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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Data and Code for Atomic Scale Etching of Diamond: Insights from Molecular Dynamics Simulations

This work investigates the effects of argon ions, hydrogen atoms, and hydrogen ions on the diamond (100) surface using classical molecular dynamics simulations. The purpose of this investigation was to asses plasma processing techniques for applications in quantum device manufacturing. The simulations suggest that combining argon ion smoothing with selective, near threshold energy H removal of amorphous C could be an effective strategy for diamond surface engineering, leading to more reliable and sensitive diamond color center devices. Results were found to differ significantly with interatomic potential, and an analysis of these differences was also carried out. Included in this repository are LAMMPS source files, input scripts, and plotting scripts required to reproduce the data. Also included are the output data required to make all the plots included in the associated publication.

Brenner↗
DOE OSTI2026

The General Antiparticle Spectrometer (GAPS) Antarctic Balloon Payload

The General Antiparticle Spectrometer (GAPS) is an Antarctic stratospheric balloon mission designed to provide unmatched sensitivity to low-energy (<0.25 GeV/n) cosmic-ray antiprotons, antideuterons, and antihelium nuclei as signatures of dark matter. The distinctive GAPS particle identification technique relies on measuring the energy loss along the track of an incoming antinucleus as it slows down and is captured into an exotic atom, and then detecting the de-excitation X-rays and the nuclear annihilation products. This measurement is realized using a Tracker composed of more than 1000 custom silicon strip detectors and a plastic scintillator time-of-flight (TOF) system instrumenting more than 40m$^2$. Together, these subsystems provide the velocity and energy resolution, stopping power, particle tracking, and X-ray identification necessary to distinguish rare antinucleus signals from the abundant positive-nucleus backgrounds, all within the constraints of a high-altitude mission. A multi-loop capillary heat pipe system has been developed to maintain the tracker operating temperature with significant mass and power savings over a conventional pump-based system. The first GAPS science payload flew for 25 days during the 2025/26 NASA Antarctic balloon campaign. We detail the design, integration, and commissioning of the payload prior to flight.

Aoyama, Kazutaka [JAXA, Sagamihara]↗
DOE OSTI2026

Dissipation Enables Strongly Detuning-Dependent Interference in Pulsed Dynamical Decoupling

One of the defining features of pulsed dynamical decoupling is its suppression of a driven qubit's sensitivity to static detuning errors between the drive field and qubit resonance. In this paper, we show that dissipation, in the form of excited-state decay, can change this behavior entirely, producing an interference signal with a strong detuning dependence. This signal arises from decay during driven evolution and relies on coherence retained by the qubit after such a decay event. We develop analytical and numerical models that capture the underlying mechanism and observe this same dissipation-induced detuning dependence experimentally in both a free-space strontium atom interferometer and a superconducting transmon qubit system. We also use this dissipation-induced detuning dependence as the basis for a new spectroscopic technique called Dissipative Carr-Purcell Spectroscopy (DCPS) and compare it with a traditional Ramsey sequence. Our results establish a regime of pulsed dynamical decoupling in which dissipation reshapes, rather than merely degrades, coherent control, and we expect these dynamics to be relevant to a wide range of quantum systems.

DeRose, Kenneth [Northwestern U.; Fermilab] (ORCID↗
DOE OSTI2025

Pick-and-Place Transfer of Arbitrary-Metal Electrodes for van der Waals Device Fabrication

Van der Waals electrode integration is a promising strategy to create nearly perfect interfaces between metals and 2D materials, with advantages such as eliminating Fermi-level pinning and reducing contact resistance. However, the lack of a simple, generalizable pick-and-place transfer technology has greatly hampered the wide use of this technique. Here, we demonstrate the pick-and-place transfer of prefabricated electrodes from reusable polished hydrogenated diamond substrates without the use of any sacrificial layers due to the inherent low-energy and dangling-bond-free nature of the hydrogenated diamond surface. The technique enables transfer of arbitrary-metal electrodes and an electrode array, as demonstrated by successful transfer of eight different elemental metals with work functions ranging from 4.22 to 5.65 eV. We also demonstrate the electrode array transfer for large-scale device fabrication. The mechanical transfer of metal electrodes from diamond to van der Waals materials creates atomically smooth interfaces with no interstitial impurities or disorder, as observed with cross-section high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy. As a demonstration of its device application, we use the diamond transfer technique to create metal contacts to monolayer transition metal dichalcogenide semiconductors with high-work-function Pd, low-work-function Ti, and semimetal Bi to create n- and p-type field-effect transistors with low Schottky barrier heights. We also extend this technology to air-sensitive materials (trilayer 1T’ WTe 2 ) and other applications such as ambipolar transistors, Schottky diodes, and optoelectronics. This highly reliable and reproducible technology paves the way for new device architectures and high-performance devices.

