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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 OSTI2025

Effect of Ni deposition on CrI 3 monolayer: First-principles study

In our recent experimental work, we demonstrated that Ni thin film deposition can be used to tune the surface magnetic states in bulk CrI 3 . Here, we present the results of a computational study of Ni deposition on a CrI 3 monolayer. In particular, we compare structural, electronic, and magnetic properties of three different systems: a pristine CrI 3 monolayer, a CrI 3 monolayer with partial Ni coverage, and a CrI 3 monolayer with full Ni coverage. The corresponding cells used in our calculations are Cr 2 I 6 , Cr 2 I 6 Ni 1 , and Cr 2 I 6 Ni 3 . In Cr 2 I 6 Ni 1 , the Ni atom is positioned over the hollow site, which corresponds to the lowest energy configuration. In Cr 2 I 6 Ni 3 , the three Ni atoms are positioned over the single hollow site, and over the two Cr sites. Our calculations indicate that the partial coverage of CrI 3 monolayer with Ni retains the semiconducting nature of the parent compound, but results in a strong reduction of the energy band gap. At the same time, the full coverage of CrI 3 monolayer with Ni results in a metallic transition, with a highly spin-polarized (possibly half-metallic) electronic structure. The magnetic alignment of the CrI 3 monolayer with the deposited Ni is ferrimagnetic, due to the anti-aligned magnetic moments of Cr and Ni atoms. While the partial coverage of the CrI 3 monolayer with Ni has a moderate impact on the lattice parameter of the parent compound, full coverage by Ni results in a significant increase of the lattice constant. For both partial and full coverages, the lowest energy configuration corresponds to the Ni atoms being approximately aligned with the out-of-plane coordinate of the surface iodine layer. In addition, in the full coverage mode, the Cr layer exhibits a significant shift away from the Ni atoms, effectively “detaching” the Ni / I atomic layer from the rest of the cell.

2D magnetism↗
DOE OSTI2022

Accurate Fe–He machine learning potential for studying He effects in BCC-Fe

Nanostructured Ferritic Alloys (NFAs) containing oxide nanoparticles are prospective advanced structural materials in future fusion reactors. Lacking fusion neutron sources with an adequate flux, modeling is critical to understand radiation damage in the NFAs, including helium effects. Machine learning interatomic potentials (MLPs) have been demonstrated to be capable of describing atomic interactions in chemically complex systems with comparable accuracy to density functional theory (DFT) but with much less computational costs. Hence, MLPs are chosen to study He bubble accumulation in chemically complex NFAs. As a preliminary step, we develop a Fe–He potential, based on ~10,000 atomic configurations. The developed MLP accurately predicts the bulk properties of BCC-Fe compared to DFT, including the lattice constant (2.832 Å), elastic constants (c 11 = 271 GPa, c 12 = 141, c 44 = 93), and phonon frequencies (maximum error < 3.5%). The MLP predicts He binding energies in He n V bubbles and He n clusters with a mean absolute error (MAE) of only ~70 meV, which is ~3 to ~5 times smaller than the MAE of binding energies estimated using empirical potentials. The MLP also accurately predicts the migration barrier of interstitial He (64 meV). Furthermore, the MLP correctly predicts the maximum number of He atoms (critical size) at which a He n V bubble (He n cluster) can kick-out a self-interstitial atom (SIA), forming a bigger He n V 2 bubble (He n V bubble). Subsequently, we use the MLP to perform molecular dynamics simulations to investigate the effect of temperature on the critical size of He n V bubbles and He n clusters. We find that the critical size decreases with increasing temperature — indicating that smaller bubbles and clusters can kick-out an SIA at higher temperatures, thereby escalating the He bubble growth. We report the current Fe–He MLP can be further developed to include all chemical interactions in NFAs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Hot Hydrogen Exposure of U x Zr 1-x C y Nuclear Fuel: The Influence of Composition and Density

