SEARCH · Search NASA

Results for “High Performance Nuclear Thermal Propulsion NTP SNP”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

2,208 records · Page 98

All sources NASA NTRS DOE OSTI

DOE OSTI2026

X-ray tomography of damage dynamics in advanced materials using a laser wakefield accelerator

Additively manufactured (AM) metals offer the potential for customizable, cost-effective components, but qualification and certification are crucial. Key to this process is understanding pore dynamics under stress, typically analyzed using micro-computed tomography. This study introduces laboratory-scale “betatron” x-rays from laser wakefield acceleration as a high-throughput alternative for x-ray tomography of advanced materials, such as AM AlSi10Mg alloys. Coupled with 3D finite element modeling, this method provides detailed insights into stress-porosity interactions. The approach delivers high-resolution scans, revealing that pore shape and local triaxiality significantly influence fracture dynamics, supporting advanced material characterization. This work also demonstrates the potential and versatility of laser-betatron x-ray μCT for generating large datasets to accelerate our understanding of the stochastic, process-specific nature of pore formation in AM alloys.

Senthilkumaran, Vigneshvar↗

NASA NTRSDate not supplied

Biocybernetic Closed-Loop System for Mitigating Hazardous States of Awareness

The past century of passenger flight has seen continuous improvement in aviation safety by the aerospace industry. However, while commercial aviation accident rates have continued to decline, human error-related incident and accident rates remain remarkably constant across all types of aviation (Shappell, et al., 2007). Unfortunately, this level of human error is unacceptable when considering projections for increased traffic volume (FAA, 2009), and is likely to yield more incidents and accidents unless a more complete understanding of operator error is achieved and remediations are implemented. One area of interest highlighted by researchers is Hazardous States of Awareness (HSAs) that can result from deficiencies in the design and inappropriate use of human-machine interfaces. Identifying and mitigating HSAs is critical for reducing operator errors. One promising approach uses psychophysiological measures which enable automated systems to adapt to the operator?s state and modify modes of operation to support optimal human performance (Scerbo, 2007). This paper will survey previous research and describe future directions for the application of psychophysiological measures of operators derived from cortical and autonomic assessment to perform real-time adaptive modulation of human-automation task mode mixes. The authors will present a summary of previous work done at NASA LaRC and Old Dominion University using a Psychophysiologically Adaptive System (PAS) in which the level of automation of the NASA Multi-Attribute Task Battery was modulated based on Engagement Indices derived from the users? electroencephalogram (Pope, Bogart, & Bartolome, 1995; for review see, Scerbo, Freeman, & Mikulka, 2003). Future theoretical and methodological directions for this type of closed-loop research will be discussed. Specifically, the capacity for this type of PAS to maintain effective operator state and to enable validation of candidate physiological indices will be described. Consideration will also be given to critical system characteristics (e.g., engagement indices, methods for invoking changes among system states, individual differences among users, etc.) that have been or still need to be studied. The potential of the PAS approach for interactive system design and prototyping will also be described. Examples of adaptive automation flight deck concepts in recent experiments will be highlighted and discussed.

Chad L Stephens↗

NASA NTRS1994

Crystal Growth of Selected II-VI Semiconducting Alloys By Directional Solidification

A Hg 0.84 Zn 0.16 Te alloy crystal was back-melted and partially resolidified during the first United States Microgravity Laboratory (USML-1) mission in the Marshall Space Flight Center's Crystal Growth Furnace. The experiment was inadvertently terminated at about 30% of planned completion. Nonetheless, it was successfully demonstrated that HgZnTe alloy ingots partially grown and quenched on the ground can be back-melted and regrown in space under nearly steady state growth conditions. An identical 'ground-truth' experiment was performed following the mission. Preliminary results are presented for both crystals, as well as for a series of other crystals grown prior to the mission for the purposes of optimizing in-flight growth conditions.

S L Lehoczky↗

NASA NTRS1990

Artificial Intelligence for Multi-Mission Planetary Operations

A brief introduction is given to an automated system called the Spacecraft Health Automated Reasoning Prototype (SHARP). SHARP is designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for evaluation of the prototype in a real-time operations setting during the Voyager spacecraft encounter with Neptune in August, 1989. The preliminary results of the SHARP project and plans for future application of the technology are discussed.

