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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Considerations for Introducing Artificial Intelligence into Nuclear Power Plants

Advanced computational tools and techniques such as artificial intelligence and machine learning (AI/ML) can transform the nuclear power industry. This is necessary given that the economic viability of the existing fleet is in jeopardy and its labor-centric approach to operations and maintenance. Currently, AI/ML research is being undertaken for reactor system design and analysis including fault and accident prognosis, nuclear risk analysis such as plant safety and security evaluation, and plant operations and maintenance including predictive maintenance. Applications include both existing and advanced reactor technologies with the aim of improving operational and business efficiencies. Most every aspect of the organization can benefit, from instrumentation and control, to work planning, to human-machine interactions and business management. AI/ML in nuclear can simplify complex problems and produce more effective decision-making. Nonetheless, careful consideration must be given to the implementation of an AI/ML initiative. The aims of this research are to 1) review barriers to AI/ML adoption within the nuclear power industry, and 2) suggest potential solutions. These barriers are organized along five distinct categories (Figure 1) that are interconnected. The first are historical barriers that track the industry’s development over the decades including worldwide nuclear events that shaped public perceptions. The resulting federal scrutiny and intense safety culture that emerged are discussed. Technical barriers to AI/ML adoption are considerable, and include data privacy concerns, data governance, and the current lack of AI/ML expert knowledge at the plants. The main business case barrier remains cost, but an absence of an industry-wide vision and wide-scale adoption also produces reluctance. Stakeholder readiness is reviewed with special attention given to regulatory readiness. The 5-year strategic plan for AI readiness recently published by the U.S. Nuclear Regulatory Commission is highlighted. Last, adoption barriers at the user level are addressed including the importance of user experience and explainable AI. The AI adoption barriers described here are inter-related and ideally should be addressed in a holistic fashion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Co-Catalyst Enabled Biotransformation of Polyunsaturated Fatty Acids for Biobased Monomers

Enzymatic lipid epoxidation offers a promising approach to obtain renewable intermediates for biomaterials, but regiochemical control of these reactions has remained elusive. Here we report the discovery and application of artificial cocatalysts to direct the regioselectivity of catalytic epoxidation with the lipase CpLIP2. The methyl esters of alkyl dicarboxylic acids show the unique ability to direct regioselective epoxidation of polyunsaturated fatty acids, major components of plant and algae-based oils. We apply this transformation to the conversion of linoleic acid into sebacic acid, a dicarboxylic acid precursor valuable for biobased polyester polyurethanes, through a six-step pathway involving a regioselective Meinwald rearrangement. To highlight the route’s significance, sebacic acid was used to prepare a 100% biobased thermoplastic polyurethane, illustrating the relevance of this pathway to industrial applications. Furthermore, this regioselective chemoenzymatic oxidation and rearrangement process can be used to access multiple dicarboxylic acids that have remained previously unexplored as biobased monomers.

09 BIOMASS FUELS↗
DOE OSTI2025

POWER ELECTRONICS GRID TIED SYSTEM FINAL REPORT

Across the country, electric utilities are grappling with the persistent hurdles of integrating Distributed Energy Resources (DERs). Managing these assets safely and effectively is a complex endeavor, complicated by varying ownership structures, management philosophies, and the diversity of the technologies themselves. Consequently, the industry has seen a proliferation of bespoke system designs, control strategies, and communication frameworks—forcing utilities to spend significant time and resources developing one-off integration solutions. This project addressed these integration hurdles through a scalable demonstration of intelligent devices designed to coordinate and control diverse resources in low-voltage applications. This concept minimized the need for complex integration by transforming the separate DERs into a dispatchable virtual power plant (VPP) with integrated resiliency functions (called a Node). By collaborating with a utility partner, the project focused on developing rapidly implementable use cases that bridged the gap between theoretical control and real-world deployment

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1989

Life support systems research at the Johnson Space Center

The bioregenerative life support systems research at Johnson Space Center focuses on the use of lunar regolith as a plant growth medium. Current dissolution experiments are being conducted to ascertain the response of lunar regolith to various solvents and weathering environments. The transformation of lunar minerals into minerals such as zeolites which would be more conducive to plant growth is also investigated. A study is currently underway to examine the ability of zeolite/apatite mixtures to provide N, P, and K through dissolution and ion exchange. The development and characterization of simulated lunar regolith for preliminary experimentation are also discussed. The life support systems technology used on the Mercury, Gemini, Apollo, and Shuttle missions is reviewed and current research on regenerative life support systems technology for potential use in Space Station Freedom is discussed.

