accelerating the computations and by developing novel analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