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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Zn acceptors in β-Ga 2 O 3 crystals

Electron paramagnetic resonance (EPR) is used to identify and characterize neutral zinc acceptors in Zn-doped β-Ga 2 O 3 crystals. Two EPR spectra are observed at low temperatures, one from Zn ions at tetrahedral Ga(1) sites (the $Zn$$^{0}_{Ga 1}$ acceptor) and one from Zn ions at octahedral Ga(2) sites (the $Zn$$^{0}_{Ga 2}$ acceptor). These Zn acceptors are small polarons, with the unpaired spin localized in each case on a threefold coordinated oxygen O(I) ion adjacent to the Zn ion. Resolved hyperfine interactions with neighboring 69 Ga and 71 Ga nuclei allow the EPR spectra from the two acceptors to be easily distinguished: $Zn$$^{0}_{Ga 1}$ acceptors interact equally with two Ga(2) ions and $Zn$$^{0}_{Ga 2}$ acceptors interact unequally with a Ga(1) ion and a Ga(2) ion. The as-grown crystals are compensated, with the Zn ions initially present as singly ionized acceptors ($Zn$$^{-}_{Ga 1}$ and $Zn$$^{-}_{Ga 2}$). Exposing a crystal to 325 nm laser light, while being held at 140 K, primarily produces neutral $Zn$$^{0}_{Ga 2}$ acceptors when photoinduced holes are trapped at $Zn$$^{-}_{Ga 2}$ acceptors. This suggests that there may be significantly more Zn ions at Ga(2) sites than at Ga(1) sites. Warming the crystal briefly to room temperature, after removing the light, destroys the EPR spectrum from the shallower $Zn$$^{0}_{Ga 2}$ acceptors and produces the EPR spectrum from the more stable $Zn$$^{0}_{Ga 1}$ acceptors. Furthermore, the $Zn$$^{0}_{Ga 2}$ acceptors decay in the 240–260 K region with a thermal activation energy near 0.65 eV, similar to $Mg$$^{0}_{Ga 2}$ acceptors, whereas the slightly deeper $Zn$$^{0}_{Ga 1}$ acceptors decay close to room temperature with an approximate thermal activation energy of 0.78 eV.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Sec14 domain protein is required for photoautotrophic growth and chloroplast vesicle formation in Arabidopsis thaliana

In eukaryotic photosynthetic organisms, the conversion of solar into chemical energy occurs in thylakoid membranes in the chloroplast. How thylakoid membranes are formed and maintained is poorly understood. However, previous observations of vesicles adjacent to the stromal side of the inner envelope membrane of the chloroplast suggest a possible role of membrane transport via vesicle trafficking from the inner envelope to the thylakoids. Here we show that the model plant Arabidopsis thaliana has a chloroplast-localized Sec14-like protein (CPSFL1) that is necessary for photoautotrophic growth and vesicle formation at the inner envelope membrane of the chloroplast. The cpsfl1 mutants are seedling lethal, show a defect in thylakoid structure, and lack chloroplast vesicles. Sec14 domain proteins are found only in eukaryotes and have been well characterized in yeast, where they regulate vesicle budding at the trans -Golgi network. Like the yeast Sec14p, CPSFL1 binds phosphatidylinositol phosphates (PIPs) and phosphatidic acid (PA) and acts as a phosphatidylinositol transfer protein in vitro, and expression of Arabidopsis CPSFL1 can complement the yeast sec14 mutation. CPSFL1 can transfer PIP into PA-rich membrane bilayers in vitro, suggesting that CPSFL1 potentially facilitates vesicle formation by trafficking PA and/or PIP, known regulators of membrane trafficking between organellar subcompartments. These results underscore the role of vesicles in thylakoid biogenesis and/or maintenance. CPSFL1 appears to be an example of a eukaryotic cytosolic protein that has been coopted for a function in the chloroplast, an organelle derived from endosymbiosis of a cyanobacterium.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Neuromorphic learning with Mott insulator NiO

Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence found in nature in the solid state can serve as inspiration for algorithmic simulations in artificial neural networks and potential use in neuromorphic computing. In this work, we demonstrate nonassociative learning with a prototypical Mott insulator, nickel oxide (NiO), under a variety of external stimuli at and above room temperature. Similar to biological species such as Aplysia, habituation and sensitization of NiO possess time-dependent plasticity relying on both strength and time interval between stimuli. A combination of experimental approaches and first-principles calculations reveals that such learning behavior of NiO results from dynamic modulation of its defect and electronic structure. An artificial neural network model inspired by such nonassociative learning is simulated to show advantages for an unsupervised clustering task in accuracy and reducing catastrophic interference, which could help mitigate the stability–plasticity dilemma. Mott insulators can therefore serve as building blocks to examine learning behavior noted in biology and inspire new learning algorithms for artificial intelligence.