Henninger, D. L.↗
DOE OSTI2026

Machine learning enables reconstruction of past fire regimes from charcoal-derived fire intensity and fuel composition

Background Fire is a foundational ecological process that shapes ecosystem structure, diversity, and resilience. Quantifying paleofire regime attributes such as frequency, severity, and intensity is essential for understanding the historical range of variability in fire behavior and its ecological effects. While frequency and severity are often reconstructed in paleofire studies, quantitative reconstructions of fire intensity remain limited. Recent work has shown that maximum pyrolysis temperature—a proxy for fire intensity—and plant species type can be inferred from charcoal using transmission Fourier-transform infrared (FTIR) spectroscopy. However, the sample preparation for transmission FTIR is destructive and time-consuming, limiting application and reuse of materials for other analyses. We evaluated reflectance FTIR spectroscopy as a non-destructive alternative for reconstructing combustion temperature and plant species from laboratory-generated charcoal. We also examined the influence of contrasting airflow environments (ambient air versus nitrogen-rich) on pyrolysis temperature and plant species reconstruction prediction accuracies and compared predictive performance between a novel, neural network–based deep learning model with the traditional modern analogue technique (MAT) using k-nearest neighbor functions. As proof of concept, we apply our enhanced methodology to ancient charcoal to demonstrate applicability at improving long-term fire regime reconstructions and the ability to link paleofire records with contemporary fire ecology. Results Our analysis shows that transmission and reflectance FTIR spectra yield comparable spectral profiles. However, sample preparation for reflectance FTIR is minimal and non-destructive, unlike transmission FTIR which is destructive. We demonstrate that oxygen environments improved reconstruction accuracy relative to nitrogen-rich conditions. Finally, our deep learning neural network (DL) achieved testing accuracies of 98.7% for temperature and 96.2% for species identification, outperforming MAT’s k-NN approach (89.8% and 65.9%, respectively). A Shapley importance analysis identified 5 key spectral regions that greatly influenced the model’s temperature or species categorization. When applied to ancient charcoal, our results show historic fires from the most recent past primarily burned at low intensities (400–500 °C), reflective of natural fire regimes in ponderosa pine forests. Our results corroborate charcoal morphology data that suggests all ancient charcoal originated from burned woody plant types. Conclusions By combining reflectance FTIR spectroscopy with a deep learning approach, we provide the first accuracies high enough to confidently identify both species and temperature from laboratory-produced charcoal, improving quantitative reconstructions of fire intensity and fuel composition from paleofire records. This opens a wide range of research into the link between fire and larger drivers (i.e., climate or human) and greater ecological understanding of fire regimes beyond that of burn scars or recent observations. These methodological improvements have direct relevance for fire management by improving interpretation of historical fire behavior, informing fuel–fire relationships, and providing a scalable analytical framework applicable to both long-term ecological studies and contemporary fire science.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Loss of Glen Canyon Dam Hydropower Plant Capabilities

The power grid in the western United States is undergoing a major transformation, driven by technological advancements, power markets, policy shifts, and evolving energy demands. The integration of variable renewable energy (VRE) resources, such as wind and solar, into the power grid has become a major driver of change. Between 2018 and 2023, about 19 gigawatts (GW) of new solar capacity and 14 GW of new wind capacity was built in the Western Interconnection (WI) region. These two VRE resources accounted for the majority of WI capacity additions. The Western Interconnection is expected to host 30 GW of wind, 40 GW of solar, and 14 GW of energy storage by 2030 (Western Electricity Coordinating Council n.d.).