David J Atkinson↗

DOE OSTI2025

Large language model-driven database for thermoelectric materials

Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here, in this work, we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.

Database↗

DOE OSTI2025

Monitoring Depolymerization in Mesopores Using Dynamic Properties of Polymeric Melt Accessed via Dielectric Spectroscopy

Traditional design principles for heterogeneous catalysis guide the use of catalytic particles with mesosized (∼2–50 nm) pores to increase the number of surface-active sites by way of an increased surface area. However, the entry of long-chain polymers into such pores may be significantly limited by the size and entanglement of polymers in the melt state, thereby decreasing the number of accessible sites. Assessment of catalyst performance from traditional reactor-based studies averages over intrapore reaction events as well as reactions on the surface of a particle, resulting in an inability to distinguish between differences in site accessibility and activity. Techniques that assess the intrapore performance can inform the design of future heterogeneous catalysts for polymer upcycling. In this work, we demonstrate the use of broadband dielectric spectroscopy to monitor depolymerization of a polymer melt within mesopores via changes in the segmental relaxation time scale of amorphous polymer chains. In particular, we highlight the use of an anodic aluminum oxide (AAO) membrane as a readily available model for catalyst pores with a well-characterized pore morphology. The decrease in the segmental relaxation (α-relaxation) time of the melt with increasing chain scission emerges as a measure of the extent of polymer deconstruction inside mesopores. To demonstrate the utility of this technique, we demonstrate the decomposition of two commercial poly(propylene carbonate) polymers with different decomposition rates within mesopores. As the polymers depolymerize, their segmental relaxation time decreases as the molecular weight decreases (as predicted by the Fox–Flory equation). The BDS-measured change in segmental relaxation time mirrors the expected trend based on change in molecular weight measured by size exclusion chromatography.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Anticipating Optical Availability in Hybrid RF/FSO Links Using RF Beacons and Deep Learning

Radiofrequency (RF) communications offer reliable but low data rates and energy-inefficient satellite links, while free-space optical (FSO) promises high bandwidth but struggles with disturbances imposed by atmospheric effects. A hybrid RF/FSO architecture aims to achieve optimal reliability along with high data rates for space communications. Accurate prediction of dynamic ground-to-satellite FSO link availability is critical for routing decisions in low-earth orbit constellations. In this paper, we propose a system leveraging ubiquitous RF links to proactively forecast FSO link degradation prior to signal drops below threshold levels. This enables pre-calculation of rerouting to maximally maintain high data rate FSO links throughout the duration of weather effects. We implement a supervised learning model to anticipate FSO attenuation based on the analysis of RF patterns. Through the simulation of a dense lower earth orbit (LEO) satellite constellation, we demonstrate the efficacy of our approach in a simulated satellite network, highlighting the balance between predictive accuracy and prediction duration. An emulated cloud attenuation model is proposed to provide insight into the temporal profiles of RF signals and their correlation to FSO channel dynamics. Our investigation sheds light on the trade-offs between prediction horizon and accuracy arising from RF beacon numbers and proximity.

FSO availability↗

DOE OSTI2026

Prime Time for Model-Predictive Control? Assessing the Technical and Market Readiness of Advanced Controls in Buildings

Despite three decades of extensive research and field testing that have consistently validated the benefits of Model Predictive Control (MPC) in building applications, the technology has seen limited market adoption. This paper evaluates the readiness of MPC for widespread deployment, showcases recent demonstrations and field tests across diverse building types, including residential, small commercial, large commercial, and campus settings. Our results demonstrate that MPC can optimize system operations to achieve load shifting, minimize curtailment of on-site generation, and reduce energy costs by up to 80 %, while maintaining or improving occupant comfort. We also show that MPC can effectively control large assets, such as MW-sized thermal storage systems, and respond to dynamic pricing signals. However, achieving scale remains difficult due to labor-intensive workflows, reliance on a “PhD-in-the-loop” for MPC design and maintenance, susceptibility to fragile data infrastructure, and persistent workforce education and acceptance barriers. To bridge this gap, we outline a transition from bespoke, labor intensive prototypes toward streamlined, segment-targeted deployment strategies that leverage model templates, semantic tools, and generative AI. By automating control configuration and reducing engineering effort, these recommendations provide a pathway for transforming successful research demonstrations into scalable, market ready solutions for MPC-based controls.