2D materials↗
DOE OSTI2020

Helium Bubble Growth and Retention Characteristics in Aging Palladium Tritide

The helium-related characteristics of aged palladium tritide, including tritium loss, the formation of He bubbles from tritium decay-induced He atoms, and He thermal desorption behavior are computed using a continuum model of bubble evolution that incorporates the log-normal bubble spacing distribution deduced from 3 He nuclear magnetic resonance (NMR) measurements. This spacing distribution produces significant differences between mean (expectation) values of the bubble size and pressure and the average (median) values of these aging characteristics obtained by a previous calculation. The new calculations find much of the He is retained in a large quantity of smaller bubbles with higher bubble pressures, improving the overall stability of the bubbles and extending the age of He retention. By contrast, the integrated tritide material characteristics of swelling and tritium pressure are found relatively insensitive to details of the bubble spacing distribution. Inter-bubble fracture is predicted to begin with small, closely-spaced bubbles and progress to include larger bubbles near the onset of rapid He release. The critical concentration for this onset increases almost linearly with material tensile strength and decreases with shear modulus. Release of He from the aging solid is modeled as a growing network of fractured inter-bubble ligaments. For small particle or small grain material, the physical size of the fracture cluster, relative to the material dimensions, becomes important. In contrast with normal aging, inter-bubble fracture occurring during thermal desorption appears to begin with large, widely-spaced bubbles, indicating elevated temperature techniques may be of limited use for evaluating development of the bubble fracture network.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

High-Power Clock Laser Spectrally Tailored for High-Fidelity Quantum State Engineering

Highly frequency-stable lasers are ubiquitous tools for optical-frequency metrology, precision interferometry, and quantum information science. While making a universally applicable laser is unrealistic, spectral noise can be tailored for specific applications. Here we report a high-power 698-nm clock laser with a maximum output of 4W and minimized frequency noise up to a few kHz Fourier frequency, together with long-term instability of 3.5 × 10 −17 at one to thousands of seconds. The laser-frequency noise is precisely characterized with atom-based spectral analysis that employs a pulse sequence designed to suppress sensitivity to intensity noise. This method provides universally applicable tunability of the spectral response and analysis of quantum sensors over a wide frequency range. With the optimized laser system characterized by this technique, we achieve an average single-qubit Clifford gate fidelity of up to 𝐹$^2_1$ = 0.999⁢64⁢(3) when simultaneously driving 3000 optical qubits with a homogeneous Rabi frequency ranging from 10 Hz to 1 kHz. This result represents the highest single optical-qubit-gate fidelity for a large number of atoms.

atomic gases↗
DOE OSTI2020

One-center close-coupling approach to two-center rearrangement collisions

Calculations of ionization and electron-capture cross sections in ion-atom collisions usually require solving the Schrödinger equation governing the collision system by expanding the total scattering wave function in a basis of target- and projectile-centered pseudostates. This approach leads to the two-center close-coupling equations which in some cases may become ill-conditioned due to the non-orthogonality of the underlying combined basis. Here we develop a technique which allows to accurately extract the necessary collision information, including that for the rearrangement channels, from the computationally more convenient one-center close-coupling equations which are built from only target-centered pseudostates. The robustness of the method is demonstrated by considering the proton-hydrogen scattering problem across a wide incident energy range. The developed method is then applied to study proton scattering on multielectron target of lithium. Here, the obtained results for the 2s → 2p excitation and the total electron-capture cross sections are in good agreement with corresponding experimental data. It is concluded that the presented technique could be a simpler alternative when integrated cross sections are required.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Revealing Possible Coherence Limiting Sources in Superconducting Qubit with Advanced Electron Microscopy

Superconducting materials hold great potential for solid-state quantum computing. Their fabrication relies on established semiconductor fabrication techniques, such as thin film deposition and lithography, but the complex processing steps can result in defects at the qubits' interfaces and surfaces that can negatively impact coherence time. To improve superconducting qubit performance, it is essential to understand the structural features, at the atomic scale, that may act as sources of decoherence limiting factor in both the Josephson junction (JJ) and resonators, which are key components of superconducting qubit. This talk will present our recent studies on the microstructures in a 2D-transmon, with an emphasis on the JJ. For this research, a combination of advanced microscopy techniques, including high-resolution (S)TEM imaging, and spectroscopy (EDS and EELS) are used to identify possible coherence-limiting defects or structural features.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Optimization of the generator coordinate method with machine-learning techniques for nuclear spectra and neutrinoless double- β decay: Ridge regression for nuclei with axial deformation