42 ENGINEERING↗
DOE OSTI2023

Focused Interest Groups Propel Innovation in the Emerging Data-Driven Hardware Ecosystem

Over the past several decades, the science of electron microscopy (EM) has risen to become one of the cornerstone approaches to understanding material structure, chemistry, and defects at exceptional spatial resolution. This rise can be attributed to the hard work of researchers and companies who have pushed the bounds of instrumentation and analysis, but it is also the result of advocacy by members of professional societies. Furthermore, such advocacy is exemplified by the Aberration Corrected EM (ACEM) focused interest group (FIG) of the Microscopy Society of America (MSA), which has played an important role in facilitating new hardware developments, promoting the exchange of ideas to catalyze discovery, and building the next generation of leaders in electron microscopy. From the early 2000s to the present, aberration correction has moved from proof-of-concept instrumentation to an established technique, providing unprecedented improvements in spatial and chemical resolution for breakthroughs in chemistry, physics, and materials science.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Determination of rutile transition metal oxide (110) surface terminations by scanning tunneling microscopy contrast reversal

The surfaces of rutile transition-metal oxides (TMO 2 ) are widely investigated for catalysis, photoelectrochemical solar cells, memristors, and supercapacitors, but their structures have remained controversial. Here we employ density functional theory to predict that a universal behavior of metallic TMO 2 surfaces, i.e., the stoichiometric TMO 2 surfaces, exhibit a contrast reversal in simulated scanning tunneling microscopy (STM) images at different scanning biases. The predictions are verified by experimental STM imaging of RuO 2 (110) surfaces and this feature is shown to enable accurate determinations of the TMO 2 (110) surface structures under various conditions. This research provides different insights into the electronic properties of TMO 2 (110) surfaces and offers an effective method to directly map the surface structure and point defects using bias-dependent STM.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Absence of long-range magnetic order in Fe 1–δ Te 2 (δ ≈ 0.1) crystals

Transition metal dichalcogenides attract considerable attention due to variety of interesting properties, including long range magnetism in nanocrystals. Here we have investigated magnetic, thermal and electrical properties of FeTe 2 single crystal with iron vacancy defects. Magnetic measurements shows paramagnetic state and the absence of magnetic order with small anisotropy in magnetic susceptibility. Fe 3d orbitals are well hybridized, contributing to bad metal electrical resistivity. Observed thermal conductivity values below room temperature are rather low and comparable to high performance thermoelectric materials. Furthermore, our results indicate that FeTe 2 can form in highly defective marcasite crystal structure which can be exploited in future materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Comment on “Anisotropic Scattering Caused by Apical Oxygen Vacancies in Thin Films of Overdoped High-Temperature Cuprate Superconductors”

The comment is on the article published in Vol. 128, Iss. 13 — 1 April 2022, https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.128.137001. In Ref. 1, Wang et al. address an important problem in the overdoped cuprates, taking the first steps toward understanding the structure of real defects in these materials, in this case the apical oxygen vacancy, VO, that sits immediately above the planar Cu. However, the approach taken has some issues, which we outline in this Comment

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Controlling colloidal crystals via morphing energy landscapes and reinforcement learning

We report a feedback control method to remove grain boundaries and produce circular shaped colloidal crystals using morphing energy landscapes and reinforcement learning–based policies. We demonstrate this approach in optical microscopy and computer simulation experiments for colloidal particles in ac electric fields. First, we discover how tunable energy landscape shapes and orientations enhance grain boundary motion and crystal morphology relaxation. Next, reinforcement learning is used to develop an optimized control policy to actuate morphing energy landscapes to produce defect-free crystals orders of magnitude faster than natural relaxation times. Morphing energy landscapes mechanistically enable rapid crystal repair via anisotropic stresses to control defect and shape relaxation without melting. This method is scalable for up to at least N = 10 3 particles with mean process times scaling as N 0.5 . Further scalability is possible by controlling parallel local energy landscapes (e.g., periodic landscapes) to generate large-scale global defect-free hierarchical structures.

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

Anomalous transport in high-mobility superconducting SrTiO 3 thin films

The study of subtle effects on transport in semiconductors requires high-quality epitaxial structures with low defect density. Using hybrid molecular beam epitaxy (MBE), SrTiO 3 films with a low-temperature mobility exceeding 42,000 cm 2 V -1 s -1 at a low carrier density of 3 × 10 17 cm -3 were achieved. A sudden and sharp decrease in residual resistivity accompanied by an enhancement in the superconducting transition temperature were observed across the second Lifshitz transition where the third band becomes occupied, revealing dominant intraband scattering. These films further revealed an anomalous behavior in the Hall carrier density as a consequence of the antiferrodistortive (AFD) transition and the temperature dependence of the Hall scattering factor. Using hybrid MBE growth, phenomenological modeling, temperature-dependent transport measurements, and scanning superconducting quantum interference device imaging, we provide critical insights into the important role of inter- versus intraband scattering and of AFD domain walls on normal-state and superconducting properties of SrTiO 3 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Effect of Annealing on Structural, Textural, Thermal, Magnetic, and Luminescence Properties of Calcium Fluoride Nanoparticles

