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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Free-Energy Landscapes and Surface Dynamics in Methane Activation on Ni(511) via Machine Learning and Enhanced Sampling

Methane activation on stepped Ni(511) surfaces involves the rearrangement of surface atoms as the chemical reaction proceeds. This process is particularly sensitive to temperature. Using machine-learned interatomic potentials (MLIPs) coupled with enhanced sampling techniques, we investigate the activation of methane under realistic operando conditions. Our analysis reveals that methane dissociation occurs predominantly at step-edge nickel atoms. As CH x (where x = 3 or 4) species bind to additional surface nickel atoms, their reduced mobility leads to entropic penalties that suppress certain configurations and transition states. This is reflected in the underlying free energy surfaces, where configurations such as methyl binding to hollow sites and activation routes involving two nickel atoms become unfavorable as temperature increases. At elevated temperatures, methane activation extends from step-edge sites to terrace regions because of reduced free-energy barriers and enhanced surface dynamics. By decomposing the free-energy into enthalpic and entropic contributions, we uncover temperature-dependent shifts in the preferences of methane for the relevant active sites and arrive at a detailed molecular picture of methane activation.

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

A molecular dynamics survey study of impact-induced amorphization in yttria nanoparticles

The impact of a single yttria (Y 2 O 3 ) nanoparticle onto a yttria substrate was studied as a function of particle velocity (300–1200 m/s) and diameter (5–12 nm) for three particle orientations and two substrate orientations using molecular dynamics simulations. Impacts resulted in minimal dislocation motion but extensive disordering of the crystal lattice without approaching the melting temperature. The resulting amorphous microstructure was both precisely coincident with plastic strain and retained until the end of the simulation, suggesting a deformation mechanism of amorphization-facilitated viscous flow. Further analysis revealed that the degree of amorphization depended primarily on the impact velocity and secondarily on the orientations of the particle and substrate, with significant second-order effects from variable interactions.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Role of dislocations on martensitic transformation temperatures and microstructure: A molecular dynamics study

Microstructure and defects strongly affect martensitic transformations in metallic alloys. Significant progress has been made in understanding the atomic-level processes that control the role of grain boundaries and precipitates in these solid-to-solid phase transformations. Yet, the role of dislocations and their structures on martensitic transformation temperature and the resulting microstructure remains unclear. Therefore, we used large-scale molecular dynamics simulations to study the forward and reverse transformation of a martensitic material modeled after Ni63Al37 under cyclic thermal loading. The simulations reveal that dislocations in the austenite phase act as one-dimensional seeds for the martensite phase, which is present at temperatures significantly above the martensite start value. We find a reduction in the dislocation density during cyclic thermal loading, which results in the increase in martensite and austenite transition temperatures, in agreement with experiments. Importantly, we extracted a critical martensitic nuclei size for developing stable domains and found that relatively low dislocation densities are needed to grow independent martensitic variants resulting in a multi-domain structure.

Physics↗
DOE OSTI2026

Neural network potentials with effective charge separation for non-equilibrium dynamics of ionic solids: a ZnO case study

Developing neural network potentials (NNPs) accurate under non-equilibrium dynamics is challenging, as such systems require extensive sampling beyond equilibrium phases. Here we construct high-fidelity NNPs for zinc oxide (ZnO), a polymorphic ionic solid, using density functional theory (DFT) reference data. To efficiently capture transitional configurations, we combine enhanced-sampling molecular dynamics with empirical potentials, data distillation, and pretraining on short-range atomic energies (A-Train), followed by transfer learning with DFT-relabeled datasets. This hierarchical approach improves transferability across polymorphs and stress states. We further introduce effective charge separation, treating long-range Coulombic terms analytically while short-range residual interactions are learned by the NNP. The optimal effective charges fall in the range 0.5–1.0 q e , consistent with dielectric-screened values derived from formal charges but distinct from Bader estimates. Motivated by this observation, we propose a simple data-driven protocol in which effective charges are optimized by comparing DFT reference energies with explicit Coulomb calculations, without additional NNP training. This strategy improves accuracy and transferability in DFT-level predictions of energies, forces, and stress. Together, these results provide a practical charge-selection framework for robust NNP development in ionic solids, enabling reliable simulation of polymorphic phase transformations and non-equilibrium dynamics.

