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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Target Diagnostic Menu Lawrence Livermore National Laboratory SYSM-5620: Design Thinking and Systems Engineering

Target Diagnostic’s Engineering Science (TDES) currently supports over 80 diagnostic systems, all of which draw from a fixed budget that covers staff time and procurement. As the division continues to add new diagnostics, demand on these limited resources increases, yet the budget remains unchanged. Shot Responsible Individuals (RIs) have unrestricted freedom to select any number or type of diagnostics for each experiment, often by copying previous shot configurations with only minor modifications. This practice makes it easy to generate new shots but does not encourage critical evaluation of diagnostic necessity. As a result, many diagnostics are routinely included in a shot without a clear justification, and in practice, much of the data collected is not analyzed. The ever-growing arsenal of diagnostics also increases the burden on TDES personnel, requiring more staff for support, maintenance, and service. This environment creates challenges in focusing resources on diagnostics that provide the greatest value to the NIF mission and raises concerns about the continued justification for maintaining all existing systems. The static TDES budget cannot sustain the ongoing growth in demand for new diagnostic systems. Shot RIs currently face no constraints on the number or type of diagnostics they assign to each experiment, often defaulting to previous configurations without critically assessing the necessity of each diagnostic. This results in the routine inclusion of diagnostics whose data may not be analyzed or may no longer directly support the NIF mission. Consequently, TDES is required to maintain and support an expanding set of diagnostics, straining limited resources and risking inefficient use of staff and funding. There is a need for TDES to efficiently allocate limited resources by establishing a process that requires shot RIs to critically evaluate and justify the inclusion of each diagnostic in their experiments. This process should discourage the routine, unexamined inclusion of diagnostics, support the identification of underutilized or obsolete systems, and ensure that only those diagnostics providing the greatest value to the NIF mission are maintained and supported. Ultimately, this approach must enable TDES to operate within budget constraints while maximizing scientific impact and operational efficiency.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Intermountain West Energy Sustainability & Transitions Initiative: CO2 Transport and Geologic Storage Modeling Results

These resources provide the full set of cost modeling results and methods as part of the I-WEST Roadmap Initiative that were used to compile figures as part of the "Pathways to CO2 Utilization and Storage for the Intermountain West Region" chapter. The data were generated from a series of National Energy Technology Laboratory (NETL) cost models and relate to carbon dioxide (CO2) transport costs, CO2 enhanced oil recovery (CO2-EOR) economics, and saline storage economics. These models were used to analyze various business cases given changes in technical and financial assumptions for the I-WEST region as a means to explore how these assumptions influence CO2 transport and storage costs, as well as to evaluate the effect of changing oil prices on the viability of CO2-EOR and the mass of CO2 stored via CO2-EOR. The accompanying report titled "Intermountain West Energy Sustainability & Transitions Initiative: CO2 Transport and Geologic Storage Modeling Results" provides a detailed overview on the models, assumptions, and parameters used in the modeling, as well as example results..

CO2 EOR costs,CO2 Storage Costs,CO2 transportation↗
DOE OSTI2022

Supply chain optimization of sustainable aviation fuel from carinata in the Southeastern United States

We report carinata is a purpose-grown oilseed feedstock for renewable fuels, including sustainable aviation fuel (SAF) that can replace conventional aviation fuel (CAF). Given carinata is a new crop in the Southeastern United States, it is crucial to analyze its sustainability from a supply chain perspective. This study developed a mixed-integer linear programming (MILP) model and simulated it for 20 years, starting from a farm (county-level data) and ending at the airport. About 2.06 million ha in Alabama, Florida, and Georgia combined were found suitable for carinata production. Given the three-year rotation period, about 0.69 million hectares can be cultivated annually, approximately 65% of which was in Georgia. About 2.4% of the combined SAF annual demand of four major airports (about 210 thousand t) in the study area is satisfied at that level of carinata cultivation. However, all available SAF was supplied to the Atlanta airport as this decision minimizes the supply chain cost. A total of 1343 storage units, one oil extraction mill, and one biorefinery were needed to meet the overall demand. We found that SW Georgia is the top supplier of carinata seeds. The unit cost of production and carbon intensity were estimated to be $\$$0.89 L -1 (or $\$$26.79 GJ -1 ) and 0.91 kg CO 2 e L -1 (or 27.28 kg CO 2 e GJ -1 ), respectively. This carbon intensity of carinata-based SAF was 67.8% lower than that of CAF. With variations included in SAF demand, yield, and soil carbon sequestration, carbon savings remained between 66.5% and 67.8%. Given the GHG advantage of SAF over CAF, there is justification for subsidies required to make SAF competitive.

