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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Epitaxy of Beta-Ga2O3 on Highly-Offcut (Greater than 10 Degrees) Substrates

Beta-Ga2O3 has emerged as a leading candidate for next-generation power electronics, radio frequency (RF) switches, and extreme environment electronics due to a wide band gap (4.6 - 4.9 eV), high dopability (approximately 40 meV activation energy for an isolated silicon donor), and melt growth characteristics resulting in commercially available 4-inch substrates and commercial demonstrations of 6-inch substrates by multiple techniques. The (100) surface of Ga2O3 is highly desirable from a device and epitaxy standpoint - bulk growth of (100) material is more scalable than (010), the surface is nearly lattice-matched to p-type partner NiO, and Al2O3 incorporates at higher concentrations without phase separation. However, the epitaxial growth rate on (100) surfaces is less than 10% of other faces due to weak bonding and favorable desorption. Recent demonstrations have shown growth rate improvements from 0.4 nm/min to 1.5 nm/min by growing on (100) wafers that are offcut 6 degrees in the -c direction.1 These films show step-flow growth from (-201) step-edges and high electron mobility. Despite these exciting results, offcuts greater than 6 degrees have not been explored due to the waste associated with grinding and polishing large offcuts. In this talk we will discuss the molecular beam epitaxy (MBE) growth and properties of Beta-Ga2O3 grown on (100) substrates offcut in the -c direction up to 13.4 degrees. These large offcuts are enabled by edge-fed film-defined growth (EFG) where the offcut is grown into the surface by pulling the crystal through the EFG die with the seed crystal rotated by the desired offcut angle. We will demonstrate that 13.4 degrees offcut substrates still exhibit a terraced (100) surface, and that a >10x increase (4.8 nm/min) in growth rate is achieved. As previously reported on lower offcuts, we observe 100% reversal of substrate twin domains around the (001) direction at the substrate-epilayer interface. We will discuss electrical properties including record-low (by MBE) unintentional doping densities of < 5E15 cm-3.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Fast Growth of Ga2O3 on Highly Offcut (100)-Oriented Substrates

Beta-Ga2O3 has emerged as a leading candidate for next-generation power electronics, radio frequency (RF) switches, and extreme environment electronics due to a wide band gap (4.6 - 4.9 eV), high dopability (approximately 40 meV activation energy for an isolated silicon donor), and melt growth characteristics resulting in commercially available 4-inch substrates and commercial demonstrations of 6-inch substrates by multiple techniques. The (100) surface of Ga2O3 is highly desirable from a device and epitaxy standpoint - bulk growth of (100) material is more scalable than (010), the surface is nearly lattice-matched to p-type partner NiO, and Al2O3 incorporates at higher concentrations without phase separation. More importantly, the impact ionization coefficients along the [100] direction are low, leading to the highest possible critical fields. This is advantageous compared to the current state of the art, (001), due to reduced surface defects and increased possible breakdown voltage. However, the epitaxial growth rate on (100) surfaces is less than 10% of other faces due to weak bonding and favorable desorption, and on-axis (100) growth easily forms twin domains. Recent demonstrations have shown growth rate improvements from 0.4 nm/min to 1.5 nm/min by growing on (100) wafers that are offcut 6 degrees in the -c direction. These films show step-flow growth from (20-1) step-edges and high electron mobility due to suppressed twins. Despite these exciting results, offcuts greater than 6 degrees have not been explored due to the waste associated with grinding and polishing large offcuts. In this talk we will discuss the molecular beam epitaxy (MBE) growth and properties of Beta-Ga2O3 grown on (100) substrates offcut in the -c direction up to 13.4 degrees. These large offcuts are enabled by edge-fed film-defined growth (EFG) where the offcut is grown into the surface by pulling the crystal through the EFG die with the seed crystal rotated by the desired offcut angle. We will demonstrate that 13.4 degrees offcut substrates still exhibit a terraced (100) surface, and that a >10x increase (>5 nm/min) in growth rate is achieved. As previously reported on lower offcuts, we observe reversal of substrate twin domains around the (001) direction at the substrate-epilayer interface. We will discuss electrical properties including record-low (by MBE) unintentional doping densities of < 5E15 cm-3 and critical breakdown field in Schottky barrier diodes comparable with state-of-the-art (001) Ga2O3 without edge termination.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Proton radiation effects in indium oxide using cascade molecular dynamics simulations

