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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 OSTI2021

Basic Energy Sciences Roundtable: Foundational Science for Carbon-Neutral Hydrogen Technologies

Basic research to identify and understand the fundamental principles governing hydrogen processes is essential for achieving a carbon-neutral, hydrogen-based energy and chemical infrastructure. In August 2021, the Office of Basic Energy Sciences (BES)—in coordination with the US Department of Energy (DOE) technology Offices of Energy Efficiency and Renewable Energy, Fossil Energy and Carbon Management, and Nuclear Energy—held a roundtable titled, “Foundational Science for Carbon-Neutral Hydrogen Technologies,” to discuss the scientific and technical barriers for carbon-neutral hydrogen production, storage, and utilization. Four priority research opportunities (PROs) were identified to address these scientific and technical challenges and accelerate progress toward the realization of energy-efficient, carbon-neutral cycles for hydrogen processes. The PROs are as follows: Discover and Control Materials and Chemical Processes to Revolutionize Electrolysis Systems; Manipulate Hydrogen Interactions to Harness the Full Potential of Hydrogen as a Fuel; Elucidate the Structure, Evolution, and Chemistry of Complex Interfaces for Energy- and Atom-Efficiency; and Understand and Limit Degradation Processes to Enhance the Durability of Hydrogen Systems.

08 HYDROGEN↗
DOE OSTI2021

Foundations of Rigorous Cyber Experimentation

This report presents the results of the “Foundations of Rigorous Cyber Experimentation” (FORCE) Laboratory Directed Research and Development (LDRD) project. This project is a companion project to the “Science and Engineering of Cyber security through Uncertainty quantification and Rigorous Experimentation” (SECURE) Grand Challenge LDRD project. This project leverages the offline, controlled nature of cyber experimentation technologies in general, and emulation testbeds in particular, to assess how uncertainties in network conditions affect uncertainties in key metrics. We conduct extensive experimentation using a Firewheel emulation-based cyber testbed model of Invisible Internet Project (I2P) networks to understand a de-anonymization attack formerly presented in the literature. Our goals in this analysis are to see if we can leverage emulation testbeds to produce reliably repeatable experimental networks at scale, identify significant parameters influencing experimental results, replicate the previous results, quantify uncertainty associated with the predictions, and apply multi-fidelity techniques to forecast results to real-world network scales. The I2P networks we study are up to three orders of magnitude larger than the networks studied in SECURE and presented additional challenges to identify significant parameters. The key contributions of this project are the application of SECURE techniques such as UQ to a scenario of interest and scaling the SECURE techniques to larger network sizes. This report describes the experimental methods and results of these studies in more detail. In addition, the process of constructing these large-scale experiments tested the limits of the Firewheel emulation-based technologies. Therefore, another contribution of this work is that it informed the Firewheel developers of scaling limitations, which were subsequently corrected.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Basic Energy Sciences Roundtable: Foundational Science for Carbon Dioxide Removal Technologies (Brochure)

Basic research to identify and understand the fundamental principles governing carbon dioxide removal processes of capture, conversion, and storage is essential for achieving zero carbon emissions by 2050. In March 2022, the Office of Basic Energy Sciences (BES)—in coordination with the US Department of Energy (DOE) technology Offices of Energy Efficiency and Renewable Energy, Fossil Energy and Carbon Management, and Nuclear Energy—held a roundtable titled, “Foundational Science for Carbon Dioxide Removal Technologies,” to discuss the scientific and technical barriers for CO 2 capture, conversion, and storage. Five priority research opportunities were identified to address these scientific and technical challenges and accelerate progress toward the realization of zero carbon emissions. The PROs are as follows: 1) Master Interfacial Processes of CO2 Transport and Reactivity Across Multiple Length and Time Scales; 2) Create Materials that Simultaneously Exhibit Multiple Properties for CO 2 Capture and Release or Conversion; 3) Discover Unconventional Pathways for Energy-Efficient CO 2 Capture, Release, and Conversion; 4) Control Multiphase Interactions Required for CO 2 Conversion into Minerals and Materials; and 5) Achieve Predictive Understanding of Coupled Processes in Complex Subsurface Geologic Systems for Secure Carbon Storage.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Foundational Open Source Solar System Modeling Through Improvement and Validation of the System Advisor Model and PVWatts (FY19-FY21 Final Technical Report)

