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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Data for Photosynthetic responses to temperature across the tropics: a meta-analytic approach

This data package contains raw data, data output, and code of photosynthetic temperature response curves from tropical forests. Data are used in "Photosynthetic responses to temperature across the tropics: a meta-analytic approach". The research investigates how photosynthetic optimum temperatures and shapes of photosynthetic temperature response curves varies across tropical forest climates and growth conditions. Growth climate variables include mean annual temperature, max and max temperature, diurnal temperature range, and aridity index. Meta-analysis combines 18 datasets with representation from Africa, Oceana, North American, and South America. Growth conditions analyzed considers deciduousness, successional status, light conditions, and whether plants are grown in situ or ex situ. All files, except for the raw datafile (Tropical_MetaAnalysis_Master_3.8.22_Edit.csv), have been processed using R code, which is provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Supporting Data: Inverse Trans Influence and Uranium-Arene σ-Bonding Drive Molecular Geometry: Ligand Modification from Hard to Soft Flips the Oxide from Axial to Equatorial

Supporting Computational Data from the manuscript titled "ITI and Uranium-Arene s-Bonding Drive Molecular Geometry: Ligand Modification from Hard to Soft Flips the Oxide from Axial to Equatorial" by Benedikt Kestel, Daniel Pividori, Sabyasachi Roy Chowdhury, Frank W. Heinemann, Bess Vlaisavljevich, and Karsten Meyer published in J. Am. Chem. Soc. (DOI: 10.1021/jacs.5c05029).

Chowdhury, Sabyasachi Roy [Department of Chemistry↗
DOE OSTI2025

Classical Benchmarks for Variational Quantum Eigensolver Simulations of the Hubbard Model

Simulating the Hubbard model is of great interest to a wide range of applications within condensed matter physics, however its solution on classical computers remains challenging in dimensions larger than one. The relative simplicity of this model, embodied by the sparseness of the Hamiltonian matrix, allows for its efficient implementation on quantum computers, and for its approximate solution using variational algorithms such as the variational quantum eigensolver. While these algorithms have been shown to reproduce the qualitative features of the Hubbard model, their quantitative accuracy in terms of producing true ground state energies and other properties, and the dependence of this accuracy on the system size and interaction strength, the choice of variational ansatz, and the degree of spatial inhomogeneity in the model, remains unknown. Here we present a rigorous classical benchmarking study, demonstrating the potential impact of these factors on the accuracy of the variational solution of the Hubbard model on quantum hardware, for systems with up to 32 qubits. We find that even when using the most accurate wavefunction ansätze for the Hubbard model, the error in its ground state energy and wavefunction plateaus for larger lattices, while stronger electronic correlations magnify this issue. Concurrently, spatially inhomogeneous parameters and the presence of off-site Coulomb interactions only have a small effect on the accuracy of the computed ground state energies. Our study highlights the capabilities and limitations of current approaches for solving the Hubbard model on quantum hardware, and we discuss potential future avenues of research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Forecast of Wildfire Potential Across California USA Using a Transformer

Wildfires are a major issue facing the United States, a matter further exacerbated by an ever-changing climate. In California alone, wildfires are responsible for billions of dollars in damages and take lives each year. Accurately predicting fire danger conditions allows preparation awareness before wildfires start. Transformers are a class of deep learning models designed to identify patterns in sequential datasets. In recent years, transformers have gained popularity through their impressive performance in natural language processing and other applications of signal recognition. This analysis demonstrates the ability of a transformer with a residual connection to forecast fire danger potential over the state of California. Wildland fire potential index (WFPI) maps collected from the US Geological Survey database from January 1st 2020 to December 31st 2023 were used to tune, train and evaluate the transformer. Meteorological inputs (provided by Daymet daily weather and climatological summaries), the normalized difference vegetation index (NDVI) (calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS)), and outputs from the Scott and Burgman fire behavior fuel models (to characterize maps of fuel types), were used as inputs. Our results show that a transformer can effectively emulate the US Forest Service modeled WFPI maps of California USA for four week long forecasts over the month of July, 2023, with correlations ranging from 0.85 – 0.98.

