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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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DOE OSTI2024

The Lithuania 100% Renewable Energy Study - Interim Results: Electricity System Scenarios for 2030 [Slides]

Lithuania's Energy Vision aims to achieve self-sufficiency in electricity generation by 2035 and transition to 100% renewable energy as soon as possible while maintaining affordability, reliability, and energy security. The Lithuania Energy Agency (LEA) is partnering with the National Renewable Energy Laboratory (NREL) to conduct the Lithuania 100% Renewable Energy Study (Lithuania 100) to provide evidence-based analysis for development of Lithuania's National Energy Independence Strategy. The Lithuania 100 Study leverages unique tools and capabilities of NREL to provide rigorous technical analysis of clean energy policies to achieve 100% renewable energy, and assess impacts on electricity grid operations, hydrogen system development, electricity distribution networks, air quality, and human health outcomes. The study is supported by a stakeholder committee chaired by the Ministry of Energy of Lithuania and implemented by four technical working groups. This report provides highlights of key interim results from modeling of Lithuania's near-term electricity grid through the year 2030. Results show that Lithuania has sufficient renewable energy potential, flexible generation capacity, and interconnection with neighboring European Union countries to reliably meet projected 2030 electricity demand with 100% renewable energy. A range of scenarios were modeled, each of which achieves at least 100% renewable energy in electricity, on average over the year, by 2030. Potential demands for hydrogen across industrial and transportation sectors were also evaluated, as well as the cost of hydrogen produced in Lithuania by 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Volcanology, Geochemistry, and Petrology Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

This article is composed of a commentary about the state of Integrated, Coordinated, Open, and Networked (ICON) principles in Volcanology, Geochemistry, and Petrology (VGP), and discussion on the opportunities and challenges of adopting them. VGP encompasses a broad field that addresses volcanic, magmatic, hydrothermal, geomicrobial systems; process investigations that span the physical, geochemical and biological realms, including planetary geology; and one that is extensively supported by state-of-the-art research facilities. We suggest that an open, inclusive, collaborative and evolving model of an international coordinated network is critical to answering the most pressing challenges in VGP. In this commentary piece, we begin to discuss the elements of, challenges to, and path forward in developing such a model. For this team, ICON means collaboration, equitable access to data for the entire scientific community, and forging of partnerships that potentially contribute to more innovative ways of coordinating and sharing research. It also means bringing more equity to science, by implementing effective measures which consider access to funding, analytical equipment, resources, and mentors. More importantly, ICON to us means having important conversations around what we value in the advancement of science, perhaps exploring outside the idea of meritocracy and evaluating what individual traits can contribute to science outside what has traditionally been considered the norm.

58 GEOSCIENCES↗
DOE OSTI2020

Spatial Atomic Layer Deposition to Scale Manufacturing of Robust Catalysts for Biomass Conversion Applications: Cooperative Research and Development Final Report, CRADA Number CRD-17-715

This CRADA will facilitate technology maturation for NREL-developed ALD-coated catalyst materials that are tailored for durability during harsh biomass conversion chemistries. This project will address optimizing process parameters for scale-up of Al2O3 ALD-coated catalysts, demonstrating ALD-coated catalyst performance for muconic acid hydrogenation, and validating economic models that project significant cost benefits for ALD-enhanced catalytic processes. This work will strengthen private-public partnerships in the area of advanced catalyst manufacturing for energy-related technology. Critical information will be collected to elevate the Technology Readiness Level and increase our competitiveness for cooperative R&D agreements and licensing. Success of this work will be crosscutting as it can facilitate advanced catalyst development for both renewable and conventional processes.

09 BIOMASS FUELS↗
DOE OSTI2020

PLATFORM for Product Launch

Pecan Street Inc. (PSI) and its partners set out in 2017 to validate the PLATFORM for Product Launch, a new model for improving the effectiveness of investments in clean energy technologies and accelerating market entry of disruptive technologies. In partnership with a newly formed Innovation Advisory Council, PSI recruited fourteen companies with new hardware-based technologies that enable or create clean energy opportunities. Pecan Street carried out product evaluations and conducted market research with stakeholders and target customers to develop recommendations on product optimization opportunities for all companies, and created third party performance evaluation reports that include environmental metrics, such as water and energy savings potential, to assist in creating investment confidence and to unlock additional sources of funding, such as impact investments. Pecan Street set-up the product testing environment, performed small-batch field testing, and provided a verified third-party performance report on the product of twelve companies. PSI Street and its partners leveraged the performance evaluations and insights from the newly formed PRI toolkit to raise over $1.5M across five companies, and garner interest for private sector adoption of the PLATFORM for Product Launch.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Enhanced Catalyst Durability for the Oxidative Production of Biobased Chemicals (Cooperative Research and Development Final Report)