10 SYNTHETIC FUELS↗
DOE OSTI2023

Plant Cell Biology International Meeting 2022

There is a strong need to develop the knowledge base that will enable the rational design of improved crop species for sustainable agriculture and biomass production. To attain this goal, researchers must learn how plant cells integrate metabolism and cellular dynamics during growth and in response to environmental challenges. Meeting these goals require data sharing and the development and training of faculty, post-doctoral fellows, graduate and undergraduate students in state-of-the-art quantitative integrative cell biology methods. The inaugural Plant Cell Biology International (PCBI) meeting capitalized on the interaction between two well-established plant cell biology communities across the Atlantic, the Midwest Plant Cell Dynamics (PCD) and the European Network for Plant Endomembrane Research (ENPER) and provided a framework to meet these goals. The conference took place in person successfully during August 1-5th 2022 in Crete, Greece. The conference offered opportunities for undergraduate and graduate students, postdocs, young investigators across the globe to present their results and interact across different disciplines. The conference provided an open and inclusive forum for oral presentations that allowed all labs to share research results. It was attended over 80 % by students, postdocs and young investigators. Workshops on best practices for image acquisition and processing pipelines, publication guidelines by scientific journal editors, professional development and well-being benefited the participants at large. Overall, this was the inaugural joint Plant Cell Biology International conference that for the first time officially brought together plant cell biologists to discuss opportunities and challenges in the field to gain a mechanistic understanding of complex biological processes and advance sustainable agriculture. Due to its success, it was rescheduled for 2025 in Crete, to continue strengthening the plant cell biology community and exchanging knowledge and expertise across the globe.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Wastewater reuse benefits for municipal complete retention lagoons: Life cycle assessment and dynamic modeling

Complete retention lagoons with wastewater reuse for agricultural purposes may offer sustainability advantages over alternative systems for small communities in semiarid regions. This study quantifies the environmental life cycle impact of adopting agriculture water reuse systems using case study data to estimate operating and building infrastructure impacts and spatial–temporal modeling to quantify resource trade-offs. Water reuse system benefits are highly dependent on supply–storage–demand dynamics. The relative size of irrigated agricultural land to the lagoon size was the most significant factor influencing site water application rates. The benefits are sensitive to changes in air emissions occurring from the agricultural land and further emphasize the importance of proper fertilizer management when adopting water reuse systems. Wastewater reuse from complete retention lagoons reduce life cycle GHG emissions, primarily through excavation reductions, offset fertilizer use, and especially from increased crop yields from wastewater reuse at previously rainfed sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

De-Risking High-Recovery Brackish Water Desalination via Flow Reversal and Feed Flushing Using Techno-Economic Assessment