13 HYDRO ENERGY↗
DOE OSTI2026

Single-cell and spatial omics in plants: from cellular atlases to regulatory mechanisms

Single-cell RNA sequencing (scRNA-seq) has transformed transcriptomic studies by enabling gene expression profiling at the resolution of individual cells within and across a broad range of tissue types, revealing cellular heterogeneity that is obscured in bulk tissue transcriptomes. Over the past decade, improvements in microfluidics and library preparation have drastically increased throughput, allowing tens of thousands of cells to be assayed in a single experiment. Although initially developed in animal systems, scRNA-seq has rapidly emerged as a powerful and widely adopted approach in plant biology. Beyond transcriptomics, the integration of single-cell data with chromatin accessibility, proteomics, metabolomics, and spatial omics is enabling a system-level understanding of plant gene regulation and cellular organization. Network-based analytical frameworks further support the reconstruction of gene regulatory networks and the interpretation of complex single-cell data. In this review, we summarize the current technological landscape of plant single-cell studies, discuss key experimental and analytical challenges, and review emerging strategies for validating single-cell discoveries. We also discuss future directions in applying single-cell technologies to woody perennials plants and bioenergy-relevant crops, emphasizing their potential to accelerate the discovery of cell type-specific regulatory mechanisms underlying growth, stress resilience, and biomass production.

Li, Miaomiao [ORNL] (ORCID:0000000321326168)↗
DOE OSTI2025

Phylogenomic discovery and engineering of nitrogen fixation into the bioenergy woody crop poplar

Biological nitrogen fixation (BNF) is a key process enabling plants in specific lineages to convert atmospheric dinitrogen (N₂) into bioavailable ammonia through symbioses with diazotrophic microbes. Expanding this capability beyond native nitrogen-fixing clades into non-nodulating crops would reduce synthetic fertilizer use, lowering energy inputs and environmental impacts in agriculture. Supported by DOE Funding Award DE-SC0018247, the NitFix project advanced foundational knowledge required to engineer root-nodule symbioses in new host species. The team generated the most comprehensive phylogenomic analysis to date of all known nodulating lineages, resolving the evolutionary history of nitrogen-fixing symbiosis and identifying core gene suites retained across nodulating taxa. Through multimodal genomics, transcriptomics, and functional analyses in Medicago truncatula and related species, the project mapped regulatory networks underlying nodule organogenesis, bacterial infection, and nitrogen-fixation efficiency. Key discoveries include the identification of conserved signaling modules for rhizobial recognition, transcription factors controlling nodule differentiation, and metabolic pathways integrating fixed nitrogen into plant growth. The project also developed enabling tools—including optimized transformation pipelines, gene-editing workflows, and imaging-based phenotyping—to accelerate engineering efforts in emerging models. Together, these results refine the mechanistic framework of symbiotic nitrogen fixation and highlight transferable components essential for rewiring these traits into non-nodulating crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Project 1: COLLECTS Project and Project 2: M&V for Saputo Cheese Project: Cooperative Research and Development (Final Report)

Project 1: Combined Power's Hyperlight Energy and NLR will collaborate on the DOE Concentrating Optics for Lower Levelized Energy CosTS (COLLECTS) project, DE-FOA-0001268. COLLECTS funding opportunity announcement (FOA) seeks to further concentrated solar power (CSP) system technologies by soliciting disruptive, transformative projects for the concentrating solar collectors in the CSP plant. These innovative projects will seek to surpass the targets set out in the SunShot Vision Study, enabling CSP to be cost-competitive with conventional forms of electric power generation. Projects will target the design and manufacturing of novel solar collectors with the ability to significantly reduce the solar field contribution to the overall levelized cost of energy (LCOE) of the CSP plant, and which have not been previously specifically targeted by CSP FOAs. Project 2: Hyperlight will perform measurement and verification (M&V) of Green House Gases and NLR will evaluate energy consumption reduction.

14 SOLAR ENERGY↗
NASA NTRS1986

Wet-oxidation waste management system for CELSS

A wet oxidation system will be useful in the Closed Ecological Life Support System (CELSS) as a facility to treat organic wastes and to redistribute inorganic compounds and elements. However at rather higher temperatures needed in this reaction, for instance, at 260 deg C, only 80% of organic in a raw material can be oxidized, and 20% of it will remain in the liquid mainly as acetic acid, which is virtually noncombustible. Furthermore, nitrogen is transformed to ammonium ions which normally cannot be absorbed by plants. To resolve these problems, it becomes necessary to use catalysts. Noble metals such as Ru, Rh and so on have proved to be partially effective as these catalysts. That is, oxidation does not occur completely, and the unexpected denitrification, instead of the expected nitrification, occurs. So, it is essential to develop the catalysts which are able to realize the complete oxidation and the nitrification.

