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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Compositionally graded Ga 1-x In x P buffers grown by static and dynamic hydride vapor phase epitaxy at rates up to 1 μm/min

Here, we demonstrate Ga 1-x In x P compositionally graded buffers (CGBs) grown on GaAs with lattice constants between GaAs and InP by hydride vapor phase epitaxy (HVPE). Growth rates were up to ~1 μm/min and threading dislocation density (TDD) was as low as 1.0 x 10 6 cm -2 . We studied the effect of substrate offcut direction, growth rate, and strain grading rate on CGB defect structure. We compared the effect of a “dynamic grading” style, which creates compositional interfaces via mechanical transfer of a substrate between two growth chambers, vs. “static grading” where the CGB grows in a single chamber. Dynamic grading yielded smoother grades with higher relaxation, but TDD was not significantly different between the two styles. Substrate offcut direction was the most important factor for obtaining CGBs with low defect density. (001) substrates offcut towards (111)B yielded smoother CGBs with lower TDD compared to CGBs grown on substrates offcut towards (111)A. Transmission electron microscopy of static and dynamic CGBs grown on A and B-offcuts only found evidence of phase separation in a static A-offcut CGB, indicating that the B offcut limits phase separation, which in turn keeps TDD low. Reduced growth rate led to the appearance CuPt-type atomic ordering, which affected the distribution of dislocations on the active glide planes but did not alter TDD. Higher growth rates led to smoother CGBs and did not appreciably increase TDD as otherwise predicted by steady-state models of plastic relaxation. These results show HVPE’s promise for lattice-mismatched applications and low-c ost InP virtual substrates on GaAs

36 MATERIALS SCIENCE↗
DOE OSTI2025

Suppression of phase separation in AlGaInAs compositionally graded buffers for 1550 nm photovoltaic converters on GaAs

We investigate strategies to suppress phase separation and reduce threading dislocation density (TDD) in AlGaInAs compositionally graded buffers (CGBs) that span the lattice constant range from GaAs to InP. Combining the results from high resolution x-ray diffraction, cathodoluminescence, transmission electron microscopy, and photovoltaic device measurements, we correlate the choices of epitaxial growth conditions with the defect structure of the CGBs and subsequent device performance. Both the use of substrates with high misorientation off (100) toward the (111)A plane and Zn doping instead of Si doping are shown to suppress phase separation and reduce TDD. We demonstrate a 0.74 eV GaInAs device grown on a GaAs substrate offcut 19.5° toward (111)A using a Zn-doped AlGaInAs CGB with TDD = 3.5 ± 0.2 × 10 6 cm -2 that has a bandgap-open circuit voltage offset of only 0.434 V measured under the AM1.5G solar spectrum. We characterized this device under high-intensity irradiance from a 1570 nm laser and measured a 31.9% peak laser power conversion efficiency at 3.6 W/cm 2 irradiance. These results provide a roadmap to the manufacture of laser- and thermal-power conversion devices with the performance and cost-effectiveness needed to drive adoption of these technologies at scale.

14 SOLAR ENERGY↗
DOE OSTI2019

Hydrophobic catalysis and a potential biological role of DNA unstacking induced by environment effects

Hydrophobic base stacking is a major contributor to DNA double-helix stability. We report the discovery of specific unstacking effects in certain semihydrophobic environments. Water-miscible ethylene glycol ethers are found to modify structure, dynamics, and reactivity of DNA by mechanisms possibly related to a biologically relevant hydrophobic catalysis. Spectroscopic data and optical tweezers experiments show that base-stacking energies are reduced while base-pair hydrogen bonds are strengthened. We propose that a modulated chemical potential of water can promote “longitudinal breathing” and the formation of unstacked holes while base unpairing is suppressed. Flow linear dichroism in 20% diglyme indicates a 20 to 30% decrease in persistence length of DNA, supported by an increased flexibility in single-molecule nanochannel experiments in poly(ethylene glycol). A limited (3 to 6%) hyperchromicity but unaffected circular dichroism is consistent with transient unstacking events while maintaining an overall average B-DNA conformation. Further information about unstacking dynamics is obtained from the binding kinetics of large thread-intercalating ruthenium complexes, indicating that the hydrophobic effect provides a 10 to 100 times increased DNA unstacking frequency and an “open hole” population on the order of 10 –2 compared to 10 –4 in normal aqueous solution. Spontaneous DNA strand exchange catalyzed by poly(ethylene glycol) makes us propose that hydrophobic residues in the L2 loop of recombination enzymes RecA and Rad51 may assist gene recombination via modulation of water activity near the DNA helix by hydrophobic interactions, in the manner described here. We speculate that such hydrophobic interactions may have catalytic roles also in other biological contexts, such as in polymerases.

