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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 OSTI2020

X-ray topography characterization of gallium nitride substrates for power device development

Gallium nitride substrates grown by the hydride vapor phase epitaxy (HVPE) method using a patterned growth process have been characterized by synchrotron monochromatic beam X-ray topography in the grazing incidence geometry. Images reveal a starkly heterogeneous distribution of dislocations with areas as large as 0 3 mm 2 containing threading dislocation densities below 10 3 cm -2 in between a grid of strain centers with higher threading dislocation densities (> 10 4 cm -2 ). Basal plane dislocation densities in these areas are as low as 104 cm -2 . By comparing the recorded images of dislocations with ray tracing simulations of expected dislocations in GaN, the Burgers vectors of the dislocations have been determined. The distribution of threading screw/mixed dislocations (TSDs/TMDs), threading edge dislocations (TEDs) and basal plane dislocations (BPDs) is discussed with implications for fabrication of power devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Role of V-defect density on the performance of III-nitride green LEDs on sapphire substrates

In this paper, we experimentally investigated the role of V-defect density on the performance of green III-nitride LEDs grown on sapphire substrates by metalorganic chemical vapor deposition. We systematically varied the threading dislocation (TD) density from 4 × 10 8 to 1 × 10 9 cm -2 by changing the V/III ratio during initial high temperature GaN growth. A 30-period InGaN/GaN superlattice promoted V-defect formation and growth at TDs, where the density of V-defects was correlated to the TD density. By interrupting the LED growth and examining the surface of the active region, we quantified the average size and density of V-defects. In a series of LEDs, we measured a systematic decrease in forward voltage (V F ) with V-defect density. At a V-defect density of 5.0 × 10 8 cm -2 and TD density of 1 × 10 9 cm -2 , green LED devices were demonstrated with λ = 523 nm and V F = 2.94 V at 20 A cm -2 . These results highlight the potential of using V-defect engineering to achieve low V F long wavelength LEDs on sapphire substrates, where opening of remaining threading dislocations into V-defects presents an opportunity for further V F reduction.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Status and new features of the topography beamline 1-BM after the Advanced Photon Source upgrade

The beamline 1-BM of the Advanced Photon Source (APS), a bending-magnet beamline with an effective X-ray beam size of ~100×4 mm2, has relatively comprehensive synchrotron topography and rocking curve imaging capabilities for characterization of crystals (particularly wide-bandgap semiconductors SiC, AlN, GaN, Ga2O3 etc). It is equipped with a white-beam topography stage for imaging large wafers up to 8 inches. It also has a double-crystal setup, of which the second stage can be used for monochromatic-beam topography. The first stage has different beam conditioners in the grazing-incidence geometry that can expand the vertical beam size from 4 to ~100 mm for double-crystal rocking curve imaging when it is combined with the second stage. Recently APS has been upgraded to a modern 4th-generation light source, and 1-BM has been recommissioned to its normal operation for general users with better performance. The upgraded APS leads to new features at 1-BM. The much smaller source size and higher X-ray coherence significantly improve the image resolution and contrast. The higher flux and brightness of the new source reduce exposure time, which mitigates the mechanical drifting and vibration issues. Here the main capabilities and status of 1-BM together with these new features are introduced.

X-ray topography↗
DOE OSTI2025

A high-throughput approach for statistical process optimization in Laser Powder Bed Fusion

Process variability is inherent in metal additive manufacturing (AM). However, it is often overlooked in process optimization frameworks, constraining the understanding of process uncertainties and their influence on parameter selection. To address this, we present an integrated framework that combines high-throughput single-track experiments, GAN-based melt pool geometry extraction, robust statistical and machine learning modeling, and uncertainty-quantified process mapping. Process variability is characterized through single-track melt pool behaviors, and its influence on defect formation is systematically quantified to enable statistically guided process parameter optimization. This approach is demonstrated on Laser Powder Bed Fusion (L-PBF) of stainless steel 316L, effectively capturing the interplay between process parameters, melt pool variability, and defect probability. By integrating uncertainty quantification into process optimization, this study provides a structured methodology for addressing variability challenges in AM quality control, ultimately contributing to enhanced manufacturing reliability.