Metal oxide (MO) semiconductors, characterized by their wide band gaps and notable charge transport properties, are promising candidates for electronic applications in extreme environments, including near-Earth space. However, atomistic simulations of radiation–matter interactions in MOs remain challenging due to the limitations of existing interatomic potentials, which often fail to capture both the short-range repulsive forces essential for radiation damage modeling and the long-range electrostatic effects governing defect evolution. In this work, we develop a customized interatomic potential tailored for radiation damage simulations in indium oxide (In 2 O 3 ) as a model system, a representative MO material. Our potential integrates the Ziegler-Biersack-Littmark potential to accurately describe short-range interactions with Buckingham and Coulombic potentials to account for long-range forces. We perform molecular dynamics simulations of low-energy proton irradiation using this custom potential. We employ the primary knock-on atom (PKA) cascade method to study atomic displacements and primary defect formation. Simulations were conducted for 1 keV proton irradiation in four randomly chosen directions, and PKA-driven defect analyses at 5, 10, and 15 keV to examine the effects of direction and energy level on damage generation. Our results provide insight into the impact of irradiation direction and energy level on the cascade evolution and defect formation mechanisms.

Atomistic simulations↗
DOE OSTI2025

Distinctive features of structural evolution and thermodynamic response in wide-bandgap semiconductors driven by intense electronic excitation

Radiation-tolerant material selection requires balancing lattice rigidity, defect dynamics, and electronic stability, as shown by covalent SiC outperforming ionic Ga 2 O 3 and GaN under extreme environments. Responding to intense electronic excitation, irradiation-driven phase segregation (β → δ/κ in Ga 2 O 3 ) and core–shell track (disordered structure in GaN), accompanied by elemental redistribution, contrastingly, exceptional radiation tolerance manifested by comparatively minimal lattice distortion (0.17 % strain variation) was demonstrated in SiC. These differential responses are primarily attributed to two fundamental mechanisms: (i) thermodynamic driving forces governing defect migration and phase separation, and (ii) the synergistic effects of robust covalent bonding composition coupled with efficient defect recombination processes. Here, the stronger electron–phonon (e-ph) coupling in Ga 2 O 3 (4.34 × 1018 W m −3 K −1 ) and GaN (3.55 × 10 18 W m −3 K −1 ) enhances lattice energy deposition, triggering thermal spikes (ΔT ≫ T m ) and structural transition behaviors, whereas weaker e-ph coupling in SiC (3.69 × 10 18 W m −3 K −1 ), relatively high thermodynamic parameters and efficient energy dissipation suppress thermal spikes to maintaining lattice integrity. The photoresponse degradation driven by enhanced radiative recombination is dominant in N-doped SiC, while V-doped systems achieve defect-mediated photoconduction optimization characterized by abrupt current transitions, matching fluorescence yield evolutions, and directly connecting defect engineering to optoelectronic performance.