Pritoni, Marco↗

DOE OSTI2025

Numerical simulation of frost formation and heat transfer on fin-and-tube heat exchangers in turbulent cross-flow

Frost formation in fin-and-tube heat exchangers in turbulent cross-flow presents significant challenges in industrial refrigeration applications, affecting heat transfer efficiency and operational reliability. The purpose of this work is to investigate frost deposition and growth on a staggered bank of a fin-and-tube freezer coil under turbulent forced convection conditions. The focus here is on investigating conditions that closely replicate real-world scenarios in large walk-in industrial freezers. Using a direct numerical simulation approach, we examine the flow dynamics and thermal behaviour in the presence of frost, considering turbulent regimes characterized by a Reynolds number in the range 1050 ≤ R e D , avg ≤ 4800 , with the characteristic length being the outer diameter of the tube and the velocity being the bulk fluid velocity between the plates (fins). Computational fluid dynamics simulations are employed to resolve the interactions between turbulent airflow and the frost layer. Our approach incorporates a modified immersed boundary method and a slow-time acceleration technique to address the complex dynamic interface between the continuously evolving frost layer and the flowing air stream. Our findings indicate that frost forms more on the sides of the finned surfaces (plates) and less on the tubes themselves. This article is part of the theme issue ‘Heat and mass transfer in frost and ice’.

Science & Technology - Other Topics↗

DOE OSTI2026

U.S. ESCO Industry Report: Industry Size and Recent Market Trends, 2022- 2024

The latest edition of the U.S. Energy Service Company (ESCO) Industry Report by Lawrence Berkeley National Laboratory (LBNL) finds that the U.S. ESCO industry continues to show strong growth. The report draws from ESCO industry reported revenue data for the 2022-2024 period, detailing the current size and characteristics of the U.S. ESCO industry. Following 20 years of ESCO industry reports, the 2024 report explores significant revenue trends across market segments, geographic regions, ESCO size, financing structures, and business activities. New analysis in this report outlines customer priorities and non-energy benefit drivers of Energy Savings Performance Contract projects, adjusted revenue analysis detailing the impacts of inflation on industry growth, and project challenges by market segment.

Chelminski, Kathryn↗

DOE OSTI2026

Experimental observation and integrated modelling of proton-beryllium fusion in He and D plasmas at JET

Validated integrated modelling of JET ITER-like wall experiments in which fusion performance is driven by reactions between fast ions and intrinsically present metal wall impurities is presented. A steady-state L-mode plasma with dominant proton-beryllium fusion and neutron yields of up to ≈ 6·10 13 s -1 is developed in He and D, via radiofrequency heating of a H minority. The fusion drive is unambiguously confirmed by the neutral particle analyser, fast ion loss detector, and γ-ray diagnostics. Experiments are analysed via an integrated modelling framework, developed to model the two-stage proton beryllium-fusion chain and produce high-fidelity fusion product source terms. The modelling chain comprises TRANSP and JETTO for plasma core modelling, LOCUST for full orbit product tracking and collisional slowing-down, DRESS to resolve two- and three-body fusion kinematics, and MCNP for neutron transport calculations. Modelling shows that the primary 9 Be(p,n) 9 B reaction is the dominant neutron emitter at naturally present concentrations of beryllium in these experiments. The yield contribution of secondary reactions between fusion products and beryllium, 9 Be(d,n) 10 B and 9 Be(α,n) 12 C, is found to be negligible. The proton-deuteron knock-on effect in D plasmas is modelled, which is calculated to contribute ≈ 25% to the total neutron yield. For both He and D discharges the total computed neutron rates match fission chamber (FC) measurements within the combined experimental and computational uncertainty, with an average discrepancy of ≈ ± 20%. Realistic proton-beryllium neutron sources are propagated through JET’s MCNP neutron transport model which shows that 235 U FCs’ response is sensitive to p–Be source changes, with up to ≈ 10% variation compared to a D–D neutron source. We show that the high-energy tail of the fast proton minority can be studied with multi-foil neutron activation. The framework is also applied to the study of interactions between fast protons and boron impurities, of relevance to ITER. We calculate that in JET conditions a significant alpha source with DT-like energies could be generated through 11 B(p, α)2α fusion, and detected via γ-emission in secondary interactions between fast alphas and boron. The work represents an important step towards validating predictive integrated modelling capabilities for non-standard fusion reactions.