Limber, Russell [ORNL]↗
DOE OSTI2026

N 2 Onet: a global collaborative network facilitating advances in measurement, modeling, and mitigation of agricultural soil nitrous oxide emissions

Nitrogen (N) fertilizer supports global food production, but its use and overuse drive emissions of nitrous oxide (N 2 O), a potent and long-lived greenhouse gas. Understanding the drivers of N 2 O fluxes remains elusive, making it difficult to predict emissions in time and space and to develop and evaluate ways to lower emissions through management. Major scientific uncertainties underlying the understanding of the drivers of N 2 O fluxes identified in a workshop of N 2 O emissions experts include poor process-based understanding of controls on soil N 2 O emissions in the field; insufficient data to reduce uncertainty in N 2 O budgets from the field to regional scales, including N 2 O emission measurements and importantly, field-scale N balances; and high uncertainty in model predictions of soil N 2 O emissions across environmental and management conditions. To reduce these uncertainties, we present the concept of N 2 Onet, a global collaborative initiative to accelerate advances in N 2 O measurement, analyses, and mitigation. N 2 Onet will serve as an observational network of supersites with multi-scale measurements; a database hub for N 2 O flux and ancillary data; and a catalyst for community building, information sharing, and training. By coalescing and coordinating the global community of researchers, N 2 Onet will provide a roadmap for reducing N 2 O emissions from agriculture worldwide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Thermodynamic Profiling Through ASSIST Observations and TROPoe Retrievals

This report reviews the most relevant theoretical aspects of thermodynamic profiling techniques based on spectral observations from ASSIST-II infrared radiometers and TROPoe retrievals. The ASSIST+TROPoe system is a cutting-edge remote sensing technology deployed during the AWAKEN and WFIP3 field campaigns to estimate high-frequency profiles of temperature and humidity in the atmosphere. These profiles are highly valuable for characterizing atmospheric stratification, improving wind models, and understanding the impacts of wind plants on the climate. In this document, we discuss the operating principles of ASSIST, the physics of atmospheric infrared radiation, and the mathematical framework and capabilities of TROPoe. Sources of uncertainties in both the instrument and the retrieval method are also thoroughly addressed. This guide is designed to help users of ASSIST, TROPoe, and thermodynamic data in collecting, estimating, and applying thermodynamic profiles rigorously and scientifically.

17 WIND ENERGY↗
DOE OSTI2020

Comprehensive Land Use and Environmental Stewardship

Comprehensive Land Use and Environmental Stewardship (CLUES) Report serves as a summary document of the land use and environmental stewardship activities occurring on the Idaho National Laboratory (INL) Site (Desert) and the Research and Education Campus (REC) within Idaho Falls. Land and facility use planning and decisions at the INL Site are guided by a comprehensive planning process in accordance with the United States (U.S.) Department of Energy (DOE) Order 430.1C, “Real Property Asset Management,” which states "Establish a data-driven, risk-informed, performance-based approach to the life-cycle management of real property assets that aligns the real property portfolio with DOE mission needs; acquire, manage, positively account for, and dispose of real property assets in a safe, secure, cost-effective, and sustainable manner; and ensure the real property portfolio is appropriately sized, aligned, and in the proper condition to support efficient mission execution." Land use planning, like Campus Master Planning and 5-Year Facility Planning, provides a means for better, more sustainable use of the INL Site in a coordinated effort to ensure current and future mission needs are met, including acquisition, recapitalization, maintenance, disposition, real property utilization and long-term stewardship. This document and all functions of INL are guided by the DOE Vision for INL and the INL Mission and builds on the baseline established in the FY 2015 CLUES Report. However, it delivers a revised structure with focus on new resource management zones, which provide organization of key management considerations and access restrictions to optimize land use and environmental stewardship. A new set of thematic Guiding Principles presented in this report provide the intent and sustainable management direction to protect the INL Site natural environment. They demonstrate that the mission and vision of DOE and INL can be realized with inclusion of first of a kind technology, private sector development, and globally recognized testing and demonstration. This CLUES Report encourages comprehensive management decision-making with additional resource discussions for sustainability, the built environment, and the ecological landscape at the INL Site. Enhanced resource considerations and trends emphasize the importance of air, land use, environmental, subsurface, and cultural resources. The INL Site supports exceptional and interdependent resources. A diversity of bat species are accommodated by culturally significant caves distributed around the Site. Big game species like elk, deer, and moose seek vegetation communities which are protected by long-term stewardship and monitoring programs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Data for "Anti-Pdc1p Nanobody as a Genetically Encoded Inhibitor of Ethanol Production Enables Dual Transcriptional and Post-translational Controls of Yeast Fermentations"