Chemistry↗
DOE OSTI2022

ORNL_AISD_NiNb

This dataset describes the nickel-niobium solid solution binary alloy, where the two constituent elements nickel (Ni) and niobium (Nb) are randomly placed on an underlying crystal lattice. This dataset for nickel-niobium (Ni-Nb) alloys available includes the formation energy and bulk modulus for each crystal structure. Each atomic sample has a disordered phase which is obtained starting from an initial regular crystal structure of type body-centered cubic (BCC), face-centered cubic (FCC), or hexagonal compact packed (HCP). The geometry optimization ensures that all the alloy samples reached the equilibrium with negative formation energy. We perform geometry optimizations using the LAMMPS simulation package [1], a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. We utilized the embedded atom model (EAM) potential for Ni and Nb developed in a previous study [2]. The potential could describe behaviors of the liquid and solid phases of Ni-Nb alloy. The structural factors and angular distributions of three atoms are well-matched with X-ray and ab initio-based molecular dynamics data. We prepared the three different crystals with different initial lattice parameters (3.52 Ã… for FCC, 3.32 Ã… for BCC, and 3.5 Ã… for HCP). We performed energy minimization in two steps. Firstly, we minimized the structures with an isotropic unit cell to minimize the side effects from our arbitrary lattice parameters for all other compositions. Then, we applied geometry optimization with a triclinic (non-orthogonal) unit cell to fully minimize the stress components to calculate the elastic constants. In this procedure, we chose 10,000 as the maximum number of allowable steps aimed at obtaining fully relaxed atomic geometries. The dataset consists of three sets of crystal structures. The first set contains 46,086 irregular crystal structures, each of them with 54 atoms, obtained through optimization starting from a regular BCC crystal structure. The second set contains 24,543 irregular crystal structures, each of them with 32 atoms, obtained through optimization starting from a regular FCC crystal structure. The third set contains 39,303 irregular crystal structures, each of them with 48 atoms, obtained through optimization starting from a regular HCP crystal structure. The atomic configurations within each set span the possible compositional range. The three sets have been unified in a global dataset, which is extremely heterogeneous in terms of crystal structures, lattice volumes, and atomic configurations. Organization of files inside the dataset: the dataset contains three subdirectories called • BCC_opt • FCC_opt • HCP_opt based on the type of initial regular structure used to start the geometry optimization. Inside each of these folders, every atomic structure is identified by a string “A_B_Câ€, where A denotes the number of Nb in the system, B denotes index of structure with a given Nb number, and C denotes the total number of structures generated with a given Nb number. For each optimized crystal structure identified by the unique string of characters “A_B_Câ€, three files are provided: • A_B_C_opt.xyz: The optimized geometries in xyz format • A_B_C_opt.cfg: The optimized geometries in cfg format. It includes cell information and atomic energy, and forces calculated from LAMMPS. • A_B_C.elastic: Raw data of 21 elastic constants from LAMMPS output. • A_B_C.bulk: Calculated upper and lower bounds of bulk modulus and averaged one based on Voigt-Reuss-Hill approach from *.elastic. References: [1] A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in 't Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, and S. J. Plimpton. LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comp. Phys. Comm., 271:108171, 2022. [2] Y Zhang, R Ashcraft, MI Mendelev, CZ Wang, and KF Kelton. Experimental and molecular dynamics simulation study of structure of liquid and amorphous ni62nb38 alloy. The Journal of chemical physics, 145(20):204505, 2016.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Understanding Proton Movement in [Fe-Fe] Hydrogenases

Nature uses specialized metalloenzymes to carry out small molecule activation reactions, including CO 2 fixation, O 2 activation, and proton reduction, with unparalleled efficiency, rates, and selectivity. The latter reactions are performed by hydrogenases, protein metallo-complexes that interconverts H 2 to protons and electrons (H 2 oxidation) and the reverse reaction (H 2 production) with incredibly low energy input and amazingly fast kinetics. Reproducing both the activity and efficiency of metalloenzymes in sustainable anthropogenic systems remains one of the “holy grails” of inorganic chemistry. However, identifying the precise molecular components responsible for these desirable properties has been challenging in the natural metalloenzymes, hindering efforts to develop analogous processes in synthetic compounds. Considering the inherent complexity of a metalloenzyme and the many interactions, both strong and weak, that contribute to the function of an enzyme, we have elected to model natural metalloenzymes on a biochemical platform. Towards this end, we have a developed structural, functional, and mechanistic mimic of the [Ni-Fe] hydrogenases within a robust protein scaffold, rubredoxin, to understand the influence of the secondary coordination environment on the metal center. This involved preparing a series of three rubredoxin constructs containing a single point mutation at Val positions and making the NMR chemical shift assignments for the paramagnetic (nickel-substituted) and non-paramagnetic (zinc-substituted) form. These physical studies were complemented with in silico molecular dynamic studies on proteins with [Fe-S] clusters to engineer new proton channels to test in vitro . To assist our search for new natural metalloprotein scaffolds within the vast number of sequenced genomes, we created a neural network-based program to identify proteins with specific metal-binding sites. These computational and physical studies with metalloenzymes provide direct insight into the fundamental chemical principles driving the natural systems and offer design principles for developing catalysts that utilize analogous principles.