Refractory carbide nuclear fuel has been one of the most promising fuel candidates for space nuclear propulsion due to its high melting point, temperature stability, and compatibility in a hot hydrogen environment. In this study, U x Zr 1-x C y fuel was produced by means of a carbothermic reduction process in different UC compositions including 5,10, 20, and 30 at.% UC in the fuel compound. The powder feedstock was consolidated via direct current sintering with densities up to 97% of the theoretical density. The samples with different U x Zr 1-x C y compositions were exposed to hot hydrogen at 2600 K for a cumulative time of 300 min. The samples were characterized by SEM, XRD, density, and measured for mass losses. The high-density samples displayed improved performance in hot hydrogen by minimizing porous sites and reducing areas of direct contact with hydrogen gas, leading to reduced mass losses. Variations in sample density proved to induce large changes in mass loss rates, increasing them up to 90%. The compositions with higher UC content reported the largest mass losses in the study. The loss of uranium occurred primarily at the surfaces exposed to the hot hydrogen where changes in the lattice constant confirmed losses exceeding 50% of the initial UC content in higher compositions, specifically to U 0.3 Zr 0.7 C y . XRD analyses revealed the presence of UH 3 in U 0.3 Zr 0.7 C y suggesting that metallic uranium formed inside the sample as a product of carbon losses. High-density U x Zr x-1 C y fuel with UC concentrations at or below 20 at.% UC exhibited stability and negligible density changes in a high temperature hydrogen environment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Extended defects in GaAs/GaAs 1-x Sb x /GaAs (001) heterostructures

The atomic-scale structure of extended defects in GaAs/GaAs 1-x Sb x /GaAs (001) heterostructures has been characterized using aberration-corrected scanning transmission electron microscopy. The defect located at the tensile-strained GaAs(cap)/GaAs 0.34 Sb 0.66 interface had no edge component in the projection plane and is identified as either a dissociated screw dislocation or a partial dislocation dipole. The associated intrinsic stacking fault is bounded by two 30° Shockley partial dislocations of opposite sign. Another defect, located at the compressively-strained GaAs 0.91 Sb 0.09 /GaAs(substrate) interface, is identified as a dissociated 90° dislocation. The associated intrinsic stacking fault is bounded by a 30° Shockley partial dislocation and a partial dislocation with a Burgers vector of either or , where a is the lattice constant. Unpaired atomic columns observed at the cores of the 30° Shockley partial dislocations indicate that both defects belong primarily to the glide set.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Experimental and theoretical investigation of the crystalline surface, film, and interface properties of antiperovskite Mn 3 GaN grown by molecular beam epitaxy on MgO(001)

Here, we present a study of the epitaxial growth, characterization, and theoretical modeling of thin film antiperovskite Mn 3 GaN, an antiferromagnetic material with kagome structure which is grown on MgO (001) substrates using N-plasma-assisted molecular beam epitaxy. Reflection high energy electron diffraction is used to assess the in-plane evolution of the film structure during growth, and the surface is investigated in-situ using scanning tunneling microscopy and Auger electron spectroscopy. These results are combined with precision measurements done ex-situ determining the film lattice constants using a combination of x-ray diffraction with reciprocal space mapping and scanning transmission electron microscopy. Overall, a uniform, homogeneous film with an atomically smooth vacuum surface and atomically sharp substrate interface is found having very small in-plane tensile strain and mild out-of-plane compressive strain. First-principles theoretical calculations are applied in order to ascertain the lowest energy models for both the Mn 3 GaN surface and the Mn 3 GaN/MgO film/substrate interface. Models including MnGa versus MnN surface layers and MnGa versus MnN interfacial layers are considered as functions of both the Mn and Ga chemical potentials. The predictions are discussed in comparison to the experimental results. The overall findings suggest that Mn 3 GaN on MgO(001) is a viable epitaxial film which can be further explored in connection with antiferromagnetic spintronics.

Density functional theory↗
DOE OSTI2023

Epitaxial growth of oriented CoO films by radio-frequency sputtering deposition

Rock-salt CoO is a p-type semiconductor and its Neel temperature is close to room temperature. CoO-based compounds are known as promising systems for renewable energy harvest with high efficiency. CoO with catalytic and exchange bias properties can be widely used for industrial applications. In this paper, we report high-quality stable CoO(111) and (100) films epitaxially grown on c-cut (0001) and r-cut ($10\bar1$2) alpha-Al 2 O 3 substrates, respectively, using radio-frequency sputtering deposition. X-ray diffraction (XRD) measurements revealed that the CoO films had a rock-salt structure (Fm3m) with lattice constants of 4.2477 Å and 4.2617 Å for film grown on (0001) and ($10\bar1$2) α-Al 2 O 3 substrates, respectively. CoO films with the best crystal quality were grown at a substrate temperature of similar to ~700°C. XRD measurements of CoO(111) films indicated a lack of structural residual strain, whereas CoO(100) films had substantial amounts of structural strain. X-ray reflectivity (XRR) and transmission electron microscopy measurements showed neither oxygen vacancy nor defects in both CoO(111) and (100) films. Further, XRR revealed that the mean electron density of the CoO films was nearly identical to a pure CoO and that the films were considerably stable under the atmosphere.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Heteroepitaxial Integration of ZnGeN 2 on GaN Buffers Using Molecular Beam Epitaxy

