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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Sharing the Sun: Community Solar Deployment and Subscriptions (As of January 2026)

The community solar market analysis presented here is based primarily on data collected through Sharing the Sun, an initiative of the National Community Solar Partnership+ (NCSP+). Sharing the Sun data collection and analysis are conducted by the National Laboratory of the Rockies (NLR) as part of its support for implementation of NCSP+. NLR first released a dataset of community solar projects in 2018 and updates it biannually. The January 2026 dataset, data collection methodology, and all the previous datasets are available from NLR's Data Catalog: https://data.nlr.gov/submissions/244. The dataset presents project-level information including location, capacity, operating utility, and year of interconnection. The dataset is created from multiple data sources such as utility data, public utility commissions, project developer websites, media releases, primary data collection by NLR, and data provided by developers under nondisclosure agreements. This presentation builds on a previous analysis of the community solar project dataset, Sharing the Sun: Community Solar Deployment and Subscriptions (as of June 2024). Dr. Gabriel Chan and his team at the University of Minnesota contribute to this effort. NCSP+ is led and funded by U.S. Department of Energy's Integrated Energy Systems Office (IESO).

14 SOLAR ENERGY↗
DOE OSTI2025

Standardizing UI/UX across accelerator labs

During February 26–28, 2025, the first-ever particle accelerator user interface/user experience (UI/UX) workshop was held at SLAC. Attendees had backgrounds ranging from software development to control systems management and human factors (HF) science. The workshop began with participants discussing the current state of UI/UX procedures and practices at their respective laboratories to share experiences and learn from one another. Additional discussions focused on how to effectively integrate UI/UX best practices into actionable goals for developers, managers, and operators when working on new or existing interfaces. The goal of the working group is to create a website that will guide developers, managers, scientists, and end users at accelerator laboratories in incorporating UI/UX best practices into software development. The working group continues to meet virtually toward this goal, and is planning a second workshop for next year.

Tran, Tiffany [SLAC]↗
DOE OSTI2026

Alternative Fuels Data Center

This presentation provides an overview of the Alternative Fuels Data Center for the 2026 Transportation Technologies Annual Merit Review, including project objectives, milestone, approach to developing and maintaining the website, project accomplishments and progress, and collaboration with other national labs and external partners.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Educational Consortium for Energy-related Data Science & Computation in Building Engineering Programs

The project spearheaded by Pennsylvania State University aims to address the growing need for integrating energy-focused computation and data science into building engineering education. As the demand for energy-efficient building designs and operations increases, the educational sector must adapt to equip future engineers with the necessary skills. This initiative responds to this need by developing a consortium that unites multiple institutions to enhance curriculum development, dataset curation, and resource sharing, thereby ensuring students are well-prepared for the evolving energy sector. The primary goal of the project is to establish a consortium that will develop and disseminate educational materials and training programs focused on energy-related data science and computation. Key accomplishments include the creation of a beta website for resource sharing, the development of training programs and standalone modules, and the curation of datasets accessible to the public. This effort will culminate in a curriculum that incorporates advanced modeling technologies and data science skills into building engineering programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Laboratory Directed Research and Development Program: FY 2024 Completed Projects Report

Oak Ridge National Laboratory (ORNL) is the US Department of Energy’s (DOE’s) largest multiprogram science, technology, and energy laboratory. It possesses distinctive capabilities in a variety of fields, such as neutron science, computing, advanced materials, and nuclear science and technology. Using these capabilities, ORNL conducts basic and applied research and development (R&D) to support DOE’s overarching mission “to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.” As a national resource, ORNL also applies its capabilities and skills to the specific needs of other federal agencies and customers through the DOE Strategic Partnership Projects (SPP) Program. Information about the laboratory and its programs is available on the ORNL website. The Laboratory Directed Research and Development (LDRD) Program at ORNL operates under the authority of DOE Order 413.2C, Laboratory Directed Research and Development,3 which establishes DOE’s requirements for the program while providing the laboratory director broad flexibility for program implementation. The LDRD Program funds are obtained through a charge to all laboratory programs. Although it represents a relatively small portion of the overall research budget, the LDRD Program plays an essential role in maintaining the laboratory’s ability to respond to national needs. The program allows ORNL to improve its distinctive capabilities and to enhance its ability to conduct cutting-edge R&D. In accordance with the DOE order, R&D projects funded through the LDRD Program at ORNL support the goals of • maintaining the scientific and technical vitality of the laboratory; • enhancing the laboratory’s ability to address future DOE missions; • fostering creativity and stimulating exploration of forefront areas of science and technology; • serving as a proving ground for new concepts in R&D; and • supporting high-risk, potentially high-value R&D. This report provides an overview of the LDRD Program at ORNL in FY 2024 and contains summaries of all the LDRD research projects that concluded between October 1, 2023, and September 30, 2024.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Laboratory Directed Research and Development Program: FY 2025 Completed Projects