The generator coordinate method (GCM) is an important tool of choice for modeling large-amplitude collective motion in atomic nuclei. The computational complexity of the GCM increases rapidly with the number of collective coordinates. It imposes a strong restriction on the applicability of the method. In this work, we propose a subspace-reduction algorithm that employs optimal statistical ML models as surrogates for exact quantum-number projection calculations for norm and Hamiltonian kernels. The model space of the original GCM is reduced to a subspace relevant for nuclear low energy spectra and the NME of ground state to ground state 0νββ decay based on the orthogonality condition (OC) and the energy-transition-orthogonality procedure (ENTROP), respectively. For simplicity, the polynomial ridge regression (RR) algorithm is used to learn the norm and Hamiltonian kernels of axially deformed configurations. The efficiency and accuracy of this algorithm are illustrated for 76 Ge and 76 Se by comparing results obtained using the optimal RR models to direct GCM calculations. The low-lying energy spectra of 76 Ge and 76 Se, as well as the 0νββ-decay NME between their ground states, are computed. Furthermore, the results show that the performance of the GCM+OC/ENTROP+RR is more robust than that of the GCM+RR alone, and the former can reproduce the results of the original GCM calculation accurately with a significantly reduced computational cost.

59 ≤ A ≤ 89↗
DOE OSTI2020

Quantum Dynamics at Scale: Ultrafast Control of Emergent Functional Materials

Confluence of extreme-scale quantum dynamics simulations (i.e. quantum@scale) and cutting-edge x-ray free-electron laser experiments are revolutionizing materials science. An archetypal example is the exciting concept of using picosecond light pulses to control emergent material properties on demand in atomically-thin layered materials. This paper describes efforts to scale our quantum molecular dynamics engine toward the United States' first exaflop/s computer, under an Aurora Early Science Program project named "Metascalable layered material genome". Key algorithmic and computing techniques incorporated are: (1) globally-scalable and locally-fast solvers within a linear-scaling divide-conquer-recombine algorithmic framework; (2) algebraic `BLASification' of computational kernels; and (3) data alignment and loop restructuring, along with register and cache blocking, for enhanced vectorization and efficient memory access. The resulting weak-scaling parallel efficiency was 0.93 on 131,072 Intel Xeon Phi cores for a 56.6 million atom (or 169 million valence-electron) system, whereas the various code transformations achieved 5-fold speedup. The optimized simulation engine allowed us for the first time to establish a significant effect of substrate on the dynamics of layered material upon electronic excitation.

Algebraic BLASification↗
DOE OSTI2022

Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials: case study of thorium dioxide

Predicting materials properties of nuclear fuel compounds is a challenging task in materials science. Their thermodynamical behaviors around and above the operational temperature are essential for the design of nuclear reactors. However, they are not easy to measure, because the target temperature range is too high to perform various standard experiments safely and accurately. Moreover, theoretical methods such as first-principles calculations also suffer from the computational limitations in calculating thermodynamical properties due to their high calculation-costs and complicated electronic structures stemming from f-orbital occupations of valence electrons in actinide elements. Here, we demonstrate, for the first time, machine-learning molecular-dynamics to theoretically explore high-temperature thermodynamical properties of a nuclear fuel material, thorium dioxide. The target compound satisfies first-principles calculation accuracy because f-electron occupation coincidentally diminishes and the scheme meets sampling sufficiency because it works at the computational cost of classical molecular-dynamics levels. We prepare a set of training data using first-principles molecular dynamics with small number of atoms, which cannot directly evaluate thermodynamical properties but captures essential atomistic dynamics at the high temperature range. Then, we construct a machine-learning molecular-dynamics potential and carry out large-scale molecular-dynamics calculations. Consequently, we successfully access two kinds of thermodynamic phase transitions, namely the melting and the anomalous λ transition induced by large diffusions of oxygen atoms. Furthermore, we quantitatively reproduce various experimental data in the best agreement manner by selecting a density functional scheme known as SCAN. Our results suggest that the present scale-up simulation-scheme using machine-learning techniques opens up a new pathway on theoretical studies of not only nuclear fuel compounds, but also a variety of similar materials that contain both heavy and light elements, like thorium dioxide.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Assessment of thermally driven local structural phase changes in 1⁢𝑇′−MoTe 2

