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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Elucidating lipid nanoparticle properties and structure through biophysical analyses

Designing lipid nanoparticle (LNP) delivery systems with specific targeting, potency and minimal side effects is crucial for their clinical use. However, traditional characterization methods, such as dynamic light scattering, cannot accurately quantify physicochemical properties of LNPs and how these are influenced by the lipid composition and mixing method. Here, we structurally characterize polydisperse LNP formulations by applying emerging solution-based biophysical methods that have higher resolution and provide biophysical data beyond size and polydispersity. These techniques include sedimentation velocity analytical ultracentrifugation, field-flow fractionation followed by multiangle light scattering and size-exclusion chromatography in line with synchrotron small-angle X-ray scattering. Here, we show that LNPs have intrinsic polydispersity in size, RNA loading and shape, which depend on both the formulation technique and the lipid composition. Lastly, we predict LNP transfection in vitro and in vivo by examining the relationship between mRNA translation and physicochemical characteristics. Solution-based biophysical methods will be essential for determining LNP structure–function relationships, facilitating the creation of new design rules for LNPs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Three-dimensional high-content imaging of unstained soft tissue with subcellular resolution using a laboratory-based X-ray microscope

With increasing interest in studying biological systems across spatial scales—from centimeters down to nanometers—histology continues to be the gold standard for tissue imaging at cellular resolution, providing an essential bridge between macroscopic and nanoscopic analysis. However, its inherently destructive and two-dimensional nature limits its ability to capture the full three-dimensional complexity of tissue architecture. Here, we show that phase-contrast X-ray microscopy can enable three-dimensional virtual histology with subcellular resolution. This technique provides direct quantification of electron density without restrictive assumptions, allowing for direct characterization of cellular nuclei in a standard laboratory setting. By combining high spatial resolution and soft tissue contrast, with automated segmentation of cell nuclei, we demonstrated virtual Hematoxylin and Eosin (H&E) staining using machine learning-based style transfer, yielding volumetric datasets compatible with existing histopathological analysis tools. Furthermore, by integrating electron density and the sensitivity to nanometric features of the dark field contrast channel, we achieve stain-free, high-content imaging capable of distinguishing nuclei and extracellular matrix.

3D virtual histology↗
DOE OSTI2025

First multi-institutional systematic comparison of the neutron ambient dose equivalent produced by proton therapy systems

Objective. Isochronous cyclotrons, synchrocyclotrons, and synchrotrons are used to accelerate protons for proton therapy. An accurate measurement of neutron doses generated by these accelerators and associated delivery systems and its clinical relevance requires systematic protocols and proper neutron dosimetry for a meaningful assessment. We present the first comprehensive comparison of neutron ambient dose equivalent (H*(10)) produced by clinically operational proton therapy systems. Approach. Treatment plans with 10 cm modulation-depth and ranges of 10 cm (R10M10) and 25 cm (R25M10) were created to cover a 10 × 10 × 10 cm 3 water target. The pencil beam scanning proton therapy machines studied were: two gantry-mounted synchrocyclotrons (Hyperscan, Mevion, half-gantry), two isochronous cyclotrons (ProBeam, Varian, full-gantry), one isochronous cyclotron (Proteus, IBA, full-gantry), and two synchrotrons (PROBEAT, Hitachi, full- and half-gantry). Proton beams were delivered to 30 × 30 × 40 cm 3 plastic water phantoms. WENDI-II and LUPIN-BF3-NP neutron rem-meters were positioned at three angles (0°, 45°, 90°) relative to the beam direction to measure the neutron H*(10) at distances between 50–300 cm from the isocenter. Main results. H*(10) showed dependence on beam energy, machine type, and measurement location. The highest reading was for the gantry-mounted synchrocyclotron, whereas other systems produced approximately comparable neutron doses. In all cases, the H*(10) reduced with distance from the isocenter. The H*(10) drop at 2 m distance compared to that at 0.5 m was a factor of ∼5 for the gantry-mounted synchrocyclotron whereas in other systems the decrease was a factor of 10. The WENDI-II device suffered from dead-time-associated under-estimation of the dose by a factor of ∼2–3 under the synchrocyclotron beam due to its high dose-per-pulse. However, WENDI-II and LUPIN-BF3-NP results were within reasonable agreement in isochronous cyclotron and synchrotron beams, indicating that both devices are suitable for those systems. Significance. Neutron H*(10) is dependent on various parameters including beam energy, measurement location, as well as machine design. Caution must be exercised in choosing the appropriate neutron-dose-measurement device to be used for low-duty-factor, particularly in high-instantaneous-rate proton delivery systems. By delivering the same volumetric proton dose across different machines, this work provides a benchmark for inter-system comparisons and serves as a foundation for future studies.