Recently theorized hybrid II-IV-N 2 /III-N heterostructures, based on current commercialized (In,Ga)N devices, are predicted to significantly advance the design space of highly efficient optoelectronics in the visible spectrum, yet there are few epitaxial studies of II-IV-N 2 materials. In this work, we present heteroepitaxial ZnGeN 2 grown on GaN buffers and AlN templates. We demonstrate that a GaN nucleating surface is crucial for increasing the ZnGeN 2 crystallization rate to combat Zn desorption, extending the stoichiometric growth window from 215 degrees C on AlN to 500 degrees C on GaN buffers. Structural characterization reveals well-crystallized films with threading dislocations extending from the GaN buffer. These films have a critical thickness for relaxation of 20-25 nm as determined by reflection high energy electron diffraction (RHEED) and cross-sectional scanning electron microscopy (SEM). The films exhibit a cation-disordered wurtzite structure, with lattice constants a = 3.216 +/- 0.004 A and c = 5.215 +/- 0.005 A determined by RHEED and X-ray diffraction (XRD). This work demonstrates a significant step toward the development of hybrid ZnGeN 2 -GaN integrated devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials

Here, we present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalytic Pt surface reaction, high-entropy alloys (HEAs), and disordered Zr-oxides. Five MLIP architectures (MACE, NequIP, Allegro, MTP, and Torch-ANI) are trained and tested, focusing not only on traditional metrics (energies, forces, and stresses) but also explicitly validating derived physical observables such as lattice constants, volumes, and reaction barriers. We find that most models reach comparable accuracy on standard error metrics across the simple systems, although equivariant MLIPs offer 1.5–2× improvements over nonequivariant MLIPs in energy and force error for structurally complex or compositionally disordered environments such as HEAs and Zr–O systems. Our analysis highlights that low errors in energy and force predictions do not guarantee reliable observables, emphasizing the necessity of explicit validation. We demonstrate limitations in cross-framework transferability, as models trained on one zeolite framework (CHA) fail to reliably generalize to predictions of structurally distinct frameworks (e.g., MFI). Size-extensive tests show some dependence on system size for MgO, resulting from forced periodicity. The HEA and Zr–O data sets are identified as challenging tests for future benchmarks and MLIP model architecture developments as they show significant differentiation in error between MLIP architectures and are still relatively difficult at 1000 training images. Moving forward, we recommend that benchmarking efforts shift their focus from marginal accuracy improvements in energy and force errors toward identifying and understanding model failure modes, rigorously assessing transferability, and evaluating how their errors affect observable predictions. For researchers looking to choose an MLIP architecture, we suggest selecting equivariant MLIP architectures if the complexity of the system is a challenge. For simple materials problems, auxiliary features such as integration with molecular dynamics engines, trade-offs between computational data set generation cost vs MLIP inference speed, and framework integration may play a more important decision factor than small differences in error metrics that are unlikely to matter for production-level research.

chemical structure↗
DOE OSTI2021

Evaluation of Force Fields for Molecular Dynamics Simulations of Platinum in Bulk and Nanoparticle Forms

Here, understanding the size- and shape-dependent properties of platinum nanoparticles is critical for enabling the design of nanoparticle-based applications with optimal and potentially tunable functionality. Toward this goal, we evaluated nine different empirical potentials with the purpose of accurately modeling faceted platinum nanoparticles using molecular dynamics simulation. First, the potentials were evaluated by computing bulk and surface properties - surface energy, lattice constant, stiffness constants, and the equation of state - and comparing these to prior experimental measurements and quantum mechanics calculations. Then, the potentials were assessed in terms of the stability of cubic and icosahedral nanoparticles with faces in the {100} and {111} planes, respectively. Although none of the force fields predicts all the evaluated properties with perfect accuracy, one potential - the embedded atom method formalism with a specific parameter set - was identified as best able to model platinum in both bulk and nanoparticle forms.