Oak Ridge National Laboratory (ORNL) is the US Department of Energy’s (DOE’s) largest multiprogram science, technology, and energy laboratory. It possesses distinctive capabilities in a variety of fields, such as neutron science, computing, advanced materials, and nuclear science and technology. Using these capabilities, ORNL conducts basic and applied research and development (R&D) to support DOE’s overarching mission “to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.” As a national resource, ORNL also applies its capabilities and skills to the specific needs of other federal agencies and customers through the DOE Strategic Partnership Projects (SPP) Program. Information about the laboratory and its programs is available on the ORNL website. The Laboratory Directed Research and Development (LDRD) Program at ORNL operates under the authority of DOE Order 413.2C, Laboratory Directed Research and Development, which establishes DOE’s requirements for the program while providing the laboratory director broad flexibility for program implementation. The LDRD Program funds are obtained through a charge to all laboratory programs. Although it represents a relatively small portion of the overall research budget, the LDRD Program plays an essential role in maintaining the laboratory’s ability to respond to national needs. The program allows ORNL to improve its distinctive capabilities and enhance its ability to conduct cutting-edge R&D. In accordance with the DOE order, R&D projects funded through the LDRD Program at ORNL support the goals of • maintaining the scientific and technical vitality of the laboratory, • enhancing the laboratory’s ability to address future DOE missions, • fostering creativity and stimulating exploration of forefront areas of science and technology, • serving as a proving ground for new concepts in R&D, and • supporting high-risk, potentially high-value R&D. This report provides an overview of the LDRD Program at ORNL in FY 2025 and contains summaries of all the LDRD research projects that concluded between October 1, 2024, and September 30, 2025.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Pioneer WEC Dashboard

SAND2026-18911O The Pioneer WEC (Wave Energy Converter) Dashboard tool visualizes real-time data from the Pioneer WEC v1 prototype, which supplies power to a mooring in the Coastal Pioneer Array. It offers up-to-date information, performance metrics, and graphical plots that enable users to monitor the prototype's efficiency. Developed using Python and Jekyll, this static website is updated daily and hosted on GitHub. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Michelen Strofer, Carlos [Sandia National Lab. (SN↗
DOE OSTI2024

Cross Section Evaluation for Exclusive Channels of K+Λ and K+Σ0 Electroproduction off Protons Using CLAS Detector Data

In this work, a method for evaluating the cross sections of electroproduction of K+Λ0 and K+Σ0 off protons in the region of invariant masses of final hadrons MK + MY <W < 2.65 GeV (MK and MY being the masses of the kaon and hyperon, respectively) and squares of four-momentum transfers of virtual photons, i.e., photon virtualities 0 < Q2 < 5 GeV2, is developed based on experimental data of these exclusive channels’ cross sections measured by the CLAS detector in Hall B at Jefferson Lab. A set of algorithms has been implemented to evaluate the differential cross sections of these channels, along with their statistical and systematic uncertainties. A program was developed for the evaluation of differential cross sections and structure functions using C++ and Python libraries. An interactive website was created for working with the program, enabling the analysis of one-dimensional and two-dimensional dependences of structure functions and differential cross sections. The evaluation of differential cross sections for the K+Λ and K+Σ0 electroproduction channels is necessary for extracting the structure function σLT from the data on the polarization asymmetry of electroproduction reactions of these final states with longitudinally polarized electrons. The obtained results are also important for the development of realistic Monte Carlo event generators in planning future experiments and for evaluating the efficiency of detecting final particles when extracting reaction cross sections from experimental data.

Golda, A. V.↗
DOE OSTI2024

PV Performance Modeling and Stakeholder Engagement (Final Technical Report)

This core capability project’s objective is to increase the value of photovoltaic (PV) performance models by improving their functionality, demonstrating, and quantifying their validity, and offering a wide range of stakeholder engagement opportunities. In FY22-24, we developed new and improved modeling algorithms and functions to represent PV performance more accurately in a variety of environments and conditions. The “Model parameter toolkit” was developed and includes functions to translate between different module temperature models, incidence angle modifier models, and single-diode models. A new modeling capability named “PV Atlas” was also developed leveraging Sandia’s High Performance Computing resources. This capability allows us to investigate several questions and provide climate-specific best practices and geographic data files; all these are hosted on an interactive website on Sandia’s GitHub and can be used for training, system optimization, or to provide best practices for uncertainty reduction. For model validation, we published high-quality PV performance, and weather data; these data are well documented, filtered, and processed for quality and include examples on how to run PV simulations. We also developed well documented, standardized methods for validating PV models and ran independent model validation and 2 blind modeling intercomparisons engaging with 49 organizations from 17 countries. We co-led and contributed to a growing, well documented and maintained suite of open-source functions for PV modeling (i.e., the pvlib-python) and we outreached to the PV modeling stakeholders via the PVPMC workshops and web resources. In addition, this project supported US representation and leadership for the International Energy Agency (IEA) PVPS Task 13; specifically, members of our team led and supported 3 subtasks on: 1) Best practices for the optimization of bifacial photovoltaic tracking, 2) Extreme weather events and their multiple impact on PV power plants: Risks, failure mechanisms and mitigation strategies, and 3) Best practice guidelines for the use of economic and technical Key Performance Indicators (KPIs). This project resulted in the publications of 14 peer reviewed journal papers, 37 conference presentations, 6 SAND reports, 5 public datasets and 6 new webpages on the PVPMC website. It supported the release of 13 pvlib-python versions where 28 enhancements were from this PV Performance Modeling project. We co-organized 5 PVPMC workshops in FY22-24 with the participation of 214 unique institutions and around 700 participants. The PVPMC website was redesigned, and its reliability was improved; it receives over 50,000 visitors/year from 202 unique countries.