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

Early Fault Detection in Nuclear Systems: A Digital Engineering Approach

Nuclear energy systems present unique challenges in terms of ensuring safety, reliability, and efficiency during their design and operation. Early fault detection is critical for mitigating risks and fostering system resilience. However, current methods often fall short at identifying faults during early stages, potentially leading to costly delays and safety risks. The present work proposes a comprehensive digital engineering approach that leverages digital twins, digital threads, model-based systems engineering, artificial intelligence, and immersive extended reality to support early fault detection in nuclear systems. Through a series of case studies, we highlight specific gaps in the fault detection mechanisms of traditional nuclear design and operation processes, then demonstrate a suite of solutions we are working to implement to address these shortcomings in similar projects. Our findings suggest that a digital engineering approach to design and operation can significantly improve fault detection, ultimately leading to reductions in risk.

42 - ENGINEERING↗
DOE OSTI2026

Evaluation of AI-enabled Digital Documented Safety Analysis

The National Reactor Innovation Center (NRIC) is leading a transformative initiative to accelerate advanced reactor deployment by fundamentally reimagining how nuclear safety basis documentation is developed, reviewed, and maintained. Traditional Documented Safety Analysis (DSA) processes for DOE-authorized facilities rely on static, document-centric workflows that consume significant time and resources, exemplified by recent major licensing efforts requiring hundreds of thousands of staff hours and millions of pages of documentation review. These conventional approaches create barriers to the rapid, cost-effective deployment of advanced reactors that America's future energy needs demand. NRIC's DOE Authorization Digital Transformation Project addresses these challenges through an innovative framework that integrates artificial intelligence (AI), digital engineering, and systems-based data management into a cohesive digital ecosystem. This white paper presents NRIC's methodology for evaluating AI-enabled document generation capabilities within this broader digital infrastructure, using the Demonstration of Microreactor Experiments (DOME) facility as a pilot case study. The evaluation will assess an AI tool's ability to generate a Preliminary Documented Safety Analysis (PDSA) through progressive integration stages—from standalone document processing to full digital thread connectivity—while maintaining rigorous verification, validation, and regulatory acceptance standards. By establishing dynamic, traceable connections between design data and safety documentation, NRIC's approach has the potential to reduce both document development time and regulatory review cycles by as much as 50%, while simultaneously improving accuracy, consistency, and traceability. This initiative represents a critical step toward establishing reusable digital infrastructure that reactor developers can leverage to accelerate their path from concept to commercial operation, directly supporting NRIC's mission to demonstrate and deploy advanced nuclear energy technologies.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Towards Automated Cyber Mission Modelling

Large-scale enterprises execute a full range of missions to satisfy objectives. Healthy enterprises should acquire and maintain mission awareness, which requires reasoning over mission models that identify the structure and character of missions along with their related cyber resources. Models are typically constructed by subject matter experts using a time- and labour-intensive manual process. This paper describes a novel framework comprising high-level processes that model mission essential functions and mission threads as well as recognize active instances. This framework enables data-driven, semi-automated modelling to construct accurate, timely mission representations necessary for mission assurance and mission mapping.

mission modelling, mission awareness, mission assu↗
DOE OSTI2025

Artificial Intelligence and Digital Engineering as Enablers for System Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world’s energy demands and build energy security.

42 - ENGINEERING↗
DOE OSTI2025

Artificial Intelligence and Digital Engineering as Enablers for Systems Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world?s energy demands and build energy security.