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

Computational Screening of Cationic Zeolites for n -Butane/Methane Separations Using Quantitatively Accurate First-Principles-Derived Force Fields

We developed force fields for linear alkanes in Na and Ca-exchanged zeolites based on periodic first-principles calculations with coupled cluster corrections. These force fields were validated by comparing the simulated adsorption properties with extensive experimental data. As an example of using these force fields, we screened silica and aluminosilicate zeolites for separation of n-butane/methane mixtures in several different separation processes. A key step in this screening was the use of an interpolation method to create accurate zeolite structures that take account of the lattice constant changes for different Si/Al ratios for a given zeolite topology. We focused on zeolite structures that have known synthesis routes, so the materials selected from our calculations can be tested experimentally. Several promising materials that show good separation performance were selected for more detailed simulations.

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

Machine Learning an Ab-Initio Based Bond-Order Potential for Bismuthene

Bismuthene is a heavy 2D material whose strong spin–orbit coupling and recently observed single-element ferroelectricity have intensified interest in its structural, vibrational, and transport properties. Accurate modeling of these behaviors requires a short-range interatomic potential that can reproduce the underlying bonding physics at a fraction of the computational cost of first-principles methods. However, such a potential is currently unavailable. Here, in this work, we construct a Tersoff bond-order potential for β-bismuthene using a reinforcement-learning framework that integrates a continuous Monte Carlo Tree Search with a simplex-based local optimizer. The optimized parameter sets reproduce first-principles lattice constants, cohesive energy, the equation of state, elastic constants, and phonon dispersion. We validate the models by performing thermal-conductivity calculations and uniaxial fracture simulations our findings confirm the reliability of the resulting models across multiple thermomechanical regimes. Comparison of the three best solutions reveals how differences in pairwise interactions, angular terms, and bond-order behavior govern phonon features and mechanical responses. We demonstrate an interpretable and computationally efficient potential for bismuthene and demonstrate a general reinforcement-learning strategy for developing bond-order models in emerging 2D materials.

deformation↗
DOE OSTI2022

Electrodeposition of Complex High Entropy Oxides via Water Droplet Formation and Conversion to Crystalline Alloy Nanoparticles

We report that a combination of electrodeposition and thermal reduction methods have been utilized for the synthesis of ligand-free FeNiCo alloy nanoparticles through a high-entropy oxide intermediate. These phases are of great interest to the electrocatalysis community, especially when formed by a sustainable chemistry method. This is successfully achieved by first forming a complex five element amorphous FeNiCoCrMn high-entropy oxide (HEO) phase via electrodeposition from a nanodroplet emulsion solution of the metal salt reactants. The amorphous oxide phase is then thermally treated and reduced at 570–600 °C to form the crystalline FeNiCo alloy with a separate CrMnO x cophase. The FeNiCo alloy is fully characterized by scanning transmission electron microscopy and energy-dispersive X-ray spectroscopy elemental analysis and is identified as a face-centered cubic crystal with the lattice constant a = 3.52 Å. The unoptimized, ligand-free FeNiCo NPs activity toward the oxygen evolution reaction is evaluated in alkaline solution and found to have an ~185 mV more cathodic onset potential than the Pt metal. Beyond being able to synthesize highly crystalline, ligand-free FeNiCo nanoparticles, the demonstrated and relatively simple two-step process is ideal for the synthesis of tailor-made nanoparticles where the desired composition is not easily achieved with classical solution-based chemistries.

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

Utilizing Site Disorder in the Development of New Energy-Relevant Semiconductors

We report controlling site disorder in ternary and multinary compounds enables tuning optical and electronic properties at fixed lattice constants and stoichiometries, moving beyond many of the challenges facing binary alloy systems. Here, we consider possible enhancements to energy-related applications through the integration of disorder-tunable materials in devices such as light-emitting diodes, photonics, photovoltaics, photocatalytic materials, batteries, and thermoelectrics. However, challenges remain in controlling and characterizing disorder. Focusing primarily on II–IV–V 2 materials, we identify three metrics for experimentally characterizing cation site disorder. Complementary to these experiments, we discuss simulation methods to understand disordered materials. Nonidealities, such as off-stoichiometry and oxygen incorporation, can occur while synthesizing metastable disordered materials. While nonidealities may seem undesirable, we describe how if harnessed they could provide another knob for tuning disorder and subsequently properties. To illustrate the effects of disorder on device-relevant properties, we provide case examples of disordered materials and their potential in device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Coherent Electronic Band Structure of TiTe 2 /TiSe 2 Moiré Bilayer