Laser Powder Bed Fusion↗
DOE OSTI2024

Microscopy modality transfer of steel microstructures: Inferring scanning electron micrographs from optical microscopy using generative AI

Scanning electron microscopy (SEM) is resource intensive, which limits its throughput in some applications. As an alternative, we propose applying computer vision and machine learning to generate high-quality synthetic SEM micrographs from micrographs obtained using light optical microscopy (LOM). Working with a correlated LOM/SEM dataset of dual-phase steel images, we test generative models of various architectures, including encoder-decoder networks, generative adversarial networks (GANs), and diffusion-based models. We find that the diffusion models significantly outperform other methods on both qualitative and quantitative assessments, while preserving key metallurgical meaning. This work establishes diffusion as the state-of-the-art for microscopy modality transfer and demonstrates the potential of AI-powered microscopy to enhance LOM with micron scale structural recreation.

Computer vision↗
DOE OSTI2022

Explainable machine learning of the underlying physics of high-energy particle collisions

We present an implementation of an explainable and physics-aware machine learning model capable of inferring the underlying physics of high-energy particle collisions using the information encoded in the energy-momentum four-vectors of the final state particles. We demonstrate the proof-of-concept of our White Box AI approach using a Generative Adversarial Network (GAN) which learns from a DGLAP-based parton shower Monte Carlo event generator. The constrained generator network architecture mimics the structure of a parton shower exhibiting similarities with Recurrent Neural Networks (RNNs). We show, for the first time, that our approach leads to a network that is able to learn not only the final distribution of particles, but also the underlying parton branching mechanism, i.e. the Altarelli-Parisi splitting function, the ordering variable of the shower, and the scaling behavior. While the current work is focused on perturbative physics of the parton shower, we foresee a broad range of applications of our framework to areas that are currently difficult to address from first principles in QCD. Examples include nonperturbative and collective effects, factorization breaking and the modification of the parton shower in heavy-ion, and electron-nucleus collisions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Influence of Polymorphism on the Electronic Structure of Ga 2 O 3

The search for new wide-band-gap materials is intensifying to satisfy the need for more advanced and energy-efficient power electronic devices. Ga 2 O 3 has emerged as an alternative to SiC and GaN, sparking a renewed interest in its fundamental properties beyond the main β-phase. Here, three polymorphs of Ga 2 O 3 , α, β, and ε, are investigated using X-ray diffraction, X-ray photoelectron and absorption spectroscopy, and ab initio theoretical approaches to gain insights into their structure–electronic structure relationships. Valence and conduction electronic structure as well as semicore and core states are probed, providing a complete picture of the influence of local coordination environments on the electronic structure. State-of-the-art electronic structure theory, including all-electron density functional theory and many-body perturbation theory, provides detailed understanding of the spectroscopic results. The calculated spectra provide very accurate descriptions of all experimental spectra and additionally illuminate the origin of observed spectral features. This paper provides a strong basis for the exploration of the Ga 2 O 3 polymorphs as materials at the heart of future electronic device generations.

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

Wide Band Gap Chalcogenide Semiconductors

Wide band gap semiconductors are essential for today’s electronic devices and energy applications because of their high optical transparency, controllable carrier concentration, and tunable electrical conductivity. The most intensively investigated wide band gap semiconductors are transparent conductive oxides (TCOs), such as tin-doped indium oxide (ITO) and amorphous In–Ga–Zn–O (IGZO), used in displays and solar cells, carbides (e.g., SiC) and nitrides (e.g., GaN) used in power electronics, and emerging halides (e.g., γ-CuI) and 2D electronic materials (e.g., graphene) used in various optoelectronic devices. Compared to these prominent materials families, chalcogen-based (Ch = S, Se, Te) wide band gap semiconductors are less heavily investigated but stand out because of their propensity for p-type doping, high mobilities, high valence band positions (i.e., low ionization potentials), and broad applications in electronic devices such as CdTe solar cells. This manuscript provides a review of wide band gap chalcogenide semiconductors. First, we outline general materials design parameters of high performing transparent semiconductors, as well as the theoretical and experimental underpinnings of the corresponding research methods. We proceed to summarize progress in wide band gap (EG > 2 eV) chalcogenide materials—namely, II–VI MCh binaries, CuMCh 2 chalcopyrites, Cu 3 MCh 4 sulvanites, mixed-anion layered CuMCh(O,F), and 2D materials—and discuss computational predictions of potential new candidates in this family, highlighting their optical and electrical properties. Then, we finally review applications—for example, photovoltaic and photoelectrochemical solar cells, transistors, and light emitting diodes—that employ wide band gap chalcogenides as either an active or passive layer. Overall, by examining, categorizing, and discussing prospective directions in wide band gap chalcogenides, this Review aims to inspire continued research on this emerging class of transparent semiconductors and thereby enable future innovations for optoelectronic devices.