14 SOLAR ENERGY↗
DOE OSTI2024

Curating Carbon Storage Data for Reuse: Enabling Research and Modeling from Earth’s Surface to Subsurface

The volume of public geologic carbon storage (GCS) data resources has continued to increase in recent years as the result of an increase in funding from government, industry, and academia towards national, basin, regional and field scale studies to ensure carbon capture and storage becomes a commercially viable operation. Despite the increasing volume of data, GCS data applied towards analyses such as geologic, cost, and risk modeling continues to be multi-sourced and often disparate in nature, published across government agencies, websites, data repositories and buried in derivative reports and documents. Much of the time preparing for an analysis and derivative product development is spent collecting, aggregating, transforming and preparing input data. There have been significant efforts within the DOE National Energy Technology Laboratory’s Carbon Storage Program to optimize multi-source, multi-scale subsurface geologic data curation and aggregation to support data discovery, interoperability, and reuse. Methods include the use of artificial intelligence, machine learning, and data science techniques. This talk will discuss the workflows, best practices, and processes developed to support the aggregation and curation of data through the whole system – surface to subsurface data - that support multi-scale, multi-purpose analysis for carbon storage research.

Morkner, Paige↗
DOE OSTI2025

Bioenergy Research Centers Data Sharing Portal

The bioenergy.org website is the end product of the Data Sharing Shared Research objective for the Bioenergy Centers. The objective is to Enhance BRC data legacy through the development and use of shared software tools to make previously published datasets more findable and accessible through the Inter-BRC Data Products Portal, and to explore the use of generative AI to assist in the exploration of published datasets. The software repository is released per the license information below.

Thrower, Nicholas↗
DOE OSTI2024

Development of learning objectives to support undergraduate virology curriculum guidelines

It has become increasingly important for microbiology educators to help students learn critical concepts of the discipline. This is particularly true in virology, where current challenges include increasing rates of vaccine hesitancy, misinformation about the COVID-19 pandemic, and controversy surrounding research on pathogens with pandemic potential. Having students learn virology can attract more people to the field and increase the number of people who can engage in meaningful discourse about issues relating to the discipline. However, the limited number of virologists who teach undergraduates, combined with the fact that many institutions lack stand-alone virology courses, results in virology often being taught as a limited number of lectures within an undergraduate microbiology course (if it is covered at all), which may or may not be taught by an individual trained as a virologist. To provide a framework to teach virology to undergraduate students, a team of virology educators, with support from the American Society for Virology (ASV), developed curriculum guidelines for use in a stand-alone undergraduate virology course or a virology section within another course. These guidelines are available at the ASV website (https://asv.org/curriculum-guidelines/). To assist educators in implementing these guidelines, we created examples of measurable learning objectives. This perspective provides details about the virology curriculum guidelines and learning objectives and accompanies the perspective by Boury et al. in this issue of the Journal of Microbiology & Biology Education about the recent revision of the microbiology curriculum guidelines overseen by the American Society for Microbiology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

BindingDB in 2024: a FAIR knowledgebase of protein-small molecule binding data

Abstract BindingDB (bindingdb.org) is a public, web-accessible database of experimentally measured binding affinities between small molecules and proteins, which supports diverse applications including medicinal chemistry, biochemical pathway annotation, training of artificial intelligence models and computational chemistry methods development. This update reports significant growth and enhancements since our last review in 2016. Of note, the database now contains 2.9 million binding measurements spanning 1.3 million compounds and thousands of protein targets. This growth is largely attributable to our unique focus on curating data from US patents, which has yielded a substantial influx of novel binding data. Recent improvements include a remake of the website following responsive web design principles, enhanced search and filtering capabilities, new data download options and webservices and establishment of a long-term data archive replicated across dispersed sites. We also discuss BindingDB’s positioning relative to related resources, its open data sharing policies, insights gleaned from the dataset and plans for future growth and development.