Microbial fermentation provides a sustainable method of producing valuable chemicals. Adding dynamic control to fermentations can significantly improve titers, but most systems rely on transcriptional controls of metabolic enzymes, leaving existing intracellular enzymes unregulated. This limits the ability of transcriptional controls to switch off metabolic pathways, especially when metabolic enzymes have long half-lives. We developed a two-layer transcriptional/post-translational control system for yeast fermentations. Specifically, the system uses blue light to transcriptionally activate the major pyruvate decarboxylase PDC1 , required for cell growth and concomitant ethanol production. Switching to darkness transcriptionally inactivates PDC1 and instead activates the anti-Pdc1p nanobody, NbJRI, to act as a genetically encoded inhibitor of Pdc1p accumulated during the growth phase. This dual transcriptional/post-translational control improves the production of 2,3-BDO and citramalate by up to 100 and 92% compared to using transcriptional controls alone in dynamic two-phase fermentations. This study establishes the NbJRI nanobody as an effective genetically encoded inhibitor of Pdc1p that can enhance the production of pyruvate-derived chemicals.

metabolic engineering↗
DOE OSTI2025

Comparative Economic Analysis Between Bioenergy and Forage Types of Switchgrass for Sustainable Biofuel Feedstock Production: A Data Envelopment Analysis and Cost–Benefit Analysis Approach

ABSTRACT The capacity to produce switchgrass efficiently and cost‐effectively across diverse environments can be pivotal in achieving the short‐ and medium‐term Sustainable Aviation Fuel targets set by the U.S. Department of Energy. This study evaluated the economic performance of forage‐ and bioenergy‐type switchgrass cultivars and their response to N fertilization under diverse marginal environments across the US Midwest that included Illinois (IL), Iowa (IA), Nebraska (NE), and South Dakota (SD). Data Envelopment Analysis (DEA) was used to evaluate the efficiency of 23 Decision‐Making Units (DMUs)—cultivar types and N fertilization rate combinations—while a cost–benefit analysis calculated their profitability over 5 years. Results showed that two energy‐type cultivars—“Independence” and “Liberty”—were superior economically to the forage cultivars. Independence performed best with the highest profit margin when fertilized at 56 kg N ha −1 , particularly in the US hardiness zone 6a (Urbana, IL). Liberty exhibited the highest profit margins in hardiness zone 5b (Madrid, IA, and Ithaca, NE) at 56 kg N ha −1 and showed exceptional profitability with 28 kg N ha −1 in hardiness zone 6b (Brighton, IL). Switchgrass cultivar “Carthage” showed better efficiency score and profitability results in hardiness zone 4b (South Shore, SD) at 56 kg N ha −1 . The profit trends observed in current study sites may indicate broader patterns across similar US hardiness zones. This study provides valuable insights for decision‐makers to optimize input strategies for biomass production of bioenergy switchgrass to meet renewable energy demands.

Arshad, Muhammad Umer [Department of Crop Sciences↗
DOE OSTI2026

Leveraging the redox activities of cerium and dibenzotetrathiafulvalene to discover a photo-responsive magnetic material

Stimuli-responsive changes in lanthanide-based materials are a promising research direction. In this study, [DBTTF] 4 [Ce 2 Cl 10 ] DBTTF = dibenzotetrathiafulvalene (1) was synthesized by a light-induced crystallization, where photo-oxidation of DBTTF enables formation of the cerium dimer [Ce 2 Cl 10 ] 4− . Intermolecular interactions between the stacked organic units of the crystal result in charge transfer bands in the visible-NIR (near-infrared) region, evident in the solid-state absorption spectrum upon comparison with the solution spectrum. The assignments of the sublattice oxidation states were made with single-crystal X-ray diffraction (SC-XRD) structural characterization, Raman spectroscopy, X-ray absorption spectroscopy, and magnetometry. Continuous 532 nm laser irradiation of the microcrystalline solid modulates the redox states in 1, leading to ∼40% reduction in the observed magnetization at 2 K. Density functional theory PBE+U/HSE06 band structure calculations predict Mott insulating behavior in 1, with a bandgap of 0.54/0.81 eV, and further support the conjecture that the observed photo-induced change in magnetization results from electron transfer from the [Ce 2 Cl 10 ] 4− anions to the π-stacked [DBTTF] 2 2+ organic dimer subunits. An enhancement in conductivity is similarly observed upon 532 nm irradiation, determined by single-crystal transport measurements. The findings reveal that photo-responsive lanthanide-based materials can be achieved by integration of redox-active organic moieties with redox-active lanthanide cations for the realization of switchable, photo-magnetic materials.