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

The Atomic Drill Bit: Precision Controlled Atomic Fabrication of 2D Materials

The ability to deterministically fabricate nanoscale architectures with atomic precision is the central goal of nanotechnology, whereby highly localized changes in the atomic structure can be exploited to control device properties at their fundamental physical limit. Here, an automated, feedback-controlled atomic fabrication method is reported and the formation of 1D–2D heterostructures in MoS 2 is demonstrated through selective transformations along specific crystallographic orientations. The atomic-scale probe of an aberration-corrected scanning transmission electron microscope (STEM) is used, and the shape and symmetry of the scan pathway relative to the sample orientation are controlled. The focused and shaped electron beam is used to reliably create Mo 6 S 6 nanowire (MoS-NW) terminated metallic-semiconductor 1D–2D edge structures within a pristine MoS 2 monolayer with atomic precision. From these results, it is found that a triangular beam path aligned along the zig-zag sulfur terminated (ZZS) direction forms stable MoS-NW edge structures with the highest degree of fidelity without resulting in disordering of the surrounding MoS 2 monolayer. Density functional theory (DFT) calculations and ab initio molecular dynamic simulations (AIMD) are used to calculate the energetic barriers for the most stable atomic edge structures and atomic transformation pathways. These discoveries provide an automated method to improve understanding of atomic-scale transformations while opening a pathway toward more precise atomic-scale engineering of materials.

2D materials↗
DOE OSTI2023

Emergent Z 2 Gauge Theories and Topological Excitations in Rydberg Atom Arrays

Strongly interacting arrays of Rydberg atoms provide versatile platforms for exploring exotic many-body phases and dynamics of correlated quantum systems. Motivated by recent experimental advances, we show that the combination of Rydberg interactions and appropriate lattice geometries naturally leads to emergent Z 2 gauge theories endowed with matter fields. Based on this mapping, we describe how Rydberg platforms could realize two distinct classes of topological Z 2 quantum spin liquids, which differ in their patterns of translational symmetry fractionalization. Additionally, we also discuss the natures of the fractionalized excitations of these Z 2 spin liquid states using both fermionic and bosonic parton theories and illustrate their rich interplay with proximate solid phases.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

In vitro investigation of protein assembly by combined microscopy and infrared spectroscopy at the nanometer scale

The nanoscale structure and dynamics of proteins on surfaces has been extensively studied using various imaging techniques, such as transmission electron microscopy and atomic force microscopy (AFM) in liquid environments. These powerful imaging techniques, however, can potentially damage or perturb delicate biological material and do not provide chemical information, which prevents a fundamental understanding of the dynamic processes underlying their evolution under physiological conditions. Here, we use a platform developed in our laboratory that enables acquisition of infrared (IR) spectroscopy and AFM images of biological material in physiological liquids with nanometer resolution in a cell closed by atomically thin graphene membranes transparent to IR photons. In this work, we studied the self-assembly process of S-layer proteins at the graphene-aqueous solution interface. The graphene acts also as the membrane separating the solution containing the proteins and Ca 2+ ions from the AFM tip, thus eliminating sample damage and contamination effects. The formation of S-layer protein lattices and their structural evolution was monitored by AFM and by recording the amide I and II IR absorption bands, which reveal the noncovalent interaction between proteins and their response to the environment, including ionic strength and solvation. Our measurement platform opens unique opportunities to study biological material and soft materials in general.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Shear Softening in a Metallic Glass: First-Principles Local-Stress Analysis

Metallic glasses deform elastically under stress. However, the atomic-level origin of elastic properties of metallic glasses remain unclear. In this Letter using ab initio molecular dynamics simulations of the Cu 5 0Zr 50 metallic glass under shear strain, we show that the heterogeneous stress relaxation results in the increased charge transfer from Zr to Cu atoms, enhancing the softening of the shear modulus. Changes in compositional short-range order and atomic position shifts due to the nonaffine deformation are discussed. It is shown that the Zr subsystem exhibits a stiff behavior, whereas the displacements of Cu atoms from their initial positions, induced by the strain, provide the stress drop and softening.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Vapor-phase self-assembly for generating thermally stable single-atom catalysts

