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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Studies of Nucleation and Growth, Specific Heat and Viscosity of Undercooled Melts of Quasicrystals and Polytetrahedral-Phase-Forming Alloys

The local atomic structures of undercooled liquid metals are presumed to be icosahedral; this order is incompatible with translational periodicity, constituting a barrier to the nucleation of the crystal phase. The extended atomic structure of the icosahedral quasicrystal (i-phase) is similar to that presumed in the undercooled liquid. Therefore, a comparison of the maximum undercooling in alloys that form the i-phase with those that form crystal phases provides a probe of the liquid structure.

Kelton, K. F.↗
DOE OSTI2025

Status Report on the Development of Cladding Inner-wall and Outer-wall Coatings

Advanced cladding is critical for nuclear reactors with enhanced performance in radiation tolerance, neutron transparency and reactor safety. Using advanced cladding will ensure the adequate thermal conductivity and mechanical stability of the cladding base material, corrosion resistance and high-temperature coolant compatibility of the cladding surface, and chemical stability in the cladding inner wall against fuel cladding chemical interaction (FCCI). An innovative cladding with a three-layer structure (i.e., a modified outer surface, a robust clad base material, and a modified inner wall) promises to meet all these requirements. In this status report, the initial efforts on the development of cladding inner-wall and outer-wall coatings are summarized. The activities covered in this report are (1) High-resolution TEM studies of TiN/HT-9 interface atomic structure and chemistry after ion irradiation, (2) High-resolution TEM studies of TiN/14YWT ODS interface atomic structure after thermal cycling, (3) Inner-wall TiN coating for an experimental 14YWT ODS cladding, and (4) Corrosion test of TiN coated Ziracloy-4 bar samples.

36 - MATERIALS SCIENCE↗
NASA NTRS2012

Atomic Decay Data for Modeling K Lines of Iron Peak and Light Odd-Z Elements*

Complete data sets of level energies, transition wavelengths, A-values, radiative and Auger widths and fluorescence yields for K-vacancy levels of the F, Na, P, Cl, K, Sc, Ti, V, Cr, Mn, Co, Cu and Zn isonuclear sequences have been computed by a Hartree-Fock method that includes relativistic corrections as implemented in Cowan's atomic structure computer suite. The atomic parameters for more than 3 million fine-structure K lines have been determined. Ions with electron number N greater than 9 are treated for the first time, and detailed comparisons with available measurements and theoretical data for ions with N less than or equal to 9 are carried out in order to estimate reliable accuracy ratings.

modeling K lines↗
DOE OSTI2024

Identification of Defects and the Origins of Surface Noise on Hydrogen–Terminated (100) Diamond

Near-surface nitrogen vacancy centres are critical to many diamond-based quantum technologies such as information processors and nanosensors. Surface defects play an important role in the design and performance of these devices. The targeted creation of defects is central to proposed bottom-up approaches to nanofabrication of quantum diamond processors, and uncontrolled surface defects may generate noise and charge trapping which degrade shallow NV device performance. Surface preparation protocols may be able to control the production of desired defects and eliminate unwanted defects, but only if their atomic structure can first be conclusively identified. This work uses a combination of scanning tunnelling microscopy (STM) imaging and first-principles simulations to identify several surface defects on H:C(100)—2 × 1 surfaces prepared using chemical vapour deposition (CVD). The atomic structure of these defects is elucidated, from which the microscopic origins of magnetic noise and charge trapping are determined based on the modeling of their paramagnetic properties and acceptor states. Rudimentary control of these deleterious properties is demonstrated through STM tip-induced manipulation of the defect structure. Furthermore, the results validate accepted models for CVD diamond growth by identifying key adsorbates responsible for the nucleation of new layers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

CuXASNet: Rapid and accurate prediction of copper L-edge x-ray absorption spectra using machine learning

In this work, we have developed CuXASNet, a dense neural network that predicts simulated Cu -edge x-ray absorption spectra (XAS) from atomic structures. Featurization of the Cu local environment is performed using a component of M3GNet, a graph neural network developed for predicting the potential energy surface. CuXASNet is trained on simulated spectra from FEFF9 at the multiple scattering level of theory, and can predict the and edges for Cu sites to quantitative accuracy. To validate our approach, we compare 14 experimental spectra extracted from the literature with the predictions of CuXASNet. The agreement of CuXASNet with experiments is shown by an average mean absolute error of 0.125 and an average Spearman's correlation coefficient of 0.891, which is comparable to FEFF9's values of 0.131 and 0.898 for the same metrics. As such, CuXASNet can rapidly predict a large number of -edge XAS spectra at the same accuracy as FEFF9 simulations. This can be used as a drop-in replacement for multiple scattering codes for fast screening of candidate atomic structure models of a measured system. This model establishes a general framework for Cu XAS prediction, and can be extended to more computationally expensive levels of theory and to other transition metal edges.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Effects of Atomic-Scale Structure on the Fracture Properties of Amorphous Carbon - Carbon Nanotube Composites