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

Ultrafast Inverse Chirality-Induced Spin Selectivity Observed by THz Emission

Chirality-induced spin selectivity (CISS) phenomena arise from an interplay among structural chirality, electron spin orientation, and charge current. Steady-state observations such as magnetoresistance offer little insight into the timescales that govern the spin-charge interconversion and often conflate interfacial and bulk phenomena. By contrast, inverse CISS involves the conversion of spin to a charge current. Using terahertz (THz) emission spectroscopy, we directly measured an ultrafast charge current due to inverse CISS with picosecond time resolution. Polarity and polarization analysis of the THz emission map the induced charge current direction upon spin injection. We found that a charge current is generated along the spin orientation that changes direction with stereochemical configuration. These observations directly demonstrate the inherent coupling between spin and charge currents in chiral systems, offering key insights into their fundamental dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Resourceful and economical designing of fermentation medium for lab and commercial strains of yeast from alternative feedstock: ‘transgenic oilcane’

Sugarcane plant engineered to accumulate lipids in its vegetative tissue is being developed as a new bioenergy crop. The new crop would be a source of juice, oil, and cellulosic sugars. However, limited tolerance of industrially recognized yeasts towards inhibitors generated during the processing of lignocellulosic biomass to produce fermentable sugars is a major challenge in developing scalable processes for second-generation drop-in fuel production. To this end, hydrolysates generated from engineered sugarcane—‘oilcane’ bagasse contain added phenolics and fatty acids that further restrict the growth of fermenting microorganisms and necessitate nutrient supplementation and/or detoxification of hydrolysate which makes the fermentation process expensive. Herein, we propose a resourceful and economical approach for growing lab and commercial strains of S. cerevisiae on unrefined cellulosic sugars aerobically and fermentatively.

09 BIOMASS FUELS↗
DOE OSTI2025

In vitro toxicity assessment of uranium particulates on different human lung epithelial cell models

Inhalation of uranium aerosols produced via human activities such as mining can pose a threat to human respiratory systems. Uranium oxide particulates emit short-range alpha particles that elicit DNA and direct damage, beyond associated physiochemical heavy-metal toxicity, to internal epithelial tissues. The availability of reliable in vitro models to study radiation exposure can greatly enhance our ability to understand and combat the biological impacts of exposure. However, the toxicological effects of alpha emissions and/or the oxidation states of uranium particulates vary across different human lung epithelial cell models and have not been systematically compared. We have endeavored to address this limitation by comparing impacts in three different human lung cell models: primary human bronchial and tracheal epithelial cells, primary human small airway epithelial cells, and human adenocarcinoma alveolar basal epithelial cells. Other studies have mainly investigated the toxicity of depleted uranium. Here, we compared the exposure of uranium oxide particulates (U 3 O 8 and UO 3 ) of different enrichment states on the chosen cell systems. Each cell model was exposed to 0.1, 1, 10, 50, 100, and 500 µg/mL of depleted U 3 O 8 , highly-enriched U 3 O 8 , and natural UO 3 particulates for 24 hours in submerged monolayer cultures. We compared viability and superoxide dismutase activity results across cell lines and uranium enrichment/ oxidative states. The results showed that 1) the oxide state of the particulates affected cell viability, implying that uranium’s different oxidation states contribute to different toxicological responses, and 2) each cell model reacts differently when exposed to uranium oxides, which may provide insights into the mechanistic processes associated with the exposure of radiological particulates on different biological systems. For instance, increased uranium enrichment corresponds to increased toxicity for the primary cells, but not for the immortalized cells. Our study shows that a holistic approach that incorporates similarities between model systems and types of radionuclides is required to truly develop empirical solutions for radiation exposure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Comparative Analysis of Two-Wheeled Mobility Options and Suitability for the U.S. Park Police

This report is a framework to help the United States Park Police in selecting and deploying various e-mobility options that are currently available in the market. In the process of creating this framework, we developed the Mobility Optimization and Deployment Engine (MODE) tool whose use could go beyond the scope of this work and mobility options.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

From Depletion to Restoration: Lessons From Long‐Term Monitoring of Carbon Gains and Losses in Cropping Systems