Novel desalination technologies have demonstrated enhanced performance and improved financial metrics over existing processes adopted by industry. Establishing quantitative performance targets is essential for achieving financial benefits over the current state of the art. Herein, we demonstrate how WaterTAP, a techno-economic assessment (TEA) tool, can be used to identify minimum performance metrics necessary to achieve financial benefit over using existing processes. This study evaluates the feasibility of increasing water recovery at the Chino Desalter I above 90 % through the addition of a third variable configuration reverse osmosis (VCRO) stage. Sensitivity analyses revealed flow reversal frequency, feed flushing volume (used as a cleaning step), and membrane lifespan are key factors influencing the financial viability of the VCRO process. The TEA analysis demonstrated that the system must achieve a recovery of 84 % and a 1-year membrane lifespan to have a breakeven LCOW, while achieving 90 % recovery can ultimately reduce the LCOW by 16 %. Notably, a trade-off between decreasing frictional losses and increased osmotic pressure across the recovery range, resulted in a stable specific energy consumption across the recovery range, enabling meaningful LCOW reductions without an energy penalty, a key finding that contrasts with conventional RO. This work demonstrates how TEA can guide system design by identifying key performance targets and exploring trade-offs, enabling data-driven decisions to de-risk innovative processes. These findings underscore the importance of leveraging TEA to evaluate scaling mitigation strategies and optimize inland desalination systems for sustainable and cost-effective operation.

14 SOLAR ENERGY↗
DOE OSTI2026

Cracking the code of multi-layer films to promote circularity in single-use plastic packaging

Multi-layer film packaging (MLF) revolutionized food preservation by combining diverse material layers to optimize barrier properties, mechanical strength, and shelf-life. These materials are essential for transporting perishables across various climates and allow for access to fresh goods in “food deserts”, but they pose significant recycling challenges due to their structural complexity. This perspective examines key structure-property relationships governing barrier performance and highlights innovations in material design. We explore how machine learning can predict performance metrics and propose recyclable alternatives, integrating data-driven approaches with material science insights. By challenging the status quo of MLF design, we advocate for circularity in food packaging, inspiring innovation at the intersection of sustainability, material science, and artificial intelligence.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantification of early nonpharmaceutical interventions aimed at slowing transmission of Coronavirus Disease 2019 in the Navajo Nation and surrounding states (Arizona, Colorado, New Mexico, and Utah)

During an early period of the Coronavirus Disease 2019 (COVID-19) pandemic, the Navajo Nation, much like New York City, experienced a relatively high rate of disease transmission. Yet, between January and October 2020, it experienced only a single period of growth in new COVID-19 cases, which ended when cases peaked in May 2020. The daily number of new cases slowly decayed in the summer of 2020 until late September 2020. In contrast, the surrounding states of Arizona, Colorado, New Mexico, and Utah all experienced at least two periods of growth in the same time frame, with second surges beginning in late May to early June. Here, we investigated these differences in disease transmission dynamics with the objective of quantifying the contributions of non-pharmaceutical interventions (NPIs) (e.g., behaviors that limit disease transmission). We considered a compartmental model accounting for distinct periods of NPIs to analyze the epidemic in each of the five regions. We used Bayesian inference to estimate region-specific model parameters from regional surveillance data (daily reports of new COVID-19 cases) and to quantify uncertainty in parameter estimates and model predictions. Our results suggest that NPIs in the Navajo Nation were sustained over the period of interest, whereas in the surrounding states, NPIs were relaxed, which allowed for subsequent surges in cases. Our region-specific model parameterizations allow us to quantify the impacts of NPIs on disease incidence in the regions of interest.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Addendum to water resource assessment in the New Mexico Permian Basin

There are an estimated 48,745 wells producing oil or gas in New Mexico as of August 8, 2020 and with advances in drilling and oil recovery technology the use of hydraulic fracturing has become more commonplace. With a typical well requiring 1.5 to 16 million gallons of water, there is an increased demand for water in the Permian Basin and concern over the regions ability to meet this demand. This report is an addendum to the 2018 report Water Resource Assessment in the New Mexico Permian Basin (SAND2018-12018) to monitor baseline water level and chemistry data established in the original report. Results from this addendum can be used to further understand regional water supply and demands and aid in the BLMs mission of sustainably meeting the needs of water users while protecting human and environmental health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Green Computing Catalyzer Kickoff: Green Artificial Intelligence (AI) Directions

For the 2022 JISEA annual meeting, JISEA introduces in this presentation the new Green Computing Catalyzer. The new catalyzer looks to establish green computing as a salient research domain at NREL, and crucially, to begin to address the looming computing energy crisis. The presentation provides some basic numbers, establishing energy use and source or carbon emissions for computing. The presentation also includes a brief history of green computing at NREL, empirical deep learning efficiency study, and research directions.