The fracture of carbon materials is a complex process, the understanding of which is critical to the development of next generation high performance materials. While quantum mechanical (QM) calculations are the most accurate way to model fracture, the fracture behavior of many carbon-based composite engineering materials, such as carbon nanotube (CNT) composites, is a multi-scale process that occurs on time and length scales beyond the practical limitations of QM methods. The Reax Force Field (ReaxFF) is capable of predicting mechanical properties involving strong deformation, bond breaking and bond formation in the classical molecular dynamics framework. This has been achieved by adding to the potential energy function a bond-order term that varies continuously with distance. The use of an empirical bond order potential, such as ReaxFF, enables the simulation of failure in molecular systems that are several orders of magnitude larger than would be possible in QM techniques. In this work, the fracture behavior of an amorphous carbon (AC) matrix reinforced with CNTs was modeled using molecular dynamics with the ReaxFF reactive forcefield. Care was taken to select the appropriate simulation parameters, which can be different from those required when using traditional fixed-bond force fields. The effect of CNT arrangement was investigated with three systems: a single-wall nanotube (SWNT) array, a multi-wall nanotube (MWNT) array, and a SWNT bundle system. For each arrangement, covalent bonds are added between the CNTs and AC, with crosslink fractions ranging from 0-25% of the interfacial CNT atoms. The SWNT and MWNT array systems represent ideal cases with evenly spaced CNTs; the SWNT bundle system represents a more realistic case because, in practice, van der Waals interactions lead to the agglomeration of CNTs into bundles. The simulation results will serve as guidance in setting experimental processing conditions to optimize the mechanical properties of CNT composites.

Jensen, Benjamin D.↗
DOE OSTI2024

Unravelling Disorder in Aperiodic Crystals – Diffuse Scattering and Atomic Resolution Holography

The atomic–scale disorder of aperiodic crystals, and quasicrystals in particular, is inherently difficult to explore by experimental methods due to their complex atomic arrangements. Two advanced characterization techniques, a revived and an emerging one, offer direct experimental access even to such complex atomic structures: Diffuse Scattering and Atomic Resolution Holography. Finally, in this overview, we introduce their specific application to aperiodic crystals and discuss their merits and difficulties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1977

Quantum mechanical theory of a structured atom-diatom collision system - A + BC/1-Sigma/

The problem of a 2-p state atom colliding with a singlet sigma state diatom, which involves multiple potential surfaces, is investigated. Within a diabatic representation for the electronic degrees of freedom (plus spin-orbit interaction), coupled scattering equations are derived in both space-fixed and body-fixed coordinate systems. Coefficients, analogous to Percival-Seaton coefficients, are obtained. Approximations to the exact equations, including angular momenta decoupling approximations, are discussed for both the space-fixed and body-fixed formalisms.

Devries, P. L.↗
DOE OSTI2025

Atomic-scale 3D structural dynamics and functional degradation of Pt alloy nanocatalysts during the oxygen reduction reaction

Pt-based electrocatalysts are the primary choice for fuel cells due to their superior oxygen reduction reaction (ORR) activity. To enhance ORR performance and durability, extensive studies have investigated transition metal alloying, doping, and shape control to optimize the three key governing factors for ORR: geometry, local chemistry, and strain of their surface and subsurface. However, systematic optimization remains incomplete, as it requires an atomic-scale understanding of these factors and their dynamics over potential cycling, as well as their relationship to ORR activity. Here, we implement neural network-assisted atomic electron tomography to measure the 3D atomic structural dynamics and their effects on the functional degradation of PtNi alloy catalysts. Our results reveal that PtNi catalysts undergo shape changes, surface alloying, and strain relaxation during cycling, which can be effectively mitigated by Ga doping. By combining geometry, local chemistry, and strain analysis, we calculated the changes in ORR activity over thousands of cycles and observed that Ga doping leads to higher initial activity and greater stability. These findings offer a pathway to understanding 3D atomic structural dynamics and their relation to ORR activity during cycling, paving the way for the systematic design of durable, high-efficiency nanocatalysts.

Jeong, Chaehwa↗
NASA NTRS2000

Theoretical Calculations of Atomic Data for Spectroscopy

Several different approximations and techniques have been developed for the calculation of atomic structure, ionization, and excitation of atoms and ions. These techniques have been used to compute large amounts of spectroscopic data of various levels of accuracy. This paper presents a review of these theoretical methods to help non-experts in atomic physics to better understand the qualities and limitations of various data sources and assess how reliable are spectral models based on those data.