42 - ENGINEERING↗
DOE OSTI2017

Si Complies with GaN to Overcome Thermal Mismatches for the Heteroepitaxy of Thick GaN on Si

Heteroepitaxial growth of lattice mismatched materials has advanced through the epitaxy of thin coherently strained layers, the strain sharing in virtual and nanoscale substrates, and the growth of thick films with intermediate strain‐relaxed buffer layers. However, the thermal mismatch is not completely resolved in highly mismatched systems such as in GaN‐on‐Si. Here, geometrical effects and surface faceting to dilate thermal stresses at the surface of selectively grown epitaxial GaN layers on Si are exploited. The growth of thick (19 µm), crack‐free, and pure GaN layers on Si with the lowest threading dislocation density of 1.1 × 10 7 cm −2 achieved to date in GaN‐on‐Si is demonstrated. With these advances, the first vertical GaN metal–insulator–semiconductor field‐effect transistors on Si substrates with low leakage currents and high on/off ratios paving the way for a cost‐effective high power device paradigm on an Si CMOS platform are demonstrated

Tanaka, Atsunori↗
DOE OSTI2022

Oxide Two‐Dimensional Electron Gas with High Mobility at Room‐Temperature

Abstract The prospect of 2‐dimensional electron gases (2DEGs) possessing high mobility at room temperature in wide‐bandgap perovskite stannates is enticing for oxide electronics, particularly to realize transparent and high‐electron mobility transistors. Nonetheless only a small number of studies to date report 2DEGs in BaSnO 3 ‐based heterostructures. Here, 2DEG formation at the LaScO 3 /BaSnO 3 (LSO/BSO) interface with a room‐temperature mobility of 60 cm 2 V −1 s −1 at a carrier concentration of 1.7 × 10 13 cm –2 is reported. This is an order of magnitude higher mobility at room temperature than achieved in SrTiO 3 ‐based 2DEGs. This is achieved by combining a thick BSO buffer layer with an ex situ high‐temperature treatment, which not only reduces the dislocation density but also produces a SnO 2 ‐terminated atomically flat surface, followed by the growth of an overlying BSO/LSO interface. Using weak beam dark‐field transmission electron microscopy imaging and in‐line electron holography technique, a reduction of the threading dislocation density is revealed, and direct evidence for the spatial confinement of a 2DEG at the BSO/LSO interface is provided. This work opens a new pathway to explore the exciting physics of stannate‐based 2DEGs at application‐relevant temperatures for oxide nanoelectronics.

2-dimensional electron gas↗
DOE OSTI2024

Sub‐0.6 eV Inverted Metamorphic GaInAs Cells Grown on Inp and GaAs Substrates for Thermophotovoltaics and Laser Power Conversion

Abstract Inverted metamorphic Ga 0.3 In 0.7 As photovoltaic converters with sub‐0.60 eV bandgaps grown on InP and GaAs are presented. Threading dislocation densities are 1.3 ± 0.6 × 10 6 and 8.9 ± 1.7 × 10 6 cm −2 on InP and GaAs, respectively. The devices generate open‐circuit voltages of 0.386 and 0.383 V, respectively, under irradiance producing a short‐circuit current density of ≈10 A cm −2 , yielding bandgap‐voltage offsets of 0.20 and 0.21 V. Power and broadband reflectance measurements are used to estimate thermophotovoltaic (TPV) efficiency. The InP‐based cell is estimated to yield 1.09 W cm −2 at 1100 °C versus 0.92 W cm −2 for the GaAs‐based cell, with efficiencies of 16.8 versus 9.2%. The efficiencies of both devices are limited by sub‐bandgap absorption, with power weighted sub‐bandgap reflectances of 81% and 58%, respectively, the majority of which is assumed to occur in the graded buffers. The 1100 °C TPV efficiencies are estimated to increase to 24.0% and 20.7% in structures with the graded buffer removed, if previously demonstrated reflectance is achieved. These devices also have application to laser power conversion in the 2.0–2.3 µm atmospheric window. Peak laser power converter efficiencies of 36.8% and 32.5% are estimated under 2.0 µm irradiances of 1.86 and 2.81 W cm −2 , respectively.

14 SOLAR ENERGY↗
DOE OSTI2018

Flexible and Hierarchical Metal–Organic Framework Composites for High‐Performance Catalysis

Abstract The development of porous composite materials is of great significance for their potentially improved performance over those of individual components and extensive applications in separation, energy storage, and heterogeneous catalysis. Now mesoporous metal–organic frameworks (MOFs) with macroporous melamine foam (MF) have been integrated using a one‐pot process, generating a series of MOF/MF composite materials with preserved crystallinity, hierarchical porosity, and increased stability over that of melamine foam. The MOF nanocrystals were threaded by the melamine foam networks, resembling a ball‐and‐stick model overall. The resulting MOF/MF composite materials were employed as an effective heterogeneous catalyst for the epoxidation of cholesteryl esters. Combining the advantages of interpenetrative mesoporous and macroporous structures, the MOF/melamine foam composite has higher dispersibility and more accessibility of catalytic sites, exhibiting excellent catalytic performance.