Intense electronic excitation↗
DOE OSTI2024

Advanced Characterization Capabilities for Nuclear Materials via Nuclear Science User Facilities (NSUF)

Advanced post-irradiation examination (PIE) techniques are required to design new or improved nuclear materials, characterize, and understand in-core behavior of fuel and materials, and support the qualification of new reactor materials. The Nuclear Science User Facilities (NSUF) is the U.S. Department of Energy Office of Nuclear Energy's only designated nuclear science user facility. NSUF provides researchers access to PIE capabilities at Idaho National Laboratory and at a diverse mix of university, national laboratory and industrial partner institutions. The PIE capabilities include novel destructive and non-destructive techniques for radiation damage characterization, such as advanced diffraction techniques (X-ray, electron, or neutron) coupled to extreme environments; in-situ observation of microstructural evolution under irradiation; in-situ irradiation to monitor corrosive attack in coolant environments; in-situ irradiation and mechanical testing; and test methods for synergistic effects of superimposed extreme environments (temperature, irradiation, stress, corrosion) on materials behaviors. This talk will provide an overview of NSUF PIE capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Characterization and novel application of power over fiber for electronics in a harsh environment

Power-over-Fiber (PoF) technology has been used extensively in settings where high voltages require isolation from ground. In a novel application of PoF, power is provided to photon detector modules located on a surface at ∼ 300 kV with respect to ground in the planned DUNE experiment. In cryogenic environments, PoF offers a reliable means of power transmission, leveraging optical fibers to transfer optical power. PoF technology excels in maintaining low noise levels when delivering power to sensitive electronic systems operating in extreme temperatures and high voltage environments. This paper presents the R&D effort of PoF in extreme conditions and underscores its capacity to revolutionize power delivery and management in critical applications, offering a dependable solution with low noise, optimal efficiency (∼ 51%), and superior isolation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Spatiotemporal Learning in Power Modules: Wavelet-Enhanced Forecasting of Thermomechanical Degradation

Detecting internal defects in power electronics packages is critical for their performance and reliability, especially under extreme operating conditions, as these defects can lead to catastrophic failure if not properly addressed. Confocal scanning acoustic microscopy (C-SAM) plays a key role in the nondestructive evaluation of bond layer degradation within a power electronics package by detecting defects such as delamination, voids, and cracks. However, accurately quantifying and predicting these defects from C-SAM images remains a significant challenge due to the low noise-to-signal ratio, which typically arises from both imaging process and bond patterns itself. In this paper, we explore machine learning strategies for processing C-SAM images and providing predictive models of defect growth. We use C-SAM images of sintered copper and sintered silver samples, which are obtained under accelerated thermal experiments, as the representative dataset for our study. We investigate the effect of Fourier transforms and wavelet transforms on these datasets to remove high-frequency noise and address noise across multiple scales with histogram equalization to enhance the contrast and improve the visibility of defects. As a result, defect boundaries can be clearly distinguished, enabling more accurate tracking of their growth over time. We then employ different time-series forecasting algorithms on the denoised images to formulate an image-based lifetime prediction model. Statistical models and deep-learning techniques are trained on images obtained in the early stages of thermal shock, and defect growth in the later stages is predicted. Our work serves as a preliminary attempt to improve the accuracy of lifetime prediction models of power electronics packages, which is critical under extreme operating environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Power over fiber development for HEP detectors

Power-over-Fiber (PoF) technology has been used extensively in settings where high voltages require isolation from ground and electromagnetic isolation is critical. In cryogenic environments, PoF offers a reliable power transmission technology, leveraging optical fibers to transfer power with minimal system degradation. PoF technology excels in maintaining low noise levels and isolation when delivering power to sensitive electronic systems operating in extreme temperature ranges and high voltage environments. Here, in a novel application of PoF for a HEP detector, power is provided to photon detector modules located on a surface at ~300 kV with respect to ground in the planned DUNE experiment. This summary paper of the PoF talk at the 16th PISA Meeting on Advanced Detectors highlights the R&D effort of PoF in extreme conditions and underscores its capacity to revolutionize power delivery and management in critical applications offering a dependable solution with low noise, optimal efficiency, and superior isolation. The DUNE (Abi et al., 2020) experiment will soon deploy large liquid argon (LAr) time projection chambers (TPC) to detect neutrino interactions and other particle physics phenomena. In addition to the particle tracking provided by the TPC, photon detectors, powered by a first ever PoF system, in the cryostat will leverage the high scintillation light yield of LAr to provide crucial timing and additional calorimetric information.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Electronic Configurational Transformation of Network Modifiers in Aluminate Glass above Megabar Pressures

