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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 109 records · Page 6

Momentum-Resolved Direct Observation of Chiral Phonons in Elemental Tellurium

Chiral phonons carry finite phonon angular momentum, yet their momentum-resolved behavior in acoustic branches remains largely unexplored. In this work, we report the direct detection of chiral acoustic phonons in elemental Te. Through a combination of high-energy-resolution inelastic x-ray scattering experiments and atomistic modeling, we confirm that longitudinal acoustic modes develop pronounced circular atomic motion by mixing with transverse modes. Our results establish a direct link between unexpected scattering intensity in nominally forbidden geometries and circular phonons, offering a framework for characterizing momentum-resolved phonon chirality and highlighting the emergence of intrinsic phonon angular momentum in acoustic branches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Pressure-induced polyamorphic transition in CaA l 2 O 4 glass

In situ high-pressure ultrasonic velocity measurements of CaAl 2 O 4 glass reveal abrupt irreversible discontinuities in the elastic wave velocities at ~8–10 GPa. Total structure factor and pair distribution functions measured by synchrotron x-ray diffraction show a rapid change in the intermediate range structure attributed to a rearrangement of calcium ions over this narrow pressure region. Atomistic models obtained from molecular dynamics simulations reveal that this intermediate range structure is explained by a transition of Ca–O void radius distribution from a bimodal distribution with peaks at ~2.1 and ~2.4 Å to a single distribution centered at ~2.1 Å. Further, these abrupt structural changes involving the rapid increase in elastic wave velocity are markedly different to the continuous transformations observed in conventional network-forming glasses, such as SiO 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Structure and migration of heavily irradiated grain boundaries and dislocations in Ni in the athermal limit

The microstructural evolution at and near preexisting grain boundaries (GBs) and dislocations in materials under high radiation doses is still poorly understood. In this work, we use the creation relaxation algorithm (CRA) developed for atomistic modeling of high-dose irradiation in bulk materials to probe the athermal limit of saturation of GB and dislocation core regions under irradiation in fcc Ni. We find that, upon continuously subjecting a single dislocation or GB to Frenkel pair creation in the athermal limit, a local steady-state disordered defect structure is reached with excess properties that fluctuate around constant values. Case studies are given for a straight screw dislocation which elongates into a helix under irradiation and several types of low- and high-angle GBs, which exhibit coupled responses such as absorption of extrinsic dislocations, roughening, and migration. A positive correlation is found between the initial GB energy and the local steady-state GB energy under irradiation across a wide variety of GB types. Metastable GB structures with similar density in the defect core region but different initial configurations are found to converge to the same limiting structure under CRA. The mechanical responses of pristine and irradiated dislocations and GB structures are compared under an applied shear stress. Irradiated screw and edge dislocations are found to exhibit a hardening response, migrating at larger flow stresses than their pristine counterparts. Mobile GBs are found to exhibit softening or hardening responses depending on GB character. Although some GBs recover their initial pristine structures upon migration outside of the radiation zone, many GBs sustain different flow stresses corresponding to altered mobile core structures.

36 MATERIALS SCIENCE↗

Effect of relative humidity on the interlayer spacing of phosphate intercalated Mg, Al layered double hydroxide (hydrotalcite‐like) crystals

Abstract The availability of water and the type of interlayer anions present affect the arrangement and interlayer spacing of layered double hydroxide (LDH). A systematic study of the effect of relative humidity (RH) on the basal spacing of phosphate intercalated, magnesium aluminum LDHs (MgAl–PO 4 LDH) was conducted, confirming that MgAl‐PO 4 LDH exhibit distinct interlayer spacing corresponding to separate low‐ and high‐hydration states produced when exposed to low and high humidity conditions. The transition from the low‐ to high‐hydration form begins when RH exceeds 33% and is accompanied by the transition from one to two interlayers of water. An improved understanding of the effect of RH on MgAl–PO 4 LDHs will enable more accurate atomistic modeling and experimental characterization of MgAl–PO 4 LDHs and may lead to improvements in the tunability of MgAl‐PO 4 LDHs for commercial applications such as slow‐release fertilizer.

Reed, Titus↗

Identification of short-range ordering motifs in semiconductors

Chemical short-range ordering is expected to be a key factor for tuning the electronic structure of semiconductors. However, experimental evidence of short-range ordering is still lacking due to the challenge of characterizing atomic-scale ordering motifs. Here, we determined the presence of short-range order in a ternary GeSiSn semiconductor system using advanced energy-filtered four-dimensional scanning transmission electron microscopy and large-scale atomistic models generated by a machine learning neuroevolution potential of first-principles accuracy. This approach revealed preferred ordering of different atomic species with the dominant occurrence of Si–Ge–Sn triplets. Our findings not only confirmed the presence of short-range order but also directly revealed the actual atomic structure, demonstrating the potential for informed atomic order–based band engineering as a third degree of freedom beyond composition and strain tuning.