Takahashi, Y.↗
NASA NTRS1994

The H(sub infinity) optimal controller design and reduction for the inertial hold mode of the attitude control system of the XTE spacecraft

The Inertial Hold Mode (IHM) is one mode of the attitude control system of the X-ray Timing Explorer spacecraft that is disturbed by both parametric uncertainties and external torque disturbance. The IHM model is modified into a typical H-infinity mixed-sensitivity problem through choosing suitable weighting functions W(sub 1)(s) and W(sub 3)(s). The controller is designed by the H-infinity optimization technique with the transformation of shifting the imaginary axis. It can stabilize the plant with uncertainties from the natural frequencies of the flexible body. The gain margin and phase margin of the system are 24.03 db and 55.04 deg, respectively. The step response attenuates to zero within 150 seconds. These show that the controller satisfies the specified requirements. Since the order of the controller appears high, it is reduced to fourth order one. The results show that the stability and the performance of the system with the reduced controller are retained perfectly.

Xu, Zhong Ling↗
NASA NTRS1995

Multijunction InGaAs thermophotovoltaic power converter

The experimental performance of a multijunction monolithic In(0.53)Ga(0. 47)As power converter under blackbody irradiation is reported. Eight InGaAs PN junctions grown epitaxially on a semi-insulating wafer were monolithically integrated in series to boost the approximately 0.4 V photovoltage per typical InGaAs junction to over 3 volts for the 1 sq cm chip. This chip was originally designed and characterized for free-space 1.3 micron laser power beaming. This is the first report of such a multijunction TPV. This is not a traditional tandem cell in which the junctions are stacked vertically. The junctions are each about 1mm long by 1 cm wide and are laterally connected across the 1 sq cm device area. This multijunction design has the potential for lower I(sup 2)R power loss since the smaller PN junction area limits the current to one-eighth that of the equivalent surface area. In essence, the current is traded for voltage to avoid the I(sup 2)R loss, analogous to the way power utilities avoid I(sup 2)P loss in high-tension power lines, by transforming the high current, low voltage generated at a power plant into a high voltage at a low current before transmitting the power over great distances.

Wojtczuk, Steven↗
NASA NTRS1996

Multijunction InGaAs thermophotovoltaic power converter

The experimental performance of a multijunction monolithic lattice-matched 0.74 eV InGaAs thermophotovoltaic (TPV) power converter under 980 C blackbody irradiation is reported. Eight InGaAs PN junctions grown epitaxially on a semi-insulating wafer were monolithically integrated in series to boost the approximately 0.4 V photovoltage per typical InGaAs junction to over 3 volts for the 1 cm(exp 2) chip. This chip was originally designed and characterized for free-space 1.3 micron laser power beaming. The power efficiency of this TPV device is 16% for that part of the blackbody spectrum above the material bandgap. The device is shown to deliver about 1 watt of output power when driven with enough light. This is the first report of such a multijunction TPV device. This is not a traditional tandem cell in which the junctions are stacked vertically. Eight 1 mm long by 1 cm wide junctions are laterally connected across the device area. This multijunction design has the potential for lower I(exp 2)R power loss since the smaller PN junction area limits the current to one eighth that of the equivalent surface area. In essence, the current is traded for voltage to avoid the I(exp 2)R loss, analogous to the way power utilities avoid I(exp 2)R loss in high-tension power lines, by transforming the high current, low voltage generated at a power plant into a high voltage at a low current before transmitting the power over great distances.

Wojtczuk, Steven↗
NASA NTRS1995

A Globally Optimal Minimax Solution for Spectral Overbounding and Factorization

In this paper, an algorithm is introduced to find a minimum phase transfer function of specified order whose magnitude "tightly" overbounds a specified real-valued nonparametric function of frequency. This method has direct application to transforming nonparametric uncertainty bounds (available from system identification experiments and/or plant modeling) into parametric representations required for modern robust control design software (i.e., a minimum-phase transfer function multiplied by a norm-bounded perturbation).