Here, a van der Waals bonded moiré bilayer formed by sequential growth of TiSe 2 and TiTe 2 monolayers exhibits emergent electronic structure as evidenced by angle-resolved photoemission band mapping. The two monolayers adopt the same lattice orientation but incommensurate lattice constants. Despite the lack of translational symmetry, sharp dispersive bands are observed. The dispersion relations appear distinct from those for the component monolayers alone. Theoretical calculations illustrate the formation of composite bands by coherent electronic coupling despite the weak interlayer bonding, which leads to band renormalization and energy shifts.

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

Slow-Light Mid-IR Silicon Photonic Chips for NO 2 and CH 4 Gas Detection

A compact, chip-scale mid-infrared gas sensor is demonstrated, leveraging a two-dimensional photonic crystal waveguide (PCW) fabricated on a silicon-on-insulator (SOI) platform. The PCW comprises a hexagonal lattice with lattice constant a = 860 nm and hole radius r = 0.22a, incorporating a central line defect of reduced-radius holes (r s = 0.7r) to induce slow-light propagation near the photonic band edge with a group index of approximately 73, thereby enhancing light-matter interaction. The sensor operates at fundamental absorption wavelengths of 3.42 μm for nitrogen dioxide (NO 2 ) and 3.40 μm for methane (CH 4 ), utilizing the strongest molecular vibrational transitions for maximum sensitivity. Experimental validation was conducted using dynamically diluted gas mixtures generated by mass flow controllers, with signal acquisition performed by a liquid nitrogen-cooled InSb detector. For NO 2 , the sensor exhibited excellent linear response over 5–25 ppm (part per million) with coefficient of determination R 2 = 0.9934, achieving a detection limit of 210 ppb (part per billion)─representing the first reported silicon photonic-based NO 2 detection. For CH 4 , exposure to 25 ppm resulted in a 6.4% decrease in transmitted intensity, demonstrating multigas sensing capability. The CMOS-compatible fabrication process and compact 3 mm device footprint establish this SOI-PCW platform as a scalable, low-power solution for integrated mid-infrared gas sensing, with significant potential for environmental monitoring and industrial safety applications.

Crystals↗
DOE OSTI2023

Rotational and dilational reconstruction in transition metal dichalcogenide moiré bilayers

Abstract Lattice reconstruction and corresponding strain accumulation plays a key role in defining the electronic structure of two-dimensional moiré superlattices, including those of transition metal dichalcogenides (TMDs). Imaging of TMD moirés has so far provided a qualitative understanding of this relaxation process in terms of interlayer stacking energy, while models of the underlying deformation mechanisms have relied on simulations. Here, we use interferometric four-dimensional scanning transmission electron microscopy to quantitatively map the mechanical deformations through which reconstruction occurs in small-angle twisted bilayer MoS 2 and WSe 2 /MoS 2 heterobilayers. We provide direct evidence that local rotations govern relaxation for twisted homobilayers, while local dilations are prominent in heterobilayers possessing a sufficiently large lattice mismatch. Encapsulation of the moiré layers in hBN further localizes and enhances these in-plane reconstruction pathways by suppressing out-of-plane corrugation. We also find that extrinsic uniaxial heterostrain, which introduces a lattice constant difference in twisted homobilayers, leads to accumulation and redistribution of reconstruction strain, demonstrating another route to modify the moiré potential.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Machine learning the microscopic form of nematic order in twisted double-bilayer graphene

Modern scanning probe techniques, such as scanning tunneling microscopy, provide access to a large amount of data encoding the underlying physics of quantum matter. In this work, we show how convolutional neural networks can be used to learn effective theoretical models from scanning tunneling microscopy data on correlated moiré superlattices. Moiré systems are particularly well suited for this task as their increased lattice constant provides access to intra-unit-cell physics, while their tunability allows for the collection of high-dimensional data sets from a single sample. Using electronic nematic order in twisted double-bilayer graphene as an example, we show that incorporating correlations between the local density of states at different energies allows convolutional neural networks not only to learn the microscopic nematic order parameter, but also to distinguish it from heterostrain. These results demonstrate that neural networks are a powerful method for investigating the microscopic details of correlated phenomena in moiré systems and beyond.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