This CRADA will facilitate technology maturation for NREL-developed atomic layer deposition (ALD) coated catalyst materials that are tailored for durability during the oxidative production of biobased chemicals. This project will address optimizing process parameters for scaling aluminum oxide (Al 2 O 3 ) ALD coated catalysts, demonstrating ALD coated catalyst performance for biomass oxidation, and validating economic models that project significant cost benefits for ALD-enhanced catalytic processes. This work will strengthen private-public partnerships in the area of advanced catalyst manufacturing for energy-related technology. Critical information will be collected to elevate the Technology Readiness Level and increase our competitiveness for cooperative R&D agreements and licensing. Success of this work will be crosscutting as it can facilitate advanced catalyst development for both renewable and conventional processes.

09 BIOMASS FUELS↗
DOE OSTI2021

NRAP-Open-IAM Analytical Reservoir Model: Development and Testing

Geological carbon sequestration (GCS) is a key technology for reducing global carbon dioxide (CO 2 ) emissions. Over the last decade, the U.S. Department of Energy has invested in understanding the science base, developing practical implementation methods, and demonstrating secure GCS technologies to mitigate the environmental impacts associated with the atmospheric release of CO 2 . As part of the National Risk Assessment Partnership, a systems-level risk assessment tool, called the NRAP-Open-IAM, has been developed to conduct risk assessment and enable safe operations at a GCS site. The current NRAP-Open-IAM contains a simple reservoir model component that calculates the evolution of CO 2 saturation and fluid pressure in a storage reservoir during CO 2 injection operations. This report presents the development and testing of a new analytical reservoir reduced-order model (ROM), which is extended from an existing semi-analytical model for estimation of CO 2 and brine leakage along legacy wells, and enhances the capability of the NRAP-Open-IAM to simulate more types of reservoir conditions. The developed model is validated against three reference studies, and the results indicate that the new ROM predicts the behavior of the two-phase fluids (brine and injected CO 2 ) well and is applicable to different reservoir simulation boundary conditions (i.e., constant pressure boundary and infinite-acting boundary) without a priori user specification of the boundary type. Sensitivity analysis for a set of model parameters is performed using 4,000 synthetic cases prepared via a fully automated process and using machine-learning-based feature selection. The stochastic analysis identifies gravitational number (i.e., ratio of gravitational forces to viscous force) and distance between the injection well and observation location as the most impactful parameters for matching the pressure and CO 2 saturation, respectively, between the numerical simulations and the ROM. This report details the possible ROM uncertainties and serves as a guide for users to understand the use and limitations of this ROM. The code implementation of the model will be released as a module within the NRAP-Open-IAM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Kimberlina 1.2 Velocity Models and Seismic Data