JET↗

DOE OSTI2026

Ultrafast Nanoimaging of Carrier Funneling in Composition-Graded Semiconductor Nanowires

Recent advances in bandgap engineering of low-dimensional semiconductors have enabled high-efficiency carrier transport in miniaturized electronic and optoelectronic devices. The physical properties and functionalities of these materials are governed by complex carrier dynamics coupled with multiple transport mechanisms in tailored band structures. Here, we report ultrafast nanoimaging of carrier funneling and recombination in composition-grade CdSxSe1-x nanowires using pump-probe near-field nanoscopy. Leveraging the high resolution of this technique in both space and time, we resolve nanoscale local carrier dynamics along composition-graded nanowires, revealing the local variation of composition-dependent carrier mobilities and lifetimes that significantly differ from their uniform composition counterparts. Furthermore, we demonstrate a length-dependent behavior wherein shorter nanowires exhibit enhanced funneling effects, accelerating carrier transport by up to 33%. Our findings provide direct visualization of nanoscale carrier transport while supporting an effective approach for investigating complex carrier interactions in inhomogeneous semiconductor nanostructures, with implications for optimizing next-generation optoelectronic devices.

Yang, Rundi↗

DOE OSTI2026

Transient histone deacetylase inhibition reveals cell type invariant and specific effects of chromatin decondensation on irradiation response

Radiation therapy plays a prominent role in breast cancer treatment, but the high doses of radiation damage both healthy and cancerous cells. Therefore, additional research is needed into combination therapies that could preferentially radiosensitize cancer cells compared to surrounding healthy tissue without causing deleterious side effects. Histone deacetylase inhibitor drugs (HDACis) have been tested as radiosensitizers in both basic research and clinical trials, but the long exposure time typically used in these treatments and the lack of matched healthy cell controls often leave aspects of their mechanism of action unclear. Here, we show that transient (2 h) trichostatin A (TSA) treatment of cancerous and non-tumorigenic breast epithelial cell lines increases immediate DNA damage and decreases long term cell viability in both cell types at high radiation doses. Transient TSA treatment also causes an increase in DNA damage signals after 5 Gy X-rays in other cancer and healthy cell types: A375 melanoma cells and BJ5-ta fibroblasts. This suggests that chromatin decompaction acts to increase cellular vulnerability to initial DNA damage from high doses of radiation in a cell type independent manner that does not rely on changes to DNA repair pathways caused by longer TSA treatment. However, responses to lower doses of radiation and long term survival are more cell type specific: only MCF7 cells experience an effect of TSA on DNA damage after 1 Gy X-ray radiation while MCF10a cells experience somewhat more evident cell viability effects of combined TSA and radiation treatment long term.

Li, Heng [Biochemistry & Cellular and Molecular Bi↗

DOE OSTI2024

CatTestHub: A benchmarking database of experimental heterogeneous catalysis for evaluating advanced materials

The ability to quantitatively compare newly evolving catalytic materials and technologies is hindered by the widespread availability of catalytic data collected in a consistent manner. While certain catalytic chemistries have been widely studied across decades of scientific research, quantitative comparisons based on literature information is hindered by variability in reaction conditions, types of reported data, and reporting procedures. Here, we present CatTestHub, an open-access database dedicated to benchmarking experimental heterogeneous catalysis data. Combining systematically reported catalytic activity data for selected probe chemistries, with relevant material characterization and reactor configuration information, the database provides a collection of catalytic benchmarks for distinct classes of active site functionality. Through key choices in data access, availability, and traceability, CatTestHub seeks to balance the fundamental information needs of chemical catalysis and the FAIR data design principles. Details of the database architecture and the means through which to navigate it are presented, highlighting examples of catalytic insights readily drawn from the available benchmarking data. In its current iteration, CatTestHub spans over 250 unique experimental data points, collected over 24 solid catalysts, that facilitated the turnover of 3 distinct catalytic chemistries. Here, a roadmap is presented through which to expand the open-access platform that serves as a community wide benchmark, primarily through continuous addition of kinetic information on select catalytic systems by members of the heterogeneous catalysis community at large.