Vogl, Lilian M. [University of California Berkeley↗

Impact of the LiPF6 Concentration on the Interfacial Charge Transfer and Fast-charging Capabilities of Lithium-Ion Batteries

Fast-charging lithium-ion batteries (LIB) demand optimized electrolyte formulations to balance ionic conductivity, viscosity, and interfacial charge transfer kinetics. This study examines how LiPF 6 concentration shapes solvation structure, desolvation energy, charge transfer activation energy, and solid electrolyte interphase (SEI) properties, which are critical for fast-charging performance. Using Raman spectroscopy, electrochemical cycling, X-ray photoelectron spectroscopy, and atomistic modeling, we analyze how varying LiPF 6 concentrations impact interfacial and bulk transport properties. Our findings show that increasing LiPF 6 concentration alters lithium solvation structures, reduces desolvation energy, and accelerates charge transfer at the electrode interface. Higher concentrations lower the activation energy for charge transfer and suppress excessive SEI growth, improving interfacial kinetics. However, concentrations above a certain threshold increase viscosity and reduce ionic conductivity, limiting transport efficiency. These results offer insights into electrolyte solvation and interfacial charge transfer mechanisms, providing guidelines for designing next-generation fast-charging LIB electrolytes with enhanced efficiency, stability, and longevity.

Son, Seoung-Bum [Argonne National Laboratory (ANL)↗

HydraGNN v5.0

HydraGNN v5.0 expands the code base into a more portable, scalable, and flexible framework for scientific graph learning, with particular strength in atomistic machine-learning interatomic potentials and large-scale distributed training. The release adds Fully Sharded Data Parallel (FSDP) support alongside existing DDP and DeepSpeed paths, including FSDP-aware checkpointing and optimizer integration, and introduces a configurable multi-precision training workflow supporting FP32, BF16, and FP64 across GPUs and Intel XPUs. For atomistic modeling, HydraGNN v5.0 strengthens its MLIP capabilities through dynamic graph construction at every forward pass, energy-conserving force prediction via automatic differentiation, and per-atom energy loss formulations, while extending EGNN models to properly handle periodic boundary conditions. The release also broadens model expressiveness through graph-level attribute conditioning, adds new multi-task and model-parallel extensions such as MACE support and encoder/decoder branch optimization, and expands application coverage with integrated examples for datasets including OC25, Nabla2-DFT, QCML, Open Polymers 2026, and OPF. In parallel, HydraGNN v5.0 improves production readiness through performance optimizations for large-scale runs, stratified sampling and linear-regression preprocessing utilities, and tested installation scripts for DOE supercomputers including Frontier, Aurora, Perlmutter, and Andes. Overall, the release advances HydraGNN as a robust software platform for scalable graph neural networks across materials science, chemistry, and scientific machine learning workflows

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗

HydraGNN_GFM_FineTuning4Materials v1.0

This repository enables fine-tuning of the HydraGNN Predictive GFM 2026 — an open-source ensemble of pre-trained graph foundation models for atomistic materials modeling, developed at Oak Ridge National Laboratory. The GFM 2026 is freely available and downloadable via Globus from the OLCF Data Constellation (DOI: 10.13139/OLCF/2562660). Starting from these pre-trained weights, this repository provides a complete transfer learning pipeline for adapting the GFM ensemble to domain-specific molecular and materials property prediction tasks. It includes: 1) Utilities for ensemble fine-tuning with task-specific output heads 2) Example pipelines for eight widely-used materials and molecular datasets 3) Tools for model adaptation and head configuration 4) Data preprocessing utilities for each supported dataset 5) Benchmarking and evaluation scripts

Ungerboeck, Linda↗

High temperature nuclear data measurements of SiC, ZrC, and MgO [Slides]

Performed temperature dependent measurements of SiC and ZrC at ARCS instrument at SNS. Performed temperature dependent measurements of SiC, ZrC, and MgO at VISION instrument at SNS. Performed initial atomistic modeling of these materials using various techniques, including machine learned potentials. Future work includes temperature dependent transmission measurements of these materials, as well as improving the machine learned potentials with more training data and different machine learned frameworks.