Liu, Tiqing↗
DOE OSTI2025

Resource Characterization for Community Scale Tidal Instream Energy in Maine [Abstract]

Coastal and island communities in Maine are seeking solutions to increase the resiliency of their electrical grid while also reducing their carbon footprint. Unfortunately, many community scale tidal resources identified on the Maine coast have not been rigorously evaluated; previous studies identified numerous hot spots but left many of them unevaluated or under evaluated (e.g., only power density was assessed in many cases). The primary objective of this TEAMER project is to evaluate selected community scale tidal instream resources to demonstrate their potential for contributing to the renewable energy needs of nearby coastal communities. The methods developed in this study will enable the total community scale tidal instream energy resource along the Maine coast to be evaluated in follow-on studies. The study will also enable turbine developers to understand how to scale and optimize their devices for deployment in turbine farms at community scale sites. Data from the study will be shared publicly through MHKDR or relevant community websites.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

2022 Kauai Ground Transportation Survey

# 2022 Kauai Ground Transportation Survey The 2022 Kauai Ground Transportation Survey was designed to improve understanding of the transportation preferences of residents and visitors of the Hawaiian island of Kauai. For residents of Kauai, the survey focused on mode-choice decisions for commute, leisure, and shopping activities and whether they would consider using alternative modes instead of driving if such options were available. For visitors, the survey focused on whether they would consider alternatives to rental cars if such options were available. Ultimately, survey results will inform the development of sustainable transportation strategies for the island. ## Data Collection Agency NREL and the Kauai Office of Economic Development conducted the study as part of the U.S. Department of Energy's Energy Transitions Initiative Partnership Project. ## Survey Methodology The survey was conducted July—October 2022. Respondents were recruited via direct email invitation, a press release on the Kauai County website and Facebook page, and posters at community outreach events. ## Survey Records, Data, and Documentation Survey records include 1,437 participants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Kauai Ground Transportation Survey

# 2022 Kauai Ground Transportation Survey The 2022 Kauai Ground Transportation Survey was designed to improve understanding of the transportation preferences of residents and visitors of the Hawaiian island of Kauai. For residents of Kauai, the survey focused on mode-choice decisions for commute, leisure, and shopping activities and whether they would consider using alternative modes instead of driving if such options were available. For visitors, the survey focused on whether they would consider alternatives to rental cars if such options were available. Ultimately, survey results will inform the development of sustainable transportation strategies for the island. ## Data Collection Agency NREL and the Kauai Office of Economic Development conducted the study as part of the U.S. Department of Energy's Energy Transitions Initiative Partnership Project. ## Survey Methodology The survey was conducted July—October 2022. Respondents were recruited via direct email invitation, a press release on the Kauai County website and Facebook page, and posters at community outreach events. ## Survey Records, Data, and Documentation Survey records include 1,437 participants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Kauai Ground Transportation Survey

# 2022 Kauai Ground Transportation Survey The 2022 Kauai Ground Transportation Survey was designed to improve understanding of the transportation preferences of residents and visitors of the Hawaiian island of Kauai. For residents of Kauai, the survey focused on mode-choice decisions for commute, leisure, and shopping activities and whether they would consider using alternative modes instead of driving if such options were available. For visitors, the survey focused on whether they would consider alternatives to rental cars if such options were available. Ultimately, survey results will inform the development of sustainable transportation strategies for the island. ## Data Collection Agency NREL and the Kauai Office of Economic Development conducted the study as part of the U.S. Department of Energy's Energy Transitions Initiative Partnership Project. ## Survey Methodology The survey was conducted July—October 2022. Respondents were recruited via direct email invitation, a press release on the Kauai County website and Facebook page, and posters at community outreach events. ## Survey Records, Data, and Documentation Survey records include 1,437 participants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2022 Kauai Ground Transportation Survey

# 2022 Kauai Ground Transportation Survey The 2022 Kauai Ground Transportation Survey was designed to improve understanding of the transportation preferences of residents and visitors of the Hawaiian island of Kauai. For residents of Kauai, the survey focused on mode-choice decisions for commute, leisure, and shopping activities and whether they would consider using alternative modes instead of driving if such options were available. For visitors, the survey focused on whether they would consider alternatives to rental cars if such options were available. Ultimately, survey results will inform the development of sustainable transportation strategies for the island. ## Data Collection Agency NREL and the Kauai Office of Economic Development conducted the study as part of the U.S. Department of Energy's Energy Transitions Initiative Partnership Project. ## Survey Methodology The survey was conducted July—October 2022. Respondents were recruited via direct email invitation, a press release on the Kauai County website and Facebook page, and posters at community outreach events. ## Survey Records, Data, and Documentation Survey records include 1,437 participants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