AI efficiency↗
DOE OSTI2022

The USAID-NREL Partnership

The United States Agency for International Development is drawing on U.S. Department of Energy national laboratory expertise to advance clean, resilient, and equitable energy systems in the developing world through the USAID-NREL Partnership.

advanced power systems↗
DOE OSTI2025

Tool-Based Case Studies on Strategic Deployment of Untapped Micro-Pumped Hydro Storage in Michigan

With most classical hydropower sites already utilized and the global push for rapid integration of renewable energy sources accelerating, there is a critical need to identify alternative energy storage solutions. Pumped hydro energy storage, which accounts for the vast majority of global grid-scale storage, remains one of the most cost-effective and long-duration storage technologies available. Hence, this study presents a novel tool designed to assess the untapped potential of inland lakes and reservoirs for micro-PSH, using Michigan’s relatively flat landscape as a case study due to its extensive but underutilized water infrastructure. To ensure accuracy and reliability, the tool incorporates extensive data gathered from authorized sources, covering more than 420 water facilities and potential reservoirs in the state. The tool evaluates key parameters such as horizontal and vertical distances, volume, and the total storage capacity of each reservoir. Its robust assessment framework integrates these metrics to evaluate each site’s potential. The tool’s intuitive interface and geospatial visualizations support actionable insights for planners and scalable deployment of distributed storage infrastructure.

13 HYDRO ENERGY↗
DOE OSTI2023

HydroGEN and H2NEW Data Hub

HydroGEN is a multi-lab consortium focused on early-stage R&D in H2 production, supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), Hydrogen and Fuel Cell Technologies Office (HFTO). The consortium advances research and development (R&D) of innovative materials for advanced water splitting (AWS) technologies to enable clean, sustainable and low-cost ($1/kg H2) hydrogen production and fosters cross-cutting innovation using theory-guided applied materials R&D to advance all emerging water-splitting pathways for hydrogen production. Hydrogen from Next-generation Electrolyzers of Water (H2NEW) is a consortium of nine U.S. Department of Energy (DOE) national laboratories focused on making large-scale electrolyzers, which produce hydrogen from electricity and water, more durable, efficient, and affordable. The presentation introduces the HydroGEN data hub to the H2NEW consortium and encourages H2NEW members to use it to store and share data with team members and eventually the public. The two consortia share this data hub.

advanced water splitting technologies↗
DOE OSTI2023

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics

We seek to transform how new and emergent variants of pandemic-causing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can learn the evolutionary landscape of SARS-CoV-2 genomes. By pre-training on over 110 million prokaryotic gene sequences and fine-tuning a SARS-CoV-2-specific model on 1.5 million genomes, we show that GenSLMs can accurately and rapidly identify variants of concern. Thus, to our knowledge, GenSLMs represents one of the first whole-genome scale foundation models which can generalize to other prediction tasks. We demonstrate scaling of GenSLMs on GPU-based supercomputers and AI-hardware accelerators utilizing 1.63 Zettaflops in training runs with a sustained performance of 121 PFLOPS in mixed precision and peak of 850 PFLOPS. We present initial scientific insights from examining GenSLMs in tracking evolutionary dynamics of SARS-CoV-2, paving the path to realizing this on large biological data.