ARCS↗

Homopolyrotaxanes and Homopolyrotaxane Networks of PEO

In order to identify the optimum size of macrocrown ether for threading, we first investigated the size and shape of simple crown ethers in the melt at 373 K, and their extent of threading with PEO in the melt using coarse-grained Monte Carlo simulations on the 2nnd (second nearest neighbor diamond) lattice, which is a high coordination lattice whose coarse-grained chains can be reverse mapped into fully atomistic models in continuous space.

Pugh, Coleen↗

Site preference of ternary alloying additions to NiTi: Fe, Pt, Pd, Au, Al, Cu, Zr and Hf

Atomistic modeling of the site substitution behavior of Pd in NiTi (J. Alloys and Comp. (2004), in press) has been extended to examine the behavior of several other alloying additions, namely, Fe, Pt, Au, Al, Cu, Zr and Hf in this important shape memory alloy. It was found that all elements, to a varying degree, displayed absolute preference for available sites in the deficient sublattice. How- ever, the energetics of the different substitutional schemes, coupled with large scale simulations indicate that the general trend in all cases is for the ternary addition to want to form stronger ordered structures with Ti.

Bozzolo, Guillermo↗

Site Preference of Ternary Alloying Additions to AuTi

Atomistic modeling of the site substitution behavior of several alloying additions, namely. Na, Mg, Al, Si. Sc, V, Cr, Mn. Fe, Co, Ni, Cu, Zn, Y, Zr. Nb, Mo, Tc, Ru, Rh, Pd, Ag, Cd, Hf, Ta, W, Re, Os, Ir, and Pt in B2 TiAu is reported. The 30 elements can be grouped according to their absolute preference for a specific site, regardless of concentration, or preference for available sites in the deficient sublattice. Results of large scale simulations are also presented, distinguishing between additions that remain in solution from those that precipitate a second phase.

Bozzolo, Guillermo↗

Phase Structure and Site Preference Behavior of Ternary Alloying Additions to PdTi and PtTi Shape-Memory Alloys

The phasc structure and concentration dependence of the lattice parameter and energy of formation of ternary Pd-'I-X and Pt-Ti-X alloys for a large number of ternary alloying additions X (X = Na, Mg, Al, Si, Sc. V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Y, Zr, Nb, Mo, Tc, Ru, Rh, Ag, Cd, Hf, Ta, W, Re, Os, Ir) are investigated with an atomistic modeling approach. In addition, a detailed description of the site preference behavior of such additions showing that the elements can be grouped according to their absolute preference for a specific site, regardless of concentration, or preference for available sites in the deficient sublattice is provided.

Bozzolo, Guillermo↗

Effects of Cr and Nb alloying additions on high temperature creep deformation of Ni-based superalloys

Micro-twinning is the major creep deformation mechanism in Ni-based superalloys at temperatures above 700 °C. Recent experiments suggest that superlattice stacking faults y ' in phase may serve as the precursors to twin formation. Segregation of alloying elements to these precursors may have a significant effect on formation and extension of micro-twins. Using atomistic modeling we investigate and explain the effects of Cr and Nb alloying additions on these processes. We consider the experimentally obtained creep curves for several Ni-based superalloys with different elemental compositions and relate the observed trends to the simulation results presented in this study. Our results help to rationalize the experimentally observed puzzling effects of elemental composition of the alloy on creep resistance.

Valery V. Borovikov↗

Effects of Cr and Nb Alloying Additions on High Temperature Creep Deformation of Ni-Based Superalloys

Micro-twinning is the major creep deformation mechanism in Ni-based superalloys at temperatures above 700 C°. Recent experiments suggest that superlattice stacking faults in phase may serve as the precursors to twin formation. Segregation of alloying elements to these precursors may have a significant effect on formation and extension of micro-twins. Using atomistic modeling we investigate and explain the effects of Cr and Nb alloying additions on these processes. We consider the experimentally obtained creep curves for several Ni-based superalloys with different elemental compositions and relate the observed trends to the simulation results presented in this study. Our results help to rationalize the experimentally observed puzzling effects of elemental composition of the alloy on creep resistance.

Ni-based superalloys↗

Atomistic Cohesive Zone Models for Interface Decohesion in Metals

Using a statistical mechanics approach, a cohesive-zone law in the form of a traction-displacement constitutive relationship characterizing the load transfer across the plane of a growing edge crack is extracted from atomistic simulations for use within a continuum finite element model. The methodology for the atomistic derivation of a cohesive-zone law is presented. This procedure can be implemented to build cohesive-zone finite element models for simulating fracture in nanocrystalline or ultrafine grained materials.