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

Gate-Tunable Semiconductor Heterojunctions from 2D/3D van der Waals Interfaces

Van der Waals (vdW) semiconductors are attractive for highly scaled devices and heterogeneous integration since they can be isolated into self-passivated, two-dimensional (2D) layers that enable superior electrostatic control. These attributes have led to numerous demonstrations of field-effect devices ranging from transistors to triodes. By exploiting the controlled, substitutional doping schemes in covalently-bonded, three-dimensional (3D) semiconductors and the passivated surfaces of 2D semiconductors, one can construct devices that can exceed performance metrics of “all-2D” vdW heterojunctions. Here, we demonstrate, 2D/3D semiconductor heterojunctions using MoS2 as the prototypical 2D semiconductor laid upon Si and GaN as the 3D semiconductor layers. By tuning the Fermi levels in MoS2, we demonstrate devices that concurrently exhibit over seven orders of magnitude modulation in rectification ratios and conductance. Our results further suggest that the interface quality does not necessarily affect Fermi-level tuning at the junction opening up possibilities for novel 2D/3D heterojunction device architectures

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Single-Atom-Resolved Vibrational Spectroscopy of a Dislocation

Dislocations in III-nitride semiconductors impede heat transport, leading to localized overheating, which severely limits the performance and reliability of optoelectronic and power devices. Current research on phonon–dislocation interactions primarily addresses bulk materials, focusing on the average effects at specific dislocation densities. However, phonon resistance from dislocation scattering arises from both short-range core interactions and long-range strain field interactions, which remain largely unexplored. Here, in this study, electron energy-loss spectroscopy is used to investigate a GaN dislocation. Vibrational modes localized on specific core atoms are revealed, reflecting short-range interactions. Additionally, phonon energy shifts driven by strain fields surrounding the dislocation are observed, reflecting long-range interactions. Ab initio calculations support these findings and draw out additional details. This work establishes a paradigm for probing defect-induced phonon scattering at the single-atom level, revealing how dislocations affect phonon behavior through atomic reconstruction and strain engineering, thus offering insights for designing improved material functionalities.

III-nitride semiconductors↗
DOE OSTI2020

Selective-Area Remote Epitaxy of ZnO Microrods Using Multilayer–Monolayer-Patterned Graphene for Transferable and Flexible Device Fabrications

Here, selective-area remote epitaxy (SA-REpi) is demonstrated for fabricating mechanically releasable position-controlled ZnO microrod (MR) arrays from donor wafers in an arrayed form. Intaglio-patterned graphene, consisting of basal single-layer graphene (SLG) overlayered with multilayer graphene (MLG) patterned with perforated holes, is transferred onto a GaN/Al 2 O 3 wafer on which the hydrothermal synthesis is performed for growing ZnO MRs. The basal SLG area exposed through the MLG pattern yields ZnO MRs, whereas the MLG plateau inhibits the growth. The noncovalent remote epitaxial heterointerface enables the release of the MR overlayer in the arrayed form, and the original source wafer is refurbished for reproducibly repeating the SA-REpi. Density-functional theory calculations suggest that localized surface charge density is induced on the surface of SLG by the underlying GaN across ultrathin SLG, which possibly provides a driving force for precursor adatoms and the following remote epitaxy of ZnO. In contrast, the induction of the charge density redistribution does not clearly occur through MLG; so, that keeps the surface of MLG nearly charge-neutral. The diameter and spacing of ZnO MRs are controlled in a designed way by changing the pattern geometries. High-resolution scanning transmission electron microscopy reveals the remote heteroepitaxial relationship at an atomic level. The remote epitaxy is expected to provide an ideal platform to transfer the addressable spatial arrays of nano- or micro-architecture semiconductor components to arbitrary target surfaces directly after the growth without the assembly procedures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