Zvyagin, Maxim↗
DOE OSTI2021

Annual productivity and lipid composition of native microalgae (Chlorophyta) at a pilot production facility in Southern California

Microalgae are an efficient platform for the sustainable production of foods, fuels, and bioproducts. Due to the vast natural diversity of microalgae, choosing an ideal species for production can be challenging, and laboratory-derived productivity data may be misleading. In the present study, nine species of green algae (Chlorophyta) were isolated directly from an outdoor pilot production facility, identified via sequencing and microscopy, cultured under standard laboratory conditions to assess lipid content, and then cultivated in 80-L cultures in a greenhouse over the course of a year to assess productivity. Analysis of lipid content from laboratory-grown cultures revealed that these strains had high concentrations of C16 and C18 fatty acids and lipid content not exceeding 30% of dry weight during growth phase. In the greenhouse, Parachlorella kessleri-SD23 had the highest annual productivity, yielding an annual average of approximately 19 g/m 2 /d and 88 mg/L/d of biomass productivity. Furthermore, P. kessleri-SD23 had a total lipid content equal to about 19% of dry weight during growth phase under laboratory conditions with the highest concentration of C18:2 and C18:3 fatty acids among the isolates.

09 BIOMASS FUELS↗
DOE OSTI2024

Techno-economic and life-cycle analysis of strategies for improving operability and biomass quality in catalytic fast pyrolysis of forest residues

Many of the challenges faced by the first commercial biorefineries were associated with feedstock handling, quality, and cost. Strategies are needed to enable further expansion of biorefineries and meet the growing demand for bio-based fuels and products. Here, we examine 2 key feedstock challenges and mitigation strategies in the context of a catalytic fast pyrolysis (CFP) biorefinery: (1) the operability of the feed system, which may be improved by modifying the minimum particle size fed to the reactor, and (2) the quality of the biomass, which may be improved by employing air classification to remove undesirable material and increase fuel yields. We conduct techno-economic analysis (TEA) and life-cycle analysis for these strategies, employing a discrete event simulation model for biomass preprocessing combined with a series of correlations developed from literature data and a rigorous CFP conversion model. Our results highlight the importance of balancing increased cost and material losses from preprocessing against improved operability and fuel yields. Economics and sustainability were optimized when operating at the lowest minimum particle size, emphasizing the importance of minimizing material losses while maintaining the operability of the process. Economically, additional costs and material losses from air classification could be acceptable due to improved biomass conversion, and an optimum air classification speed was identified; however, the fuel GHG emissions were minimized when air classification was not used. Valorizing material removed during preprocessing as a coproduct could improve economics and sustainability, decreasing the burden of material losses.

09 - BIOMASS FUELS↗
DOE OSTI2026

Phenogenomics reveals the ecology and evolution of Trichoderma fungi for sustainable agriculture

Trichoderma fungi support sustainable agriculture by suppressing plant diseases and improving crop performance. However, emerging pathogenicity of Trichoderma warrants further ecological and genetic characterization. Here we used machine learning to correlate genomic data from 37 Trichoderma strains with over 140 phenotypic traits, spanning metabolic versatility, biotic interactions, stress tolerance and reproductive strategies. We determined Trichoderma to be an ancient, genetically cohesive and physiologically diverse genus with spores capable of germination in water and dispersal via air and water droplets. Metabolic preferences indicate universal adaptation to mycoparasitism and to niches like arboreal microbial mats, alongside broader saprotrophic versatility. Our analyses are consistent with character displacement among close relatives and convergent evolution in distant lineages, with both processes shaping ecological plasticity and traits including dispersal modes, terrestrialization or endophytism. Our findings reveal that while some Trichoderma species show traits of biosafety concern, its vast ecophysiological diversity enables the development of safe, targeted bioeffectors.

Steindorff, Andrei S. [USDOE Joint Genome Institut↗
DOE OSTI2025

AmeriFlux US-IAB Iowa State University NE tower

This is the AmeriFlux version of the carbon flux data for the site US-IAB Iowa State University NE tower. Site Description - This is a 4 ha (200 m x 200 m) crop rotation established at the Sustainable Advanced Bioeconomy Research (SABR) farm at Iowa State University. The site has a long history of conventional row-cropping, predominantly corn-soy rotations. In the immediately preceding growing season, soybeans were grown at the SABR farm.

(Rojda), Guler Aslan Sungur↗