Electronic responses of glasses under extreme pressures differ from those of crystalline analogs. Their distinct electronic environments are found in network formers with well-defined, covalent-bonded coordination environments (e.g., [4] Si and [4] Al) and in network modifiers with more disordered, ionic-bonded configurations (e.g., [5,6,7] Ca). Deciphering the evolution of the bonding environment of network modifier cations upon compression provides atomic insights into the pressure-driven hardening and transport properties of glasses. Despite the importance, in contrast to extensive efforts to uncover how network formers behave under pressure, considerable structural disorder around network modifiers makes it challenging to probe their electronic bonding environments under compression. Our understanding of the evolution of network modifiers above megabars is currently absent. Here, we report a discovery of highly densified electronic configurations of network modifier Ca in aluminate glass under extreme compression via the first inelastic X-ray scattering at the Ca L-edge up to 140 GPa. As evidenced by the prominent pressure-driven increases in electronic dispersion and delocalization, densified calcium environments are characterized by a decreased average Ca–O distance, the formation of highly coordinated calcium, a broader distribution of topological variables, and a greater distortion of Ca polyhedra above megabars. The spectral features for the Ca environments reveal significant electronic and bonding modifications, including pressure-driven increases in the ligand field interaction, the covalence characteristic of the Ca–O bond, and the electron–hole Coulomb interaction. These densification paths identify the electronic adaptation of network modifiers above megabars, shedding light on the origins of enhanced electron transport and the electron-storing capacity of glasses under pressure.

amorphous materials↗
DOE OSTI2024

Nonvolatile electrochemical memory at 600°C enabled by composition phase separation

Silicon-based microelectronics are limited to ~150°C and therefore not suitable for the extremely high temperatures in aerospace, energy, and space applications. While wide-band-gap semiconductors can provide high-temperature logic, nonvolatile memory devices at high temperatures have been challenging. In this work, we develop a nonvolatile electrochemical memory cell that stores and retains analog and digital information at temperatures as high as 600°C. Through correlative scanning transmission electron microscopy, we show that this high-temperature information retention is a result of composition phase separation between the oxidized and reduced forms of amorphous tantalum oxide. This result demonstrates a memory concept that is resilient at extreme temperatures and reveals phase separation as the principal mechanism that enables nonvolatile information storage in these electrochemical memory cells.

42 ENGINEERING↗
DOE OSTI2025

Radiation‐Resistant Aluminum Alloy for Space Missions in the Extreme Environment of the Solar System

Future human exploration of the solar system demands advanced materials capable of withstanding extreme environments, particularly exposure to solar energetic particle radiation. Current material selection criteria for space applications prioritize a high strength-to-weight ratio, high corrosion resistance and manufacturability, favoring age-hardenable Al-based alloys. However, conventional precipitation-hardened Al alloys suffer from irradiation-assisted dissolution of strengthening phases at doses as low as 0.2 displacements-per-atom (dpa), undermining their performance. Furthermore, these alloys develop radiation-induced defects, such as dislocation loops and voids, even at low doses. This study presents a novel ultrafine-grained (UFG) Al-based alloy, designed using the crossover alloying concept and strengthened by T-phase precipitates, featuring a chemically-complex structure with 162 atoms in its unit cell composed of Mg 32 (Zn,Al) 49 . It is showed that T-phase precipitates have exceptional radiation tolerance up to 24 dpa. Owing to the nanoscale UFG structure, dislocation loops are suppressed, and voids are only observed beyond 75 dpa. Microtensile tests up to 20 dpa confirm the preservation of mechanical performance under irradiation. The results underline the potential of this alloy as a radiation-resistant, lightweight material for future space applications. Three key strategies enable this performance: (i) stabilization of a UFG microstructure, (ii) T-phase precipitation featuring a highly negative Gibbs free energy and chemically-complex giant unit cell, and (iii) precise process control to prevent grain growth during heat treatment and irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A method to observe field-region oxide charge and inter-electrode isolation from CV-characteristics of n-on-p devices