LUPIN↗
DOE OSTI2024

Development and Outcomes of Returning Polycyclic Aromatic Hydrocarbon Exposure Results in the Washington Heights, NYC Community

Report-back of research results (RBRR) is becoming standard practice for environmental health research studies. RBRR is thought to increase environmental health literacy (EHL), although standardized measurements are limited. For this study, we developed a report back document on exposure to air pollutants, Polycyclic Aromatic Hydrocarbons, during pregnancy through community engaged research and evaluated whether the report increased EHL. We used focus groups and surveys to gather feedback on the report document from an initial group of study participants (Group 1, n = 22) and then sent the revised report to a larger number of participants (Group 2, n = 168). We conducted focus groups among participants in Group 1 and discussed their suggested changes to the report and how those changes could be implemented. Participants in focus groups demonstrated multiple levels of EHL. While participant engagement critically informed report development, a survey comparing feedback from Group 1 (initial report) and Group 2 (revised report) did not show a significant difference in the ease of reading the report or knowledge gained about air pollutants. We acknowledge that our approach was limited by a lack of EHL tools that assess knowledge and behavior change, and a reliance on quantitative methodologies. Future approaches that merge qualitative and quantitative methodologies to evaluate RBRR and methodologies for assessing RBRR materials and subsequent changes in knowledge, attitudes, and behavior, may be necessary.

Children’s Environmental Health↗
DOE OSTI2020

The Evolving U.S. Distribution System: Technologies, Architectures, and Regulations for Realizing a Transactive Energy Marketplace

As pockets of the U.S. experience growing penetrations of distributed energy resources (DERs), the traditional practices underpinning distribution system regulation, operation, and management are evolving. The challenges and opportunities that DERs pose are driving stakeholders across the United States to reconsider regulatory goals, utility business models, ratemaking, and grid architectures. This report reviews the evolution of the U.S. distribution system from the advent of the utility-as-regulated-monopoly business model to the technological and regulatory shifts happening. The report concludes with a discussion of transactive energy systems and summarizes some of the leading RD&D happening in this field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Pathways for Tamil Nadu’s Electric Power Sector: 2020 - 2030

This report is part one of a two-part series that represents a year-long collaboration with the Tamil Nadu Generation and Distribution Corporation Limited (TANGEDCO) and Tamil Nadu Transmission Corporation Limited (TANTRANSCO) on power sector planning. This Pathways for Tamil Nadu’s Electric Power Sector 2020-2030 report outlines NREL’s work with TANGEDCO's electricity sector planning department to develop a model of the State power system and evaluate multiple scenarios of system evolution given resource constraints, costs of technologies, and power sector policies. A broad stakeholder group comprised of TANGEDCO leadership, developers, regulators, and researchers from within the power sector community in Tamil Nadu helped to guide the main objectives of the study and provided technical feedback to the research team. The outcomes of this effort include multiple pathways for power sector growth to 2030 and a robust model of Tamil Nadu's power system that can be used to continually analyze the impact of new policies, regulations, or system changes. The second report in this series will build on the bulk system analysis by focusing on the rapidly transforming distribution network in the State. The report will outline a framework developed by NREL and TANGEDCO's distribution utility to quickly and accurately analyze the impacts of integrating renewable energy onto Tamil Nadu's distribution system. Together these studies help to prepare Tamil Nadu for a rapidly transforming power system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

An Analysis Framework for Distribution Network DER Integration Analysis in India: Distributed Solar in Tamil Nadu

This report is part of a two-part series that represents a year-long collaboration with the Tamil Nadu Generation and Distribution Corporation Limited (TANGEDCO) on power sector planning. The first report in this series, the Pathways for Tamil Nadu’s Electric Power Sector 2017-2030 report outlines NREL’s work with TANGEDCO's electricity sector planning department to develop a model of the State’s power system and evaluate multiple scenarios of system growth given resource constraints, costs of technologies, and power sector policies. This second report in this series focuses on the rapidly transforming distribution network in the State. The report outlines a framework developed by NREL with TANGEDCO's distribution utility to quickly and accurately analyze the impacts of integrating renewable energy, specifically rooftop solar PV onto Tamil Nadu's distribution system. Together these studies help to prepare Tamil Nadu for a rapidly transforming power system.