When Photoelectrons Meet Gas Molecules: Determining the Role of Inelastic Scattering in Ambient Pressure X-ray Photoelectron Spectroscopy

Inelastic photoelectron scattering (IPES) by gas molecules, a critical phenomenon observed in ambient pressure X-ray photoelectron spectroscopy (APXPS), complicates spectral interpretation due to kinetic energy loss in the primary spectrum and the appearance of additional features at higher binding energies. In this study, we systematically investigate IPES in various gas environments using APXPS, providing detailed insights into interactions between photoelectrons emitted from solid surfaces and surrounding gas molecules. Corelevel XPS spectra of Au, Ag, Zn, and Cu metals were recorded over a wide kinetic energy range in the presence of CO 2 , N 2 , Ar, and H 2 gases, demonstrating the universal nature of IPES across different systems. Additionally, we analyzed spectra of scattering effects induced by gas-phase interactions without metal solids. In two reported CO 2 -reduction systems (p-GaN/ Au/Cu and p-Si/TaO x /Cu), we elucidated that IPES is independent of the composition, structure, or size of the solid materials. Using metal foil platforms, we further developed an analytical model to extract electron excitation cross sections of gas molecules. These findings enhance our understanding of IPES mechanisms and enable the predictions of IPES structures in other solid–gas systems, providing a valuable reference for future APXPS studies and improving the accuracy of spectral analysis in gas-rich catalytic interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗
DOE OSTI2020

An Observational Comparison of Level of Neutral Buoyancy and Level of Maximum Detrainment in Tropical Deep Convective Clouds

Tropical deep convective clouds are important drivers of large-scale atmospheric circulation representing the main vertical transport pathway through the depth of the troposphere for heat, momentum, water, and chemical species. The strength and depth of this transport are impacted by the convective updraft size and intensity that are driven by buoyancy, dynamical forcing, and mixing of environmental air, i.e., entrainment. In this paper, we identify tropical deep convective systems with well-defined forward anvils using Atmospheric Radiation Measurement (ARM) ground-based profiling radars, at three ARM fixed-sites in the Tropical Western Pacific (TWP; i.e., Manus, Nauru, Darwin) and three ARM Mobile Facility deployments in Niamey, Niger; Gan Island, Maldives; and Manacapuru, Brazil. We use the difference between the level of neutral buoyancy (LNB) and the level of maximum detrainment (LMD) as a proxy for the effective bulk convective entrainment (εproxy). The LNB, the theoretical height that a parcel raised above the level of free convection would reach with no mixing, is calculated based on pre-convection radiosonde measurements using parcel theory. The LMD is the height of the maximum reflectivity observed in forward anvil clouds by profiling radars. Deep convective systems over the TWP show higher LNBs that extend to 16.3 km on average and larger εproxy (median LNB minus LMD up to 6.5 km) compared to their continental counterparts in the Amazon and West Africa. Oceanic conditions show larger convective available potential energy (CAPE) coupled with higher moisture at low levels which favors larger εproxy. In contrast, continental cases initiate and develop under high convective inhibition, steeper environmental lapse rate, and high wind shear conditions, which show smaller offset between LNB and LMD. Deep convective cases that promote significant cold pools at the surface experience less εproxy. Using a Random Forest regression algorithm, CAPE is associated with the highest feature importance score for predicting convective εproxy, followed by low-level relative humidity. For continental cases, the low-level wind shear also indicates higher importance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Comparison of Conventional and Constrained Variational Methods for Computing Large-Scale Budgets and Forcing Fields