Benchmark↗

NASA NTRS2026

Manufacturing and Scale-Up of Natural Fiber Composite eVTOL Propeller Skin and C-Channel

This report presents the manufacturing and scale-up of natural fiber composites for aerospace applications, conducted within NASA’s Convergent Aeronautics Solutions portfolio to advance aircraft capabilities and efficiency. The effort focused on the development and demonstration of two proof-of-concept articles, an Electric Vertical Take-off and Landing (eVTOL) propeller skin and a C-channel, produced through an iterative design and process optimization approach. Best practices and guidance on addressing key challenges with bio-based composite materials and manufacturing is provided. Ideally suited for non-load-bearing structural components, these emerging materials offer potential for weight reduction, vibration damping, noise mitigation, interference-free communication, and cost savings, without compromising the performance of safety-critical primary structures.

Natural fibers↗

DOE OSTI2026

Multi-modal dynamic radiography using short-pulse laser-generated probe beams

Radiography is an important tool for the interrogation of dynamic experiments in the fields of dynamic properties of materials, and in condensed matter, high explosive, and high-energy-density physics. Multi-modal radiography advances the hypothesis that combining the information delivered by multiple radiographic modalities can lead to more constrained (improved) “reconstruction” of the scene than can be obtained from a single probe. We identify four modalities: multi-probe, time sequence, multi-view, and multi-messenger. Multi-probe radiography is a promising candidate for a next-generation dynamic radiographic facility. High-energy X-rays are the most frequently used probe for dynamic radiography, although recent developments show the utility of proton (pRad), electron (eRad), and neutron probe beams. Because each probing species interacts with material in the radiographic scene through quantitatively different mechanisms, each returns independent information about the scene, which can add extra constraints to the reconstruction process. How to conduct detailed, quantitative “co-analysis” of multiple data streams remains an area of active research. Multi-beam, short-pulse, laser-generated probes offer sufficient dose, an appropriate spectrum, and appropriate spatio-temporal resolution to produce high-quality dynamic radiographs. This paper reports on technology development to advance the state of the art of multi-modal/multi-probe radiography and the pursuit of both deterministic and inferential (AI/ML assisted) co-analysis methodologies to produce more constrained reconstructions from multi-modal data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRSDate not supplied

CLDP/ISS Glovebox Technical Interchange Meeting

This presentation is designed to provide a high-level overview of the Microgravity Science Glovebox (MSG) and the Life Sciences Glovebox (LSG) facilities onboard the International Space Station. In addition, it provides metrics and lessons-learned information intended for the Commercial Low-Earth Orbit Development Program (CLDP) Partners.

glovebox↗

DOE OSTI2025

Characterizing and modeling the mechanical behavior of an anion exchange membrane for carbon capture applications

A new direct air capture (DAC) technology uses a moisture swing (MS) process with anion exchange membranes, potentially offering a more energy-efficient way to remove CO₂ from the air. In this MS process, the membrane absorbs CO₂ as it dries and releases it when water is added. Understanding the mechanical behavior of these membranes is essential for improving the design and efficiency of DAC systems and prolonging sorbent lifetime. This study tested one anion exchange membrane, Fumasep’s FAA-3, under mechanical loading and various temperature and humidity conditions to measure its swelling, stiffness, strength, plastic deformation, and stress relaxation. Experimental results were used to identify a mechanical model for FAA-3 that can be used to predict the material’s nonlinear viscous behavior under various loads and environments. Unlike prior studies that assumed linear elastic behavior, this work incorporates humidity-dependent swelling, thermal expansion, and nonlinear viscoelasticity of FAA-3 in both the experiments and the model.

Direct air capture↗