Abstract N-on-psilicon sensors will be utilized in the Compact Muon Solenoid (CMS) detector's tracker and High Granularity Calorimeter (HGCAL) in the High Luminosity upgrade of the Large Hadron Collider (HL-LHC). Among their several advantages in terms of radiation hardness over the traditionalp-on-nsensors in the extreme radiation environment of the HL-LHC are electron collection instead of holes and overlapping maxima of weighting and electric fields at the charge-collecting electrodes. The disadvantage of the multi-channel SiO 2 -passivatedn-on-psensors is the generation of an inversion layer under the Si/SiO 2 -interface by a positive interface-oxide-charge (N ox ) that at high densities can compromise the position resolution by creating a conduction channel between the electrodes. This issue is typically addressed by including additional isolnts (p-stp,p-spray) between n + -electrodes. Focusing on the guard-ring regions ofn-on-psensors where no isolation implants are applied between the electrodes, a capacitance-voltage (CV) characterization study of both 6-inch wafer test diodes and 8-inch HGCAL prototype and pre-series sensors showed a distinct threshold voltage (V th,iso ) in theCV-characteristics of a biased n + -electrode when its enclosing guard-ring was left floating. When reproduced by simulations, the measuredV th,iso was found to contain information on the field-regionN ox and indicate the threshold where the two electrodes become electrically isolated by the influence of the reverse bias voltage. Together with previous studies on the inter-electrode isolation of irradiatedn-on-psensors, the results indicate that position sensitiven-on-psensors without isolation implants may be feasible in future HEP experiments.

Instruments & Instrumentation↗
DOE OSTI2025

Bulk synthesis of radiation resistant W – Ti – Cr – V compositionally complex alloys

Refractory compositionally complex alloys are candidate material systems for next generation advanced nuclear reactors. This work showcases the first successful bulk synthesis of low activation W–Ti based refractory compositionally complex alloys using arc melting and provides insights on using additive manufacturing for these compositions using directed energy deposition. Both techniques produce equiaxed grains composed of a tungsten matrix with Ti–V–Cr dendritic boundaries. The arc melted specimen possesses a multi-modal grain size distribution, while the directed energy deposition specimen possesses a more gaussian distribution of grain size. Both arc melted and directed energy deposition specimens demonstrate high thermal stability up to 900 °C, as well as promising radiation resistance with low loop formation and the presence of homogeneously distributed helium cavities maintaining small diameters at ≥10 dpa under simultaneous light (helium) and heavy (krypton) ion irradiation at 900 °C.

Arc melting (AM)↗
DOE OSTI2025

Applying deep learning methods to develop new models of molecular charge transfer, nonadiabatic dynamics, and nonlinear spectroscopy in the condensed phase

Photon- and field-induced charge transfer has central importance in the generation and storage of electricity, the novel properties of materials, photo-induced catalysis, and electro-optic activity (e.g., photovoltaic cells, fuel cells, and organic chromophores for use in optical fibers and light-emission diodes). These non-equilibrium electronic and chemical transformations are probed by ultrafast, nonlinear spectroscopies. Accurate simulations play a crucial role in our ability to understand, optimize, and control these transformations. This project applies modern deep learning and machine learning (ML) methods to dramatically improve models of electronic dynamics, electronic-nuclear dynamics, and spectroscopic measurements for improved simulations of chemistry in complex environments, far from equilibrium phenomena, and processes in extreme environments, such as materials exposed to strong or resonant fields. This project develops accurate neural net models that go beyond predictive capability to also provide new insight into the fundamental physics underlying electron and nuclear dynamics. To achieve its objectives, this project explores and develops customized versions of high-capacity deep learning algorithms/models. These techniques are developed with an emphasis on fundamental chemical insight, not just predictive accuracy, to assist the development of the next generation of quantum simulation methods.