Analyses of atmospheric heat and moisture budgets serve as an effective tool to study convective characteristics over a region and to provide large-scale forcing fields for various modeling applications. This paper examines two popular methods for computing large-scale atmospheric budgets: the conventional budget method (CBM) using objectively gridded analyses based primarily on radiosonde data and the constrained variational analysis (CVA) approach which supplements vertical profiles of atmospheric fields with measurements at the top of the atmosphere and at the surface to conserve mass, water, energy, and momentum. Successful budget computations are dependent on accurate sampling and analyses of the thermodynamic state of the atmosphere and the divergence field associated with convection and the large-scale circulation that influences it. Utilizing analyses generated from data taken during Dynamics of the Madden-Julian Oscillation (DYNAMO) field campaign conducted over the central Indian Ocean from October to December 2011, we evaluate the merits of these budget approaches and examine their limitations. While many of the shortcomings of the CBM, in particular effects of sampling errors in sounding data, are effectively minimized with CVA, accurate large-scale diagnostics in CVA are dependent on reliable background fields and rainfall constraints. Finally, for the DYNAMO analyses examined, the operational model fields used as the CVA background state provided wind fields that accurately resolved the vertical structure of convection in the vicinity of Gan Island. However, biases in the model thermodynamic fields were somewhat amplified in CVA resulting in a convective environment much weaker than observed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Near-field terahertz nonlinear optics with blue light

Abstract The coupling of terahertz optical techniques to scattering-type scanning near-field microscopy (s-SNOM) has recently emerged as a valuable new paradigm for probing the properties of semiconductors and other materials on the nanoscale. Researchers have demonstrated a family of related techniques, including terahertz nanoscopy (elastic scattering, based on linear optics), time-resolved methods, and nanoscale terahertz emission spectroscopy. However, as with nearly all examples of s-SNOM since the technique’s inception in the mid-1990s, the wavelength of the optical source coupled to the near-field tip is long, usually at energies of 2.5 eV or less. Challenges in coupling of shorter wavelengths (i.e., blue light) to the nanotip has greatly inhibited the study of nanoscale phenomena in wide bandgap materials such as Si and GaN. Here, we describe the first experimental demonstration of s-SNOM using blue light. With femtosecond pulses at 410 nm, we generate terahertz pulses directly from bulk silicon, spatially resolved with nanoscale resolution, and show that these signals provide spectroscopic information that cannot be obtained using near-infrared excitation. We develop a new theoretical framework to account for this nonlinear interaction, which enables accurate extraction of material parameters. This work establishes a new realm of possibilities for the study of technologically relevant wide-bandgap materials using s-SNOM methods.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Controlling spin current polarization through non-collinear antiferromagnetism

The interconversion of charge and spin currents via spin-Hall effect is essential for spintronics. Energy-efficient and deterministic switching of magnetization can be achieved when spin polarizations of these spin currents are collinear with the magnetization. However, symmetry conditions generally restrict spin polarizations to be orthogonal to both the charge and spin flows. Spin polarizations can deviate from such direction in nonmagnetic materials only when the crystalline symmetry is reduced. Here, we show control of the spin polarization direction by using a non-collinear antiferromagnet Mn 3 GaN, in which the triangular spin structure creates a low magnetic symmetry while maintaining a high crystalline symmetry. We demonstrate that epitaxial Mn 3 GaN/permalloy heterostructures can generate unconventional spin-orbit torques at room temperature corresponding to out-of-plane and Dresselhaus-like spin polarizations which are forbidden in any sample with two-fold rotational symmetry. Our results demonstrate an approach based on spin-structure design for controlling spin-orbit torque, enabling high-efficient antiferromagnetic spintronics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Efficient and bright white light-emitting diodes based on single-layer heterophase halide perovskites

At present, electric lighting accounts for ~15% of global power consumption and thus the adoption of efficient, low-cost lighting technologies is important. Here, halide perovskites have been shown to be good emitters of pure red, green and blue light, but an efficient source of broadband white electroluminescence suitable for lighting applications is desirable. Here, we report a white light-emitting diode (LED) strategy based on solution-processed heterophase halide perovskites that, unlike GaN white LEDs, feature only one broadband emissive layer and no phosphor. Our LEDs operate with a peak luminance of 12,200 cd m –2 at a bias of 6.6 V and a maximum external quantum efficiency of 6.5% at a current density of 8.3 mA cm –2 . Systematic in situ and ex situ characterizations reveal that the mechanism of efficient electroluminescence is charge injection into the α phase of CsPbI 3 , α to δ charge transfer and α–δ balanced radiative recombination. Future advances in fabrication technology and mechanistic understanding should lead to further improvements in device efficiency and luminance.

36 MATERIALS SCIENCE↗