Bautista, Manuel A.↗
NASA NTRS2019

AladynPi – Adaptive Neural Network Molecular Dynamics Simulation Code with Physically Informed Potential: Computational Materials Mini-Application

This report provides an overview and description of commands used in the Computational Materials mini-application, AladynPi. AladynPi is an extension of a previously released mini-application, Aladyn (https://github.com/nasa/aladyn; Yamakov, V.I., and Glaessgen, E.H., NASA/TM-2018-220104). Aladyn and AladynPi are basic molecular dynamics codes written in FORTRAN 2003, which are designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory method. An input for the ANN is a set of structure coefficients, characterizing the local atomic environment of each atom, for which the atomic energy is obtained in the ANN inference process. In Aladyn, the ANN gives directly the energy of interatomic interactions. In AladynPi, the ANN gives optimized parameters for a predefined empirical function, known as bond-order-potential (BOP). The parameterized BOP function is then used to calculate the energy. AladynPi code is being released to serve as a training testbed for students and professors in academia to explore possible optimization algorithms for parallel computing on multicore central processing unit (CPU) computers or computers utilizing manycore architectures based on graphic processing units (GPUs). The effort is supported by the High Performance Computing incubator (HPCi) project at NASA Langley Research Center.

Yamakov, Vesselin I.↗
DOE OSTI2025

Mapping strain and structural heterogeneities around bubbles in amorphous ionically conductive Bi 2 O 3

While amorphous materials are often approximated to have a statistically homogeneous atomic structure, they frequently exhibit localized structural heterogeneity that challenges simplified models. This study uses 4D scanning transmission electron microscopy to investigate the strain and structural modifications around gas bubbles in amorphous Bi 2 O 3 induced by argon irradiation. We present a method for determining strain fields surrounding bubbles that can be used to measure the internal pressure of the gas. Compressive strain is observed around the cavities, with higher-order crystalline symmetries emerging near the cavity interfaces, suggesting paracrystalline ordering as a result of bubble coarsening. This ordering, along with a compressive strain gradient, indicates that gas bubbles induce significant localized changes in atomic packing. By analyzing strain fields with maximum compressive strains of 3%, we estimate a lower bound on the internal pressure of the bubbles at 2.5 GPa. These findings provide insight into the complex structural behavior of amorphous materials under stress, particularly in systems with gas inclusions, and offer new methods for probing the local atomic structure in disordered materials. Although considering structural heterogeneity in amorphous systems is non-trivial, these features have crucial impacts on material functionalities, such as mechanical strength, ionic conductivity, and electronic mobility.

36 MATERIALS SCIENCE↗
NASA NTRS1965

Ceramic research

X-ray diffraction micrography data on atomic structure of magnesium oxide grain boundaries

X-RAY ANALYSIS↗
DOE OSTI2025

CSGL: chemical synthesis graph learning for molecule representation

Abstract Motivation Molecule representation learning (MRL) translates molecules into a real vector space, serving as input to downstream tasks in biology, chemistry, and computer science. This article introduces a chemical synthesis graph learning (CSGL) framework, which enhances MRL by considering both the atomic structures of molecules and their roles in chemical reactions through a hierarchical graph representation. Specifically, molecules are first modeled based on their molecular graphs, which capture atomic-level structural information. They are then further refined using a chemical synthesis graph, where nodes represent reactant and product molecule sets, and edges encode chemical transformations between reactants and products (e.g. changes in molecular structures). CSGL optimizes molecular embeddings of reactant and product nodes in a fashion that ensures the embeddings conform to a chemical balance constraint. Results Experimental results show that our method CSGL achieves strong performance on a variety of tasks, including product prediction, reaction classification, and molecular property prediction. Availability and implementation https://github.com/li-2023/CSGL.

Biochemistry & Molecular Biology↗
DOE OSTI2024

X-ray and molecular dynamics study of the temperature-dependent structure of molten NaF-Zr⁢F 4

The local atomic structure of NaF-Zr⁢F 4 (53–47 mol%) molten system and its evolution with temperature are examined with x-ray scattering measurements which are then used to validate the quality of ab initio and neural network-based molecular dynamics (NNMD) calculations in the temperature range 515–700°⁢C. The machine-learning enhanced NNMD calculations offer improved efficiency while maintaining accuracy at higher distances compared to ab initio calculations. Looking at the evolution of the pair distribution function with increasing temperature, a fundamental change in the liquid structure within the selected temperature range, accompanied by a slight decrease in overall correlation is revealed. NNMD calculations indicate the coexistence of three different fluorozirconate complexes: [Zr⁢F 6 ] 2– , [Zr⁢F 7 ] 3– , and [Zr⁢F 8 ] 4– , with a shift in the dominant coordination state from the 7-coordinated Zr cation toward a 6-coordinated cation with increasing temperature. The study also highlights the metastability of different local coordination structures, with frequent interconversions between the 6- and 7-coordinate states. Analysis of the Zr-F-Zr angular distribution function reveals the presence of both “edge-sharing” and “corner-sharing” fluorozirconate complexes with specific bond angles and distances in accord with previous studies, while the next-nearest-neighbor cation-cation correlations demonstrate a clear preference for unlike cations as nearest-neighbor pairs, emphasizing nonrandom arrangement. Finally, these findings contribute to a comprehensive understanding of the complex local structure of the molten salt, providing insights into temperature-dependent preferences and correlations within the molten system.

36 MATERIALS SCIENCE↗