14 SOLAR ENERGY↗
DOE OSTI2022

Opportunities for Hybrid Wind and Solar PV Plants in India

The share of variable renewable energy (VRE) on India's grid has surpassed 100 GW, and the government has ambitious plans reach 450 GW by 2030. One strategy to increase wind and solar PV deployment is through the co-location of wind and solar PV plants to form a single hybrid power plant. Hybrid plants have the potential to reduce transmission infrastructure costs and variability in the output power profile compared to a standalone plant with a single technology, and this resource analysis aims to take a first step towards quantifying the potential savings from hybridizing wind and solar PV plants in India and the size of this opportunity. We utilize a brute-force optimization to minimize the levelized cost of energy (LCOE) for standalone wind, standalone solar PV, and hybrid wind/solar PV plants across all of India. By comparing these LCOEs, we determine that locations where hybrid plants exhibit potential cost savings and grid benefits exhibit both; a high interconnection cost and; a wind capacity factor between roughly 34% and 38%. However, because our work does not capture the value of the electricity generated by looking at energy prices, nor does it quantify the potential of hybrids to provide other value streams such as firm capacity and reserves. Further, because the work does not compare solar PV and wind hybrids to alternative generation technologies or storage systems, it cannot be considered a holistic cost-benefit analysis.

14 SOLAR ENERGY↗
DOE OSTI2022

Role of Renewable Energy, Storage, and Demand Response in Karnataka's Power Sector Future

Karnataka ranks fourth among Indian states in installed capacity of renewable energy, which accounts for over 50% of its resource mix. The state is positioned to play a leading role in India's energy transition and contribute to meeting national targets for renewable energy thanks, in part, to ambitious state goals to develop Karnataka's abundant zero carbon energy resources and plans to phase out new investments in thermal plants. Power system stakeholders in Karnataka are faced with the challenge of planning a generation portfolio that accounts for the variability of wind and solar resources, meets increasing and shifting electricity demand, and satisfies operational and reliability requirements. The objective of this study is to evaluate least-cost pathways for Karnataka's electric power system through 2050. The capacity expansion model developed for this study identifies power system investment and operational decisions for every year (2020-2050) for all of India, with detailed representation of the state of Karnataka. The study led to five high-level results and provides a framework for recurring planning studies to meet changing system conditions and needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Opportunities for Renewable Energy, Storage, Vehicle Electrification, and Demand Response in Rajasthan's Power Sector

To support the government of Rajasthan and inform state policy makers, regulators, planners, and system operators on power system trends, NREL undertook a long-term capacity expansion planning study. We used NREL's flagship capacity expansion planning tool for the power sector called the Regional Energy Deployment System India (ReEDS-India) to understand the generation and transmission needs of Rajasthan through 2050. NREL's modeling framework includes co-optimized decisions about generation, energy storage, transmission, and reserves investments needed to meet future demand while maintaining reliable electricity supply. Scenario analysis was conducted to assess a range of potential future scenarios, providing insight for planning agencies, utilities, and local stakeholders about key trends and sources of uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Impacts of Renewable Energy and Green Hydrogen Policies on Uttar Pradesh's Power Sector Future

This report is part of a broader program focused on supporting Indian states with long-term power system planning. More information about this program can be found at the National Renewable Energy Laboratory's "Supporting India's States With Renewable Energy Integration" web page at https://www.nrel.gov/international/india-renewable-energy-integration.html. The power sector in Uttar Pradesh, India's most populous state, is poised to transform over the next few decades due to a combination of national and state-level policies impacting both the supply and demand of electricity. The Government of Uttar Pradesh has policies and plans to develop in-state solar PV, pumped storage hydropower, and green hydrogen. Power system policymakers and utilities in Uttar Pradesh are faced with the challenges of planning a system that incorporates increasing amounts of renewable energy and storage resources, meets rising electricity demand due to economic development and green hydrogen production, and satisfies operational and reliability requirements. To support these various objectives, the National Renewable Energy Laboratory (NREL), RMI, and the Uttar Pradesh New and Renewable Energy Development Agency (UPNEDA) evaluated the least-cost pathways for the state's power sector through 2050. NREL developed a capacity expansion model that identifies investment and operational decisions for every year (2024-2050) for all of India, with detailed representation for the state of Uttar Pradesh, which can provide a framework for recurring planning studies. The main insights from this study can also help inform policy development and investment decisions.