Kimberlina 1.2 Velocity model and synthetic seismic data, produced in collaboration of teams at the National Energy Technology Laboratory, Los Alamos National Laboratory, and Lawrence Livermore National Laboratory through the National Risk Assessment Partnership. Data is associated with the following publication: Zheng Zhou, Youzuo Lin, Zhongping Zhang, Yue Wu, Zan Wang, Robert Dilmore, and George Guthrie, "A Data-Driven CO2 Leakage Detection Using Seismic Data and Spatial-Temporal Densely Connected Convolutional Neural Networks," International Journal of Greenhouse Gas Control, Vol 90, 2019. The Kimberlina 1.2 Velocity models were produced by Zan Wang, Robert Dilmore, William Harbert, and Lianjie Huang at NETL. The following citations are directly related to the creation of the velocity models: Wang, Z. Harbert, W., Dilmore, R., Huang, L. Modeling of time-lapse seismic monitoring using CO2 leakage simulations for a model CO2 storage site with realistic geology: Application in assessment of early leak-detection capabilities. International Journal of Greenhouse Gas Control. V. 76, September 2018, Pages 39-52. https://doi.org/10.1016/j.ijggc.2018.06.011 Wang, Z., Dilmore, R., Harbert, W. Inferring CO2 saturation from synthetic surface seismic and downhole monitoring data using machine learning for leakage detection at CO2 sequestration sites. International Journal of Greenhouse Gas Control, V. 100, September 2020. https://doi.org/10.1016/j.ijggc.2020.103115 The velocity models were built based on the Kimberlina 1.2 aquifer impact data which is associated with the following publications: Buscheck, T.A., Mansoor, K., Yang, X., Wainwright, H., and Carroll, S. (2019). Downhole pressure and chemical monitoring for CO2 and brine leak detection in aquifers above a CO2 storage reservoir. International Journal of Greenhouse Gas Control. 91. 102812. 10.1016/j.ijggc.2019.102812. Xianjin Yang, Thomas A. Buscheck, Kayyum Mansoor, Zan Wang, Kai Gao, Lianjie Huang, Delphine Appriou, Susan A. Carroll, Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, Volume 90, 2019, 102803, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2019.102803 The synthetic seismic data was produced by Youzuo Lin and team at LANL, and are associated with the following citations: Jordan, P. D., and J. L. Wagoner. Characterizing Construction of Existing Wells to a CO2 Storage Target: The Kimberlina Site, California. Zheng Zhou, Youzuo Lin, Zhongping Zhang, Yue Wu, Zan Wang, Robert Dilmore, and George Guthrie, "A Data-Driven CO2 Leakage Detection Using Seismic Data and Spatial-Temporal Densely Connected Convolutional Neural Networks," International Journal of Greenhouse Gas Control, Vol 90, 2019.

CO2 Leakage↗
DOE OSTI2025

Building collaboration to advance our understanding of regional climate impacts of dust in California's San Joaquin Valley

This project successfully achieved its central objective of building collaborative research capabilities at UC Merced, a Hispanic-Serving Institution, to advance understanding of the regional climate impacts of dust in California's San Joaquin Valley. Through strategic partnerships with three DOE national laboratories (PNNL, LLNL, and LBNL), we developed critical expertise in the Energy Exascale Earth System Model (E3SM) and Atmospheric Radiation Measurement (ARM) facilities. Among the project's scientific contributions, one key publication includes demonstrating that fallowed agricultural lands are the primary source of anthropogenic dust in California's Central Valley, with dust activities increasing substantially between 2008 and 2022, in correlation with drought severity and expanded fallowed land coverage. This finding suggests that current climate models, including E3SM, likely underestimate the dust burden due to inadequate representation of agricultural land-use changes. Beyond the scientific contributions, the project successfully trained a PhD student, established ongoing collaborations resulting in multiple manuscripts in preparation, and positioned UC Merced to participate in the DUSTIEAIM campaign for 2026-2027, thereby building sustainable research capacity while addressing climate science questions directly relevant to the California Central Valley.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

5-minute Wind Power Data based on WFIP2 WRF Simulation

The second Wind Forecast Improvement Project (WFIP2) was a public-private partnership funded by the U.S. Department of Energy and NOAA, aimed at enhancing the forecast skill of numerical weather prediction models for turbine-height winds in regions with complex terrain. An 18-month Weather Research and Forecasting (WRF) model simulation was conducted over the Pacific Northwest, with model outputs validated against observational data collected during WFIP2. Simulated wind speeds were used to estimate wind power generation using reV (the Renewable Energy Potential Model developed by NREL) at ten wind project sites. Two sets of results were produced: one using wind speeds extracted from the model grid cell at the project centroid, and another using wind speeds from the actual turbine locations. For each dataset, power output was calculated using both actual turbine-specific power curves and nine generic power curves to convert wind speed into power.