The role of layer disorder is important in establishing the topological phases of MoTe 2 . A rich tapestry of atomic ordering influences the structural phase transitions (SPTs), but there is little understanding of the mechanistic details of the phase transition. An atomistic level study was conducted to investigate the local structure of the 1⁢𝑇′ and 𝑇 𝑑 phases of MoTe 2 by using the pair distribution function (PDF) technique. While the average structure exhibits an SPT and coexistence of phases as a function of temperature, the local structure showed the suppression of SPT. The sample retained its monoclinic structure at all temperatures in short-range order. A sharp PDF peak observed at short distances indicated a strong atom-atom correlation between the Mo and Te atoms within the Mo octahedra. In addition, a large-box modeling of the PDF data indicated a preferential motion of Te atoms towards 𝑐 axis at all temperatures. Structural defects, such as stacking faults, likely result in the coexistence of phases in the average structure and suppress the local SPT of MoTe 2 . These results are stepping stones to understand the long-debated origins of structural, vibrational, and electronic properties of MoTe 2 and similar transition metal dichalcogenides.

2-dimensional systems↗
DOE OSTI2020

Ni coating on 316L stainless steel using cage plasma treatment: Feasibility and swelling studies

A modified cage plasma nitriding technique is used to coat a Ni film onto a 316L substrate as a protective layer for austenitic steels in molten fluoride salts. The coating is achieved by deposition of Ni atoms sputtered from a Ni cage with a 316L substrate floated at the same potential as the cage to reduce plasma sputtering on the substrate. The Ni coating is porosity-free and precipitation-free and forms a γ-(Fe, Ni) phase due to interdiffusion from the substrate. Beneath the interdiffusion layer exists a thick γ-phase layer mainly affected by long-range nitrogen diffusion along the grain boundary. This layer develops grain boundary Cr nitride precipitates. Ion irradiation on the polished cross-section of the plasma-treated sample shows no void swelling in the surface-deposited Ni layer, very limited void formation in N diffusion layer, and significant void swelling in bulk unaffected by nitrogen. The studies demonstrate the feasibility of the technique for Ni coating and show good swelling resistance of the coating layer and N diffusion-affected layer. Mechanisms are discussed in this paper.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The superior hydrothermal stability of Pd/SSZ-39 in low temperature passive NOx adsorption (PNA) and methane combustion

We successfully synthesized uniform SSZ-39 with an average crystal size of about a micron. Pd (0.7 - 3 wt%) was supported on SSZ-39 with Si/Al ratio ~12. The as-synthesized materials were characterized by FTIR, XRD, Helium Ion Microscopy, HAADF-STEM imaging, 27 Al, 29 Si and H solid state NMR spectroscopic techniques. FTIR studies with CO and NO probe molecules reveal that the 0.7 wt% Pd/SSZ-39 material with Si/Al ~12 has the majority of Pd dispersed atomically as isolated Pd(II) and Pd(II)-OH centers, and thus can be used as a low-temperature passive NOx adsorber. Pd(II)-NO, Pd(II)(OH)(NO) and Pd(II)(CO)(NO) complexes form during PNA in this material. We compare this PNA material directly with the Pd/SSZ-13 system (with Si/Al ratio ~12) and show its superior hydrothermal stability. Remarkably, Pd/SSZ-39 with Si/Al ratio ~12 survives hydrothermal aging up to 815 ºC in 10% H 2 O/Air vapor for 16 hours without significant loss in activity. The SSZ-39 crystal structure remains intact during hydrothermal aging up to 1,000 ºC as we elucidate it with XRD and HAADF-STEM imaging/EDS mapping. However, changes to the framework during such harsh hydrothermal treatment significantly change the NOx release profiles during PNA as evidenced by high-field 27 Al NMR on fresh and aged Pd/SSZ-39 samples as well as PNA performance measurements. Besides PNA application, these hydrothermally very stable materials (3 wt% Pd on SSZ-39 with Si/Al ratio ~12) can be used as a robust methane combustion catalyst under industrially relevant conditions (GHSV~600,000hr -1 ). This catalyst shows minimal deactivation after both harsh hydrothermal aging at 750 and 800 ºC, and prolonged time on stream (105 hrs) at 425 °C. In contrast, both 3wt% Pd/alumina and 3wt% SSZ-13 supported samples lose a significant portion of their activity. Our study opens new avenues to prepare the most hydrothermally stable known Pd/zeolite materials with applications for adsorption and catalytic hydrocarbon combustion under industrially relevant conditions.