08 HYDROGEN↗
DOE OSTI2024

Impacts of Renewable Energy and Green Hydrogen Policies on Uttar Pradesh's Power Sector Future: Additional Modeling Scenarios to Explore Hydrogen Flexibility [Slides]

This slide deck is part of a broader program focused on supporting Indian states with long-term power system planning. More information about this program can be found at the National Renewable Energy Laboratory's "Supporting India's States With Renewable Energy Integration" web page at https://www.nrel.gov/international/india-renewable-energy-integration.html. The power sector in Uttar Pradesh, India's most populous state, is poised to transform over the next few decades due to a combination of national and state-level policies impacting both the supply and demand of electricity. The Government of Uttar Pradesh has policies and plans to develop in-state solar PV, pumped storage hydropower, and green hydrogen. Power system policymakers and utilities in Uttar Pradesh are faced with the challenges of planning a system that incorporates increasing amounts of renewable energy and storage resources, meets rising electricity demand due to economic development and green hydrogen production, and satisfies operational and reliability requirements. To support these various objectives, the National Renewable Energy Laboratory (NREL), RMI, and the Uttar Pradesh New and Renewable Energy Development Agency (UPNEDA) evaluated the least-cost pathways for the state's power sector through 2050. NREL developed a capacity expansion model that identifies investment and operational decisions for every year (2024-2050) for all of India, with detailed representation for the state of Uttar Pradesh, which can provide a framework for recurring planning studies. The purpose of this slide deck is to supplement the main study (published in May 2024) with additional modeling scenarios to explore hydrogen flexibility.

08 HYDROGEN↗
DOE OSTI2026

Optimizing resource allocation in Miscanthus breeding via sparse testing designs for genomic prediction

Phenotyping high-biomass perennial crops is laborious and the rate of genetic gain in conventional perennial crop breeding programs is typically low. So, it is especially important to identify methods that produce efficiency gains in the breeding process. Miscanthus is a C4 perennial grass with favorable characteristics for producing biomass as a feedstock for biofuels and diverse bio-based products. Increasing biomass yield will increase profitability and environmental benefits, so it is a key target for Miscanthus breeding. In addition, the identification of well-adapted genotypes across a wide range of environmental conditions requires the establishment of multi-environment trials (METs). Sparse testing is a genomic prediction-based strategy that reduces the phenotyping costs in METs by selecting a subset of genotypes to evaluate in a subset of environments and then predicts the performance of the unobserved genotype-environment combinations. A Miscanthus sacchariflorus (MSA) population comprising 336 genotypes observed across three environments was analyzed implementing sparse testing designs. Three prediction models considering main effects (environments, genotypes, genomic) and interaction effects (genotype-by-environment; G×E interaction) were implemented for forecasting dry biomass yield (YDY), total culm (TCM), average internode length (AIL), and culm node number (CNN). Multiple calibration sets based on different compositions and sizes were considered to evaluate performance in terms of the predictive ability (PA) and the mean square error (MSE) for a fixed testing set size. The training set size ranged from 52 to 112 to predict a fixed set of 224 unobserved genotypes across all three environments. The results showed that the model accounting for G×E interaction consistently presented the highest PA and the lowest MSE: for CNN (PA: ~0.77, MSE: ~0.5) and YDY (PA: ~0.70, MSE: ~1.3) while for TCM and AIL these ranged from ~0.28 to 0.41 and ~1.3 to 4.3, respectively. Overall, varying training sets and allocation strategies did not affect PA and MSE, with 52 non-overlapping and 0 overlapping genotypes per environment as the optimal cost-effective allocation framework. This suggests that implementing sparse testing designs could significantly reduce phenotyping costs by fivefold, without compromising PA in breeding programs for perennial crops such as Miscanthus.

Miscanthus sacchariflorus (MSA)↗
DOE OSTI2026

Multi-trait multi-environment genomic prediction strategies for Miscanthus sacchariflorus

Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (G×E×T) and (2) two single-trait multi-environment (STME) models (with and without G×E interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.

genomic prediction (GP)↗
DOE OSTI2021

Long-Term Planning for the Tamil Nadu Power System

Increased deployment of wind and solar raises new questions for power system planners regarding the future mix of generation technologies, optimal siting of generation capacity, trade-offs between generation and transmission investments, and system flexibility needs. The National Renewable Energy Laboratory (NREL) is working with Tamil Nadu Generation and Distribution Company (TANGEDCO) to answer the following questions: How much—and what type—of generation and transmission investments are needed to serve future demand at least cost? How can variable resources such as wind and solar be considered in the planning process? What are the key drivers (e.g., policies, technology costs, fuel constraints) for investments?

Children's Investment Fund Foundation↗
DOE OSTI2021

Power System Planning: Advancements in Capacity Expansion Modeling

This fact sheet focuses specifically on one element of the long-term planning process, the capacity expansion model. It highlights the key advances in these models to enable planning for systems with growing shared of renewable energy and storage.

capacity expansion model↗