As global atmospheric CO 2 rapidly approaches a key tipping point, there is an urgent need to implement strategies to reverse this pattern. A generally accepted understanding of carbon (C) in agricultural fields includes: (H1) substantial C loss occurs when natural vegetation is converted to crops, (H2) soils typically reach a steady-state C concentration under contemporary practices, and (H3) improved management or crop selection can enhance soil C stocks over time. Significant variability exists, but studies consistently show large C losses from agricultural ecosystems, supporting H1. Although steady-state C levels (H2) are commonly assumed, measuring C gains or losses in mature agroecosystems is challenging. Efforts to increase soil C storage (H3) have limited data due to the diversity of potential practices, compounded by substantial variability in soil C measurements. Here, long-term (7–17 year) ecosystem C flux data from diverse cropping systems revealed that conventionally tilled annual row crops (maize and soybean) act as significant long-term atmospheric C sources, challenging H2. Furthermore, conservation tillage practices reduced C losses compared with conventional tillage but showed minimal evidence for long-term ecosystem C storage, even after 20+ years. This indicates that no-till practices reduce C losses but imply that no soil C is added, challenging H3. By contrast, perennial Miscanthus × giganteus, Panicum virgatum, and restored tallgrass prairie systems store C at the ecosystem scale more effectively than minimally tilled annual row crops. Analysis over multiple years demonstrates significant ecosystem C storage with perennial crops, varying by species, starting in the first year of transition. These findings, although focused on one region, suggest that the assumptions of steady-state C levels and increased storage from conservation practices do not universally apply and that significant changes to agroecosystems are required to increase C storage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Climate Forcing of Bioenergy Feedstocks: Insights From Carbon and Energy Flux Measurements

Bioenergy from biofuels has the potential to slow growing atmospheric carbon dioxide concentrations by reducing fossil fuel use. However, growing bioenergy feedstocks is a land-intensive process. In the United States, the recent expansion of maize bioethanol has presented some environmental costs, prompting the development of several alternative bioenergy feedstocks. These feedstocks, selected in part for traits associated with ecosystem services, may provide opportunities for environmental benefits beyond fossil fuel displacement. We hypothesized that these bioenergy ecosystems will provide direct climatic cooling through their influence on carbon and radiative energy fluxes (i.e., through albedo). To test this hypothesis, we investigated the potential cooling effect of five current or potential bioenergy feedstocks using multi-year records from eddy covariance towers. Perennial feedstocks were carbon sinks, with an annual mean net ecosystem carbon balance (NECB) of –2.7 ± 2.1 Mg C ha –1 for miscanthus, –0.8 ± 1.1 Mg C ha –1 for switchgrass, and –1.4 ± 0.7 Mg C ha –1 for prairie. In contrast, annual rotations were generally carbon sources, with an annual mean NECB of 2.6 ± 2.4 Mg C ha –1 for maize-soy and 3.2 ± 2.1 Mg C ha –1 for sorghum-soy. Using maize-soy as a baseline, conversion to alternative feedstocks increased albedo, inducing further cooling. This effect was strongest for miscanthus, with –3.5 ± 2.0 W m –2 of radiative forcing, and weakest for sorghum, with –1.4 ± 1.4 W m –2 . When feedstock effects on carbon and albedo were compared using carbon equivalents, carbon fluxes were the stronger ecosystem effect, underscoring the role of perennial species as effective carbon sinks. This work highlights the impact of feedstock choice on ecosystem processes as an element of bioenergy land conversion strategies.

09 BIOMASS FUELS↗
DOE OSTI2026

Optimal Methods for Estimating Cactus Pear Biomass Using Cladode Dimensions of Morphologically Diverse Accessions

Current allometric methods for photosynthetic-stem (cladode) plants, such as cactus pear (Opuntia spp.), require refinement to be used in field settings in which diverse accessions are grown. We analysed cladode dimensional data using 14 accessions representing four species and two hybrids to quantify statistically significant morphological differences among accessions and derived cross-accession models to approximate cladode fresh weight. A Box model using cladode dimensions (e.g., length, width, thickness and diameter) and factorial combinations of these measures (e.g., length*width*thickness*diameter vs. fresh weight) resulted in the highest coefficient of determination (R 2 = 0.95 general fit) across all accessions for estimating fresh weight along with parsimony estimates using the Schwarz–Bayes Criterion (SBC), which assesses the most consistent performance on individual accessions. A Fitting-box modelling approach used the measured cladode area captured using ImageJ (R 2 = 0.93 general fit). Lastly, an Elliptical model used an elliptical approximation for the measured area and performed well over all accessions (R 2 = 0.94 general fit) while avoiding extensive manual measurements. These models meet or exceed the performance of previously published approaches when applied across morphologically diverse accessions, providing efficient tools for nondestructive estimation of cactus pear biomass under the conditions tested.

Opuntia↗