Yamakov, Vesselin I.↗

Atomistic Method Applied to Computational Modeling of Surface Alloys

The formation of surface alloys is a growing research field that, in terms of the surface structure of multicomponent systems, defines the frontier both for experimental and theoretical techniques. Because of the impact that the formation of surface alloys has on surface properties, researchers need reliable methods to predict new surface alloys and to help interpret unknown structures. The structure of surface alloys and when, and even if, they form are largely unpredictable from the known properties of the participating elements. No unified theory or model to date can infer surface alloy structures from the constituents properties or their bulk alloy characteristics. In spite of these severe limitations, a growing catalogue of such systems has been developed during the last decade, and only recently are global theories being advanced to fully understand the phenomenon. None of the methods used in other areas of surface science can properly model even the already known cases. Aware of these limitations, the Computational Materials Group at the NASA Glenn Research Center at Lewis Field has developed a useful, computationally economical, and physically sound methodology to enable the systematic study of surface alloy formation in metals. This tool has been tested successfully on several known systems for which hard experimental evidence exists and has been used to predict ternary surface alloy formation (results to be published: Garces, J.E.; Bozzolo, G.; and Mosca, H.: Atomistic Modeling of Pd/Cu(100) Surface Alloy Formation. Surf. Sci., 2000 (in press); Mosca, H.; Garces J.E.; and Bozzolo, G.: Surface Ternary Alloys of (Cu,Au)/Ni(110). (Accepted for publication in Surf. Sci., 2000.); and Garces, J.E.; Bozzolo, G.; Mosca, H.; and Abel, P.: A New Approach for Atomistic Modeling of Pd/Cu(110) Surface Alloy Formation. (Submitted to Appl. Surf. Sci.)). Ternary alloy formation is a field yet to be fully explored experimentally. The computational tool, which is based on the BFS (Bozzolo, Ferrante, and Smith) method for the calculation of the energetics, consists of a small number of simple PCbased computer codes that deal with the different aspects of surface alloy formation. Two analysis modes are available within this package. The first mode provides an atom-by-atom description of real and virtual stages 1. during the process of surface alloying, based on the construction of catalogues of configurations where each configuration describes one possible atomic distribution. BFS analysis of this catalogue provides information on accessible states, possible ordering patterns, and details of island formation or film growth. More importantly, it provides insight into the evolution of the system. Software developed by the Computational Materials Group allows for the study of an arbitrary number of elements forming surface alloys, including an arbitrary number of surface atomic layers. The second mode involves large-scale temperature-dependent computer 2. simulations that use the BFS method for the energetics and provide information on the dynamic processes during surface alloying. These simulations require the implementation of Monte-Carlo-based codes with high efficiency within current workstation environments. This methodology capitalizes on the advantages of the BFS method: there are no restrictions on the number or type of elements or on the type of crystallographic structure considered. This removes any restrictions in the definition of the configuration catalogues used in the analytical calculations, thus allowing for the study of arbitrary ordering patterns, ultimately leading to the actual surface alloy structure. Moreover, the Monte Carlo numerical technique used for the large-scale simulations allows for a detailed visualization of the simulated process, the main advantage of this type of analysis being the ability to understand the underlying features that drive these processes. Because of the simplicity of the BFS method for e energetics used in these calculations, a detailed atom-by-atom analysis can be performed at any point in the simulation, providing necessary insight on the details of the process. The main objective of this research program is to develop a tool to guide experimenters in understanding and interpreting often unexpected results in alloy formation experiments. By reducing the computational effort without losing physical accuracy, we expect that powerful simulation tools will be developed in the immediate future, which will allow material scientists to easily visualize and analyze processes at a level not achievable experimentally.

Bozzolo, Guillermo H.↗

Spin-informed universal graph neural networks for simulating magnetic ordering

The screening and discovery of magnetic materials are hindered by the computational cost of first-principles density-functional theory (DFT) calculations required to find the ground state magnetic ordering. Although universal machine-learning interatomic potentials (uMLIPs), also known as atomistic foundation models, offer high-fidelity models of many atomistic systems with significant speedup, they currently lack the inputs required for predicting magnetic ordering. In this work, we present a data-efficient, spin-informed graph neural network framework that incorporates spin degrees of freedom as inputs and preserves physical symmetries, extending the functionality of uMLIPs to simulate magnetic orderings. This framework speeds up DFT calculations through better initial guesses for magnetic moments, determines the ground-state ordering of bulk materials and even generalizes to magnetic ordering in surfaces. Furthermore, we implement a closed-loop anomaly detection approach that effectively addresses the classic "chicken-and-egg" problem of creating a high-quality dataset while developing a uMLIP, unearthing anomalies in large benchmark datasets and boosting model accuracy.

Xu, Wenbin↗