17 WIND ENERGY↗
DOE OSTI2022

Quantitative interpretation of time-lapse seismic data at Farnsworth field unit: Rock physics modeling, and calibration of simulated time-lapse velocity responses

Here, this study investigates the contribution of fluid saturation variation to the time-lapse velocity response by performing fluid substitution modeling. The methodology is exemplified by the time-lapse seismic monitoring of carbon dioxide at Farnsworth field unit (FWU). In order to evaluate the fluid distribution in a matured oil reservoir, the Southwest Regional Partnership (SWP) acquired multiple vertical seismic profile (VSP) surveys at different times during the CO 2 –water alternatinggas (WAG) injection period. In this work, we present a thorough methodology for computing the elastic response of the saturated rock for different fluid saturations using a site-specific petro-elastic model (PEM). The output from the PEM was combined with results from a fluid compositional model to compute the seismic velocities at times corresponding to each VSP survey. To produce a calibrated simulated response, the measured time-lapse seismic velocities were integrated into the numerical simulation model. The mismatches between the predicted and measured time-lapse velocities were minimized through an iterative calibration process using a trained artificial neural network proxy (ANN) coupled with a particle swarm optimizer (PSO). Our study indicates that the hybrid optimization workflow can effectively perform the history matching. With an accurate prediction of the hydrodynamic properties, the migration of CO 2 within the subsurface was modeled by predicting the spatial velocity distribution for a radius of 305 m around the injection well. The technology demonstrated and the expertise gained from this study can guide similar CO 2 -WAG projects.

58 GEOSCIENCES↗
DOE OSTI2023

Analysis Program 2022 Annual Progress Report

The VTO Analysis Program supports mission-critical technological, economic, and interdisciplinary analyses to assist in prioritizing VTO technology investments and to inform research portfolio planning. These efforts provide essential vehicle and market data, modeling and simulation, and integrated and applied analyses, using the unique capabilities, analytical tools, and expertise resident in the DOE’s national laboratory system. VTO Analysis projects also demonstrate additional capabilities and expertise provided by research partnerships that may include academia, the private sector, and non-profit organizations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

2022 Peer Review Project Summary: Advanced Protection for Microgrids and DER in Secondary Networks and Meshed Distribution Systems

Although there are increasing numbers of distributed energy resources (DERs) and microgrids being deployed, current IEEE and utility standards generally strictly limit their interconnection inside secondary networks. Secondary networks are low-voltage meshed (non-radial) distribution systems that create redundancy in the path from the main grid source to each load. This redundancy provides a high level of immunity to disruptions in the distribution system, and thus extremely high reliability of electric power service. There are two main types of secondary networks, called grid and spot secondary networks, both of which are used worldwide. In the future, primary networks in distribution systems that might include looped or meshed distribution systems at the primary-voltage (mediumvoltage) level may also become common as a means for improving distribution reliability and resilience. The objective of this multiyear project is to increase the adoption of microgrids in secondary networks and meshed distribution systems by developing novel protection schemes that allow for safe reliable operation of DERs in secondary networks. We will address these challenges by working with the appropriate stakeholders of secondary network operators, protection vendors, and standards committee. The outcomes of this project include: a) development and/or demonstration of candidate methods for enabling protection of secondary networks containing high levels of DER; b) development of modeling and testing tools for protection systems designed for use with secondary networks including DERs; and c) development of new industrial partnerships to facilitate widespread results dissemination and eventual commercialization of results as appropriate.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Multimode Characterization Approach for Understanding Cell-Level PV Performance and Degradation

Cell-level degradation processes impact the economic viability and large-scale deployment prospects for both established and emerging photovoltaic (PV) technologies. This project addresses the need to develop experimental and device-modeling approaches for studying cell-level degradation processes in photovoltaic (PV) devices using a variety of characterization techniques that provide access to complementary material and device properties. Our results demonstrate that by coupling characterization results with device modeling it is possible to develop comprehensive understanding of processes leading to performance limitations and degradation. This project developed a suite of novel measurement techniques including pulsed-light-bias operando X-ray and photoelectron spectroscopy (popXPS), light-biased scanning microwave impedance microscopy (sMIM), and near-field transport imaging (TI). In addition, operando characterization methodologies and in situ stressing capabilities have been developed and applied for techniques including electron-beam-induced current (EBIC), cathodoluminescence (CL), and Kelvin probe force microscopy (KPFM). Device-physics models were developed and applied to simulate correlative, multi-mode measurements to extract material and device parameters that control performance degradation. These characterization and modeling techniques were applied in a multi-mode approach to probe cell-level degradation mechanisms in Cd(Se,Te) and hybrid perovskite PV devices. Together these efforts contribute to foundational PV degradation science by establishing a framework for understanding PV performance degradation at the cell level and benefit the U.S. PV industry by providing resources in the form of novel experimental capabilities, knowledge gained, and available expertise that can accelerate research and development of improved PV device materials and architectures. The project provided a comprehensive understanding of degradation in baseline Cd(Se,Te) solar cells provided by our collaborators at Colorado State University (CSU). EBIC and CL-based measurements and revealed unusual collection and recombination profiles in these devices, which underwent significant changes with during stressing. KPFM and operando XPS measurements showed that device stressing permanently alters energy-band alignments at the (Mg,Zn)O/Cd(Se,Te) interface, which in turn account for an observed loss in fill factor. Studies on hybrid perovskite devices were hampered to a significant extent by delays related to the pandemic. Nevertheless, a set of hybrid perovskite devices (supplied through an NREL-industry partnership) were stress tested and characterized with techniques including EBIC, sMIM, popXPS/popUPS and optically excited TI. Available results from these measurements informed the device modeling effort and suggest that defects and related band offsets at the C60/LiF/hybrid perovskite interface are the primary source of degradation in these devices.