Huang, Ning↗
DOE OSTI2021

An Integrated Design of a Polypseudorotaxane-Based Sea Cucumber Mimic

The development of integrated systems that mimic the multi-stage stiffness change of marine animals such as the sea cucumber requires the design of molecularly tailored structures. Herein, we used an integrated biomimicry design to fabricate a sea cucumber mimic using sidechain polypseudorotaxanes with tunable nano-to-macroscale properties. A series of polyethylene glycol (PEG)-based sidechain copolymers were synthesized to form sidechain polypseudorotaxanes with α-cyclodextrins (α-CDs). By tailoring the copolymers’ molecular weights and their PEG grafting densities, we rationally tuned the sizes of the formed polypseudorotaxanes crystalline domain and the physical crosslinking density of the hydrogels, which facilitated 3D printing and the mechanical adaptability to these hydrogels. After 3D printing and photo-crosslinking, the obtained hydrogels exhibited large tensile strain and broad elastic-to-plastic variations upon α-CD (de)threading. Finally, these discoveries enabled a successful fabrication of a sea cucumber mimic, demonstrating multi-stage stiffness changes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Optimizing point‐to‐point communication between adaptive MPI endpoints in shared memory

Summary Adaptive MPI is an implementation of the MPI standard that supports the virtualization of ranks as user‐level threads, rather than OS processes. In this work, we optimize the communication performance of AMPI based on the locality of the endpoints communicating within a cluster of SMP nodes. We differentiate between point‐to‐point messages with both endpoints co‐located on the same execution unit and point‐to‐point messages with both endpoints residing in the same process but not on the same execution unit. We demonstrate how the messaging semantics of Charm++ enable and hinder AMPI's implementation in different ways, and we motivate extensions to Charm++ to address the limitations. Using the OSU micro‐benchmark suite, we show that our locality‐aware design offers lower latency, higher bandwidth, and reduced memory footprint for applications.

White, Sam↗
DOE OSTI2021

Instruction Roofline: An insightful visual performance model for GPUs

The Roofline performance model provides an intuitive approach to identify performance bottlenecks and guide performance optimization. However, the classic FLOP-centric approach is inappropriate for the emerging applications that perform more integer operations than floating point operations. In this article, we reintroduce our Instruction Roofline Model on NVIDIA GPUs and expand our evaluation of it. The Instruction Roofline incorporates instructions and memory transactions across all memory hierarchies together, and provides more performance insights than the FLOP-oriented Roofline Model, that is, instruction throughput, stride memory access patterns, bank conflicts, and thread predication. We use our Instruction Roofline methodology to analyze eight proxy applications: HPGMG from AMReX, Matrix Transpose benchmarks, ADEPT from MetaHipMer's sequence alignment phase, EXTENSION from MetaHipMer's local assembly phase, CUSP, cuSPARSE, cudaTensorCoreGemm, and cuBLAS. We demonstrate the ability of our methodology to understand various aspects of performance and performance bottlenecks on NVIDIA GPUs and motivate code optimizations.

Ding, N↗
DOE OSTI2026

Speedup of UEDGE Parameter Scans Using Machine-Learning Optimized OpenMP Parallelization and a Continuation Solver

This article presents the OpenMP parallelization of the preconditioning Jacobian assembly and right‐hand side residual evaluation in UEDGE. A continuation algorithm, utilizing the internal NKSOL implicit Jacobian‐Free Newton‐Krylov solver to efficiently scan physical parameters, is also presented. The implemented parallelization reduces the computational time for a benchmark scan run on 32 threads by compared to the serial version when using trained random forest regression models to identify the optimal decomposition of the system of equations. Random forest regression models applied to the UEDGE time‐dependent and continuation solver algorithms did not yield meaningful improvement in computational performance. A benchmark DIII‐D gas injection rate scan in the 0.35–0.75 kA interval, performed on a test cluster using the parallelized code and continuation solver, produced 1066 steady‐state solutions with a 22 s average wall‐clock computational time per steady‐state solution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