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

Final Technical Report for DoE award DE‐SC0023367 “Energetic Electron Transport in Magnetized Plasma with Magnetic Islands”

This project investigated how plasmas interact with energetic particles and solid materials under extreme conditions relevant to fusion energy, space plasmas, and planetary environments. Using experiments on the DIII-D National Fusion Facility, the research first examined how high-energy electrons move, become trapped, and are released in plasmas containing magnetic islands—structures commonly found in fusion reactors and Earth’s magnetosphere—providing new insight into particle transport and acceleration processes. The project also explored plasma-driven chemical reactions that can occur during meteoroid entry into planetary atmospheres, demonstrating that simple molecules such as ammonia can be produced and survive in high-temperature plasma conditions. Together, these results improve understanding of plasma behavior across laboratory, space, and planetary systems while informing fusion plasma control and plasma–material interaction studies. The project additionally contributed to workforce development by training graduate students, undergraduates, and early-career researchers and by disseminating results through peer-reviewed publications and international scientific conferences.

Orlov, Dmitri Mikhailovich [UC San Diego] (ORCID:0↗
DOE OSTI2025

DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys

Designing ductile materials for extreme environments such as fusion reactors requires a deep understanding of the complex interplay between electronic structure, mechanical stability, and wide compositional space. Here, in this work, we introduce DuctGPT, a physics-informed, GPT-powered machine learning platform that enables rapid and accurate prediction of ductility across a wide range of refractory multi-principal element alloys (MPEAs). Trained on both experimental and high-fidelity computational data, DuctGPT integrates descriptors such as density of states at the Fermi level, elastic constants, and valence electron concentration to capture the fundamental mechanisms governing ductile versus brittle behavior. Using this framework, we screen over 1000 compositions in of body-centered cubic (BCC) MPEAs, including two new alloy classes, i.e., NbTa-rich (NbTa $>$ 50 at.%) NbTa-Ti-V and W-rich ($>$ 50 at.%) W-Ti-V MPEAs, to rapidly identify promising alloy compositions with enhanced ductility. Validation against experimental data confirms the model's ability to predict ductility with high fidelity and low uncertainty. By leveraging conversational AI and robust physical modeling, DuctGPT provides a blueprint for the next generation of alloy design assistants, enabling human-AI collaboration in the accelerated discovery of ductile, high-performance materials for fusion, aerospace, and advanced manufacturing.

AI/ML↗
DOE OSTI2024

4D-STEM Mapping of Nanocrystal Reaction Dynamics and Heterogeneity in a Graphene Liquid Cell

Chemical reaction kinetics at the nanoscale are intertwined with heterogeneity in structure and composition. However, mapping such heterogeneity in a liquid environment is extremely challenging. Here, in this work, we integrate graphene liquid cell (GLC) transmission electron microscopy and four-dimensional scanning transmission electron microscopy to image the etching dynamics of gold nanorods in the reaction media. Critical to our experiment is the small liquid thickness in a GLC that allows the collection of high-quality electron diffraction patterns at low dose conditions. Machine learning-based data-mining of the diffraction patterns maps the three-dimensional nanocrystal orientation, groups spatial domains of various species in the GLC, and identifies newly generated nanocrystallites during reaction, offering a comprehensive understanding on the reaction mechanism inside a nanoenvironment. This work opens opportunities in probing the interplay of structural properties such as phase and strain with solution-phase reaction dynamics, which is important for applications in catalysis, energy storage, and self-assembly.

four-dimensional scanning transmission electron mi↗
DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

36 MATERIALS SCIENCE↗