14 SOLAR ENERGY↗
DOE OSTI2025

MRCI Task 2: Addressing Key Technical Challenges - Executive Summary Report

This report provides a high-level overview of Task 2 products that were developed through defining carbon storage systems, Precambrian basement structure and stress, developing regional technical collaboration, modeling and risk assessment. Subtask 2.1: Defining Sub-Regional CS/CCUS Systems Subtask 2.2: Defining Precambrian basement faulting/stress Subtask 2.3: Developing industrial partnerships and regional technical collaborations Subtask 2.4: Conducting regional/subregional analysis Subtask 2.5: Assessing and managing risk for potential commercial-scale storage complexes

MRCI,Technical Challenges↗
DOE OSTI2020

Enhanced Visualization Capabilities in OpenMC: Report of Activities under a DOE GAIN Voucher

This work was performed under a Cooperative Research and Development Agreement (CRADA) through the U.S. Department of Energy’s Gateway for Accelerated Innovations in Nuclear (GAIN) program in partnership with Oklo Inc., the industry participant. The broad goal of this project was to improve the visualization capabilities of OpenMC related to model development and simulation results. OpenMC is a Monte Carlo particle transport code that is developed and maintained by a broad community of contributors, of which Argonne National Laboratory plays a leading role.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

User’s Manual for Seal_Flux: A Seal Barrier Reduced-Order Model (Update)

This report provides a brief description on the use of the Seal_Flux computer program developed as part of the effort to quantify the risk of geologic storage of carbon dioxide (CO 2 ) under the U.S. Department of Energy’s (DOE) National Risk Assessment Partnership (NRAP). The Seal_Flux code simulates the flow of CO 2 through a low permeability rock horizon or seal formation overlying the storage reservoir into which CO 2 is injected. A two-phase, relative permeability approach with Darcy’s law is used for one-dimensional (1D) flow computations of CO 2 through the horizon in the vertical direction. The code also allows the simulation of time-dependent processes that can influence such flow. However, as part of its design, Seal_Flux is what can be termed a “reduced-order model” (ROM) and is not intended as a full-functioning flow code. The theory and simulation in the code is streamlined and directed towards the implementation of Monte Carlo risk analyses of CO 2 transport or as termed in this context as “leakage.” While presented in this report as a stand-alone tool, the Seal_Flux code is intended to function in the future as one of several models as part of an integrated, systems-level model of CO 2 storage performance. Finally, the code is written in Python 3.10 to provide an open framework for further development by others and to assist in linking the code with other modules in an integrated assessment model.

58 GEOSCIENCES↗
DOE OSTI2022

The energy system transformation needed to achieve the US long-term strategy

The authors designed and executed the integrated assessment modeling for the United States long-term strategy. They bring diverse expertise to the modeling and analysis of United States decarbonization. Russell Horowitz, Matthew Binsted, and Haewon McJeon are scientists at the Joint Global Change Research Institute, a partnership between Pacific Northwest National Laboratory and the University of Maryland. Allen Fawcett, James McFarland, and Morgan Browning are economists at the Environmental Protection Agency’s Climate Economics Branch. Claire Henly is White House Fellow at the Office of the US Special Presidential Envoy for Climate. Nathan Hultman is the Director of the Center for Global Sustainability at the University of Maryland.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