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

On the integration of molecular dynamics, data science, and experiments for studying solvent effects on catalysis

Computational workflows that combine molecular dynamics (MD) simulations and emerging data-centric (DC) methods can accelerate the screening and analysis of solvent systems experimentally and computationally. Here, MD simulations provide atomic positions and velocities of reactant, solvent, and catalyst materials that can be manipulated into data representations that in turn can be used by DC techniques to conduct predictive modeling, feature extraction, and experimental design. For liquid-phase catalytic applications, emerging DC techniques such as Convolutional and Graph Neural Networks (CNN/GNN), Topological Data Analysis (TDA), and Active Learning (AL) can leverage MD and experimental data to quickly predict solvent effects on reaction outcomes. For instance, in recent studies, 3D solvent environments obtained with MD have been exploited by CNNs to predict experimental reaction rates for homogeneous acid-catalyzed lignocellulosic processes. In this perspective, we discuss basic principles of DC methods and how these can be combined with MD to enable high-throughput screening of solvent selection for diverse catalysis applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Multiparametric AFM Insights into Electron Transport Mechanisms in Biomemristors

Biomemristors have attracted significant attention due to their applications in biodegradable and flexible electronic devices, and their prospective functions in information storage, neural synapses, and neuromorphic computation. Hence, understanding biomaterials' resistive switching (RS) mechanism is essential to design novel biomemristors with enhanced performance. In the last decade, various atomic force microscopy (AFM) modes, such as Kelvin probe force microscopy (KPFM) and conductive atomic force microscopy (cAFM), in situ/operando visualize the electron transport behaviors within biomemristors at the nanoscale. This review provides a comprehensive discussion of multiparametric AFM techniques to characterize biomemristors and inspire new ideas in developing next-generation consumer electronics. We also summarize the progress of revealing the internal mechanism of biomemristors with functional AFM to visualize and understand the switching behavior. Finally, the opportunities and challenges of further utilizing multiparametric AFM to explore the electron transport mechanisms in biomemristors are presented.

Shi, Chenyang↗
DOE OSTI2021

Probing the antiknock effect of anisole through an ignition, speciation and modeling study of its blends with isooctane

In order to unravel the reaction pathways relevant to anisole co-oxidation within a fuel blend, a detailed study of isooctane/anisole blends was performed with the ULille RCM. Ignition delays as well as mole fraction profiles were measured during a two-stage ignition delay using sampling and GC techniques. These results are used to validate a kinetic model developed from ab initio calculations for the most relevant rate constants which included H-atom abstraction reactions from anisole, and reactions on the potential energy surfaces of methoxyphenyl + O 2 and anisyl + O 2 . Pressure dependent rate constants were computed for the methoxyphenyl + O 2 and anisyl + O 2 reactive systems using master equation code analysis. The new kinetic model shows good agreement with the experimental data. Dual brute-force sensitivity analysis was performed, on both first- and second-stages of ignition, allowing the identification of the most important reactions in the prediction of both ignition delays. It was observed that while pure anisole does not show NTC behavior, a 60/40 isooctane/anisole blend displays such behavior, as well as two-stage ignition. This suggests anisole addition may not be as beneficial to knock resistance as expected from its high octane number. The kinetic modeling results demonstrate the importance of H-abstraction reactions both from the methoxy group and from the aryl ring in ortho-position and the addition of the resultant radicals to O2, mostly leading to the formation of polar or non-aromatic products.

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

Nano-layer deposition of metal oxides via a condensed water film

Abstract Nanocoatings on solids can be achieved by various processes, including sol-gel and atomic layer deposition. However, challenges remain for achieving uniform nanocoatings on nanoscale substrates at a large scale. Here, we report a versatile and fundamentally different technique, termed condensed layer deposition, for depositing conformal metal oxide nanocoatings on nanoparticles and nanofibers. This approach involves water in liquid hydrocarbons condensing as a nanoscale water film on the substrate surface, enabled by interfacial tension between polar water and nonpolar liquid hydrocarbons. Chemical precursors are then added, which react with the condensed water film to form a metal oxide nanocoating. We demonstrate this for titania, alumina, and niobia on substrates including carbon nanotubes, iron oxide particles and carbon black. Condensed layer deposition can achieve oxide nanocoatings on a variety of substrates with tunable thickness, in one pass, at room temperature.

36 MATERIALS SCIENCE↗