Mesoporous nanocrystalline CaF{sub 2} powder was produced by pulsed electron beam evaporation (PEBE) in vacuum. The specific surface area (SSA) of CaF{sub 2} nanopowder (NP) reached 88.7 m{sup 2}/g. The effect of in-air thermal annealing in the temperature range of 200–900°C on the particle size, morphology, textural, thermal, magnetic, and luminescence properties of NPs is studied. A strong deviation from stoichiometry is observed in produced nanoparticles and a significant increase in the SSA after annealing at 200°C. The obtained CaF{sub 2} NP shows ferromagnetic (FM) behavior. The FM response appearance can be explained by the formation of structural and radiation defects. An analysis of pulsed cathodoluminescence (PCL) and magnetization curves of CaF{sub 2} NPs allows conclusions about their interrelation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Distinctive molecular configuration of nanostructured silica deposited at a glancing angle

Glancing-angle deposition (GLAD) produces nanostructured silica, showcasing form birefringence, an attractive alternative to traditionally used crystalline materials for polarization control. This work aims to enhance the understanding of its internal structure and associated defects in its native form and after laser processing. Our observations show, for the first time, that the GLAD silica exhibits a unique Raman signature that converges to a typical silica spectrum following laser melting. Defects were also investigated with fluorescence spectroscopy. The new insight provided by this work informs our understanding of this birefringent material and drives optimization of its performance in GLAD-based polarization control devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-dimensional and high-resolution x-ray tomography for energy materials science

At the forefront of developments in synchrotron x-ray microscopy, we report nanoscale-resolution high-dimensional spectrotomography under controlled sample environments has been demonstrated. Such cutting-edge experimental capability has been broadly applied to scientific studies in the field of energy materials science, where the dynamically evolving structural and chemical defects play a vital role in the functionality. In this article, we review novel developments of this technique from both experimental and data/information mining perspectives. Using studies on lithium-ion battery electrode materials as examples, we highlight the rich information in the high-dimensional and high-resolution x-ray tomographic data, which can be used to interpret the complicated thermal-electro-chemo-mechanical interplay that occurs under the operating conditions and collectively determines battery performance. We also discuss the frontier challenges in this field and our perspectives of the future directions in the context of projected major developments in the landscape of largescale x-ray facilities across the globe.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Radiation Response of Low Dimensional Carbon Systems

The project is aimed at understanding the fundamentals of radiation response of low dimensional carbon systems and irradiation-induced mechanical property changes, with a focus on the unique phenomena caused by their geometry, boundary, and quantum size effects. In comparison with their bulk counterparts (graphite), radiation responses of low-dimensional carbon systems are substantially different. The differences exist at almost every stage of defect development, namely, displacement creation, damage cascade, thermal spike formation defect recombination, defect clustering, and structural reconstruction. Many traditional concepts in ion-solid interaction theory do not apply at the nanoscale or require substantial modification. Through this project, we systematically studied various aspects of radiation damage development in graphene, carbon nanotubes (CNTs), and graphite.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Machine Learning Vacancy Formation Energy in Nickel-Based Superalloys

Thermal vacancies play a critical role in high-temperature Ni-based superalloys and influence various properties such as creep resistance, oxidation, etc. This study systematically investigates the impact of commonly used transition metals (Cr, Co, Fe), refractory metals (Nb, Ta, Mo, W) and other elements (Al, Cu, Ti, Mn) on the thermodynamic stability of 36 binary, 20 ternary, 11 quaternary, 9 quinary, and 3 senary FCC Ni-based alloys covering various elemental combinations. Density functional theory-based studies on Ni-X binary alloys show that higher concentrations of Cr, Nb, Ta, Al, and Ti introduce significant lattice distortions and broaden the distribution of vacancy formation energies (standard deviation up to 0.15 eV). These elements partially donate electrons, reducing their self-consistent chemical potentials relative to single-element reference values and lowering vacancy formation energies, while Co, Fe, Mo, and W show lower charge localization. These trends extend from 3-6 element alloys, where Cr, Nb, and Ta-rich compositions have low-energy states (~0.5 eV) that increase vacancy concentrations. Finally, graph neural network models are developed to screen over 5000 virtual alloys. Eleven leading compositions are identified with mean vacancy formation energy higher than 1.75 eV and vacancy concentration ~2 orders of magnitude lower than pure Ni at 1000 K. These results provide valuable guidelines to achieve controlled defect engineering in structural alloys.

DFT↗
DOE OSTI2023

Revealing the Latent Atomic World Through Data-Driven Microscopy

Many emerging technologies depend on the precise design of materials structure, chemistry, and defects. As devices shrink, manufacturing tolerances tighten, and performance envelopes improve, we must increasingly measure and manipulate materials at or near the single atom level. Here we describe how transmission electron microscopy (TEM) underpins our ability to see and direct the latent atomic world. We review a selection of our recent high-resolution TEM studies of the synthesis of oxide-based nanomaterials and their evolution in extreme environments. We then discuss powerful new artificial intelligence (AI) and machine learning (ML) approaches we have developed for rich, reproducible, and scalable experimentation. Furthermore, we conclude by discussing future developments that will enable new materials for breakthrough technologies.

97 MATHEMATICS AND COMPUTING↗