Preparation of thermally stable metal single-atom catalysts (SACs) is a challenge in heterogeneous catalysis, especially on conventional supports that provide a weak metal-support interaction. In this work, we report that a modified support MgAl 2 O 4 can stabilize Pt single atoms by a mechanism of vapor-phase self-assembly in a high-temperature treatment (800°C, air). The experimental results on the formation mechanism and the structure are validated by DFT and ab initio molecular dynamics simulations. We infer that stable triangular K 3 O 3 structures help stabilize Pt single atoms at high temperatures in oxidizing conditions, exhibiting excellent reactivity for methane oxidation. The obtained Pt/K/MgAl 2 O 4 SAC presents excellent stability in methane oxidation after steam treatment at elevated temperatures, whereas the Pt/MgAl 2 O 4 nanocatalyst suffers from rapid deactivation due to Pt nanoparticle growth. Now this work paves the way for preparing thermally stable and highly active SACs using conventional high-surface-area supports, despite the weak metal-support interaction.

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

CFD Simulations of Metal Powder Production by Gas Atomization

Many crucial components in energy production, e.g., stationary gas turbines and A-USCS power plants, are desirable to manufacture by additive manufacturing (AM) with the full development of the materials and processes. Typical gas atomized (GA) feedstock for metal AM is produced in spherical powder form, but often inefficiently with a wide size distribution and with reduced quality, e.g., having internal porosity, heavily oxidized surfaces, and “satellites” that degrade printing and build quality. The proposed project aims to significantly enhance the efficiency/precision and, moreover, the quality of metal powder production by computational fluid dynamics (CFD) simulations, probing the details of the physical processes occurring in supersonic gas atomizers. The goals are improving the desired powder size range yield and quality of GA powder, reducing material and energy production costs, and helping fulfill the immense the potential of AM, thereby enhancing the competitiveness of US manufacturing and of energy and transport sectors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Lytic polysaccharide monooxygenase increases cellobiohydrolases activity by promoting decrystallization of cellulose surface

Efficient depolymerization of crystalline cellulose requires cooperation between multiple cellulolytic enzymes. Through biochemical approaches, molecular dynamics (MD) simulation, and single-molecule observations using high-speed atomic force microscopy (HS-AFM), we quantify and track synergistic activity for cellobiohydrolases (CBHs) with a lytic polysaccharide monooxygenase (LPMO) from Phanerochaete chrysosporium. Increasing concentrations of LPMO (AA9D) increased the activity of a glycoside hydrolase family 6 CBH, Cel6A, whereas the activity of a family 7 CBH (Cel7D) was enhanced only at lower concentrations of AA9D. MD simulation suggests that the result of AA9D action to produce chain breaks in crystalline cellulose can oxidatively disturb the crystalline surface by disrupting hydrogen bonds. HS-AFM observations showed that AA9D increased the number of Cel7D molecules moving on the substrate surface and increased the processivity of Cel7D, thereby increasing the depolymerization performance, suggesting that AA9D not only generates chain ends but also amorphizes the crystalline surface, thereby increasing the activity of CBHs.

09 BIOMASS FUELS↗
DOE OSTI2022

Effect of quasiperiodic and random noise on many-body dynamical decoupling protocols

Symmetries (and their spontaneous rupturing) can be used to protect and engender novel quantum phases and lead to interesting collective phenomena. In the work of K. Agarwal and I. Martin, the authors described a general dynamical decoupling (polyfractal) protocol that can be used to engineer multiple discrete symmetries in many-body systems. This work expands on the former by studying the effect of quasiperiodic and random noise on such a dynamical scheme. We find generally that relaxation of engineered symmetry generators proceeds by (i) an initial relaxation on microscopic timescales to a prethermal plateau whose height is independent of noise, (ii) a linear relaxation regime with a noise-dependent rate, followed by (iii) a slow logarithmic relaxation regime that is only present for quasiperiodic noise. We glean the essential features of these regimes via scaling collapses and show that they can be generally explained by the spectral properties of the various noise waveforms considered. In particular, the quasiperiodic noise is characterized by highly time-dependent spectrum with a noise floor that mimics white noise, and peaks that grow sharper with time. We argue that both the noise floor and peaks contribute to the initial linear-in-time relaxation while the logarithmic regime is initiated when the peaks become sufficiently well resolved and cease to contribute to further relaxation. Here, we provide numerical evidence to justify these findings.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Computational and experimental analysis of structural and Thermophysical properties of LiX-KX (X = chloride, iodide, or bromide) molten salts