Scheid, Robert E.↗
NASA NTRS2016

Satellite Estimation of Fractional Cover in Several California Specialty Crops

Past research in California and elsewhere has revealed strong relationships between satellite NDVI, photosynthetically active vegetation fraction (Fc), and crop evapotranspiration (ETc). Estimation of ETc can support efficiency of irrigation practice, which enhances water security and may mitigate nitrate leaching. The U.C. Cooperative Extension previously developed the CropManage (CM) web application for evaluation of crop water requirement and irrigation scheduling for several high-value specialty crops. CM currently uses empirical equations to predict daily Fc as a function of crop type, planting date and expected harvest date. The Fc prediction is transformed to fraction of reference ET and combined with reference data from the California Irrigation Management Information System to estimate daily ETc. In the current study, atmospherically-corrected Landsat NDVI data were compared with in-situ Fc estimates on several crops in the Salinas Valley during 2011-2014. The satellite data were observed on day of ground collection or were linearly interpolated across no more than an 8-day revisit period. Results will be presented for lettuce, spinach, celery, broccoli, cauliflower, cabbage, peppers, and strawberry. An application programming interface (API) allows CM and other clients to automatically retrieve NDVI and associated data from NASA's Satellite Irrigation Management Support (SIMS) web service. The SIMS API allows for queries both by individual points or user-defined polygons, and provides data for individual days or annual timeseries. Updates to the CM web app will convert these NDVI data to Fc on a crop-specific basis. The satellite observations are expected to play a support role in Salinas Valley, and may eventually serve as a primary data source as CM is extended to crop systems or regions where Fc is less predictable.

satellite↗
NASA NTRS1990

CELSS research and development program

Research in Controlled Ecological Life Support Systems (CELSS) conducted by NASA indicate that plant based systems are feasible candidates for human support in space. Ames has responsibility for research and development, systems integration and control, and space flight experiment portions of the CELSS program. Important areas for development of new methods and technologies are biomass production, waste processing, water purification, air revitalization, and food processing. For the plant system, the approach was to identify the flexibility and response time for the food, water, and oxygen production, and carbon dioxide consumption processes. Tremendous increases in productivity, compared with terrestrial agriculture, were realized. Waste processing research emphasizes recycle (transformation) of human wastes, trash, and inedible biomass to forms usable as inputs to the plant production system. Efforts to improve efficiency of the plant system, select new CELSS crops for a balanced diet, and initiate closed system research with the Crop Growth Research Chambers continue. The System Control and Integration program goal is to insure orchestrated system operation of the biological, physical, and chemical operation of the biological, physical, and chemical component processors of the CELSS. Space flight studies are planned to verify adequate operation of the system in reduced gravity or microgravity environments.

Bubenheim, David↗
DOE OSTI2024

The Mobility of Mo during Microbially Mediated Ferrihydrite Phase Transformation

Molybdenum (Mo) is an essential nutrient for almost all organisms. However, at high concentrations, it can be toxic to animals and plants. This study investigated the interactions of Mo(VI) with iron oxyhydroxides during ferrihydrite bioreduction in the presence of the Fe(III)- reducing Geobacter sulfurreducens. Here, in this study, we showed that Mo concentration controlled ferrihydrite phase transformation, leading to Mo release. With the biotic reduction of ferrihydrite and Fe(II) production, Mo(VI) reduction and Mo(IV)O 2 formation were observed for the first time, which further immobilised Mo after surface adsorption of Mo(VI). At low Mo levels (Mo/Fe molar ratios of 1-2 %), sufficient Fe(II) adsorption onto ferrihydrite resulted in its transformation into magnetite nanoparticles (>80%, ~25 nm) which catalysed the reduction of Mo(VI) to form Mo(IV)O 2 and immobilised Mo. Contrastingly, at high Mo concentrations (Mo/Fe molar ratios of 5-10%), Mo(VI)O 4 2- adsorption onto ferrihydrite limited Fe(II) adsorption, subsequently less magnetite (<8-12%) formed while more goethite (~30- 50%, width & length > 15 & 100 nm, respectively) and siderite (~20-30%, width & length > 100 & 200 nm, respectively) with larger particle sizes formed instead, causing Mo(VI) release due to lower Mo adsorption. This study provides a comprehensive understanding of the interaction mechanisms among Geobacter sulfurreducens, Mo(VI), and iron oxyhydroxides, enabling predictions and controls of long-term Mo mobility and Fe mineral transformation under a variety of biogeochemical scenarios.

Geobacter sulfurreducens↗