Molten salts containing lithium (Li) and potassium (K) halides, including chlorides (Cl), bromides (Br), and iodides (I), are pivotal in advanced technological applications including nuclear reactor technologies, thermal batteries, and industrial pyrochemical processes. Despite their significance, the availability of the temperature-dependent structural and thermophysical properties of these molten salts remain scarce. Here, this study addresses this knowledge gap by predicting and measuring the key properties such as coordination number, radial distribution function, density, heat capacity, and volumetric thermal expansion of molten LiI-KI, LiBr-KBr and LiCl-KCl eutectic mixtures. Utilizing ab initio molecular dynamics (AIMD) simulations, we predict these properties of LiX-KX (X=Br,I, Cl) across various temperatures, with chlorides as a benchmark. Experimental measurements using Archimedes methods and Differential Scanning Calorimetry validate the densities and heat capacities of these molten salts. Our comprehensive analysis of the structural and thermophysical properties provides critical insights into the behavior of these molten salts at various temperatures, enhancing the understanding necessary for their application in advanced technologies.

36 - MATERIALS SCIENCE↗
DOE OSTI2021

Bound state dynamics in the long-range spin- 1 2 XXZ model

Experimental platforms based on trapped ions, cold molecules, and Rydberg atoms have made possible the investigation of highly nonlocal spin-1 / 2 Hamiltonians with long-range couplings. Here, we study the effects of such nonlocal couplings in the long-range spin-1 / 2 XXZ Heisenberg Hamiltonian. Here, we calculate explicitly the two-spin energy spectrum, which describes all possible energetic configurations of two spins pointing in a specific direction embedded in a background of spins with opposite orientation. For fast decay of the spin-spin couplings, we find that the two-spin energy spectrum is characterized by well-defined discrete values, corresponding to bound states, separated by a set of continuum states describing the scattering region. In the deep long-range regime instead, the bound states disappear as they get incorporated by the scattering region. The presence of two-spin bound states results to be crucial to determine both two- and many-spin dynamics. On one hand, radically different two-spin spreadings can be observed by tuning the decay of the spin couplings. On the other hand, two-spin bound states enable the dynamical stabilization of effective antiferromagnetic states in the presence of ferromagnetic couplings. Finally, we propose a novel scheme based on a trapped-ion quantum simulator to experimentally realize the long-range XXZ model and to study its out-of-equilibrium properties.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

TeraChem: A graphical processing unit-accelerated electronic structure package for large-scale ab initio molecular dynamics

TeraChem was born in 2008 with the goal of providing fast on-the-fly electronic structure calculations to facilitate ab initio molecular dynamics studies of large biochemical systems such as photoswitchable proteins and multichromophoric antenna complexes. Originally developed for videogaming applications, graphics processing units (GPUs) offered a low-cost parallel computer architecture that became more accessible for general-purpose GPU computing with the release of CUDA in 2007. The evaluation of the electron repulsion integrals (ERIs) is a major bottleneck in electronic structure codes and provides an attractive target for acceleration on GPUs. Thus, highly efficient routines for evaluation of and contractions between the ERIs and density matrices were implemented in TeraChem. Here, electronic structure methods were developed and implemented to leverage these integral contraction routines, resulting in the first quantum chemistry package designed from the ground up for GPUs. This GPU acceleration makes TeraChem capable of performing large-scale ground and excited state calculations in the gas and condensed phase. Today, TeraChem's speed forms the basis for a suite of quantum chemistry applications, including optimization and dynamics of proteins, automated and interactive chemical discovery tools, and large-scale nonadiabatic dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Effects of carbon concentration on the local atomic structure of amorphous GST

Ge-Sb-Te (GST) alloys are leading phase-change materials for data storage due to the fast phase transition between amorphous and crystalline states. Ongoing research aims at improving the stability of the amorphous phase to improve retention. This can be accomplished by the introduction of carbon as a dopant to Ge 2 Sb 2 Te 5 , which is known to alter the short- and mid-range structure of the amorphous phase and form covalently bonded C clusters, both of which hinder crystallization. The relative importance of these processes as a function of C concentration is not known. Here we used molecular dynamics simulation based on density functional theory to study how carbon doping affects the atomic structure of GST-C. Carbon doping results in an increase in tetrahedral coordination, especially of Ge atoms, and this is known to stabilize the amorphous phase. We observe an unexpected, non-monotonous trend in the number of tetrahedral bonded Ge with the amount of carbon doping. Our simulations show an increase in the number of tetrahedral bonded Ge up to 5 at.% C, after which the number saturates and begins to decrease above 14 at.% C. The carbon atoms aggregate into clusters, mostly in the form of chains and graphene flakes, leaving less carbon to disrupt the GST matrix at higher carbon concentrations. Different degrees of carbon clustering can explain divergent experimental results for recrystallization temperature for carbon doped GST.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