Accelerating intelligent deployment of solar energy technologies demands accurate system modeling every step of the way. From project development to policy research, grid integration studies to development of novel technologies, industry and researchers alike need validated, transparent, easy-to-use, extensible, cutting-edge, and accurate models of both the performance and financing of solar systems. The System Advisor Model (SAM) and PVWatts tools provide a platform to fill that need. The overarching goal of this set of software tools is to enable accurate PV system modeling across the industry, and our usage metrics indicate that we continue to succeed in that endeavor, with a user starting SAM every 2 minutes globally, and over 17 million PVWatts hits per month. This project leveraged DOEs past investment in the SAM and PVWatts platforms to continue to provide valuable and extensible PV, battery, and financial modeling resources to the larger solar community. We pursued multiple avenues in parallel: software maintenance and technical support that are foundational to the continued usability of the SAM and PVWatts platforms; platform and PV model improvements and stakeholder engagement activities that are core to the continued relevance of the platforms; and open source activities to foster the continued creation of a vibrant open-source community around the SAM and PVWatts tools, which opens up exciting new opportunities for industry interaction.

14 SOLAR ENERGY↗
DOE OSTI2024

Early Career Researcher Support for Foundations of Molecular Modeling and Simulation Conference

This project enabled 14 early career researchers, including graduate students and postdocs, to attend the 8th triennial conference on Foundations of Molecular Modeling and Simulation (FOMMS 2022), which took place in Delavan, WI (Lake Geneva area), from July 17 to 21, 2022. Molecular-level modeling and simulation, which serve as critical tools for advancing science and engineering in a myriad of applications, were at the forefront of discussions. These ranged from the design of new materials for various energy applications to insights into the interaction between drug molecules and protein receptors within the body.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

AI Foundation Models for Science [Slides]

This presentation deals with three main points: why answer science questions with AI, trusting AI for science, and foundation models for science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Disruption avoidance via island suppression: the crucial roles of DIII-D and foundational research

The FESAC long range plan calls out disruption avoidance and mitigation as key remaining technical gaps. In discussing the roles of DIII-D and NSTX-U, the FESAC long range plan says “Additional research on these facilities, in combination with private and international collaborations, continuing support of existing university tokamak programs, and utilization of US expertise in theory and simulation, is needed to find solutions to remaining technical gaps. These gaps include disruption prediction, avoidance, and mitigation …”. Disruptions pose an existential threat to ITER and to FPPs. For a fusion reactor, unplanned shutdowns caused by disruptions will be a significant barrier to connecting such a reactor to the electric grid, even if disruption mitigation is successful. Disruption studies for ITER in recent years have largely focused on disruption mitigation (e.g., pellet injection), motivated by near-term deadlines for finalizing the design of the mitigation hardware. It is recognized, however, that mitigation alone will not suffice. The 2022 U.S. ITER Research Needs Workshop Report states that ”[d]isruptions are considered the largest threat to the ITER Research Program”, and that “[m]itigation should be a last resort”. As we discuss below, there are unresolved foundational issues that play a critical role in avoidance, and DIII-D is an ideal device for generating the data needed to address these issues.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

The Foundational Industrial Energy Dataset (FIED): Open-Source Data on Industrial Facilities

The state of data on industrial energy use has co-evolved over several decades with the demands of industrial energy analysis. The most recent development - analysis in support of decarbonizing the industrial sector - has changed the characteristics of industrial data that are useful for analysts and model developers. Although data and its collection processes may be cast from a conventional viewpoint as objective and free from the influence of social dynamics, this provides an incomplete picture of not only the processes by which information is generated, but also the limitations and opportunities of data to be useful for analysis. The foundational industry energy data set (FIED) is a result of the confluence of trends in open data and the demand for higher resolution industrial energy analysis. The general approach to compiling the FIED involves accessing, filtering, and formatting data published by federal organizations on the Internet for public use. Unlike most industrial energy datasets, which are published by the U.S. Energy Information Administration (EIA), the FIED relies on core datasets from the U.S. Environmental Protection Agency (EPA). The FIED addresses several of the areas of growing disconnect between the demands of industrial energy analysis and the state of industrial energy data by providing unit-level characterization - including estimates of energy use, greenhouse gas emissions, and design capacities - for facilities that are identified by latitude and longitude. This enables local-level analysis of existing combustion equipment, as well as regional comparisons with traditional industrial energy data estimates. The report summarizes the general logic behind compiling the FIED. The FIED itself and its Python code are available from OpenEI and GitHub, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

The Essence of Cryptol: A Denotational Cryptol Interpreter in Coq for Foundational Assurances for Quantum Resistant Cryptosystems

Systems of the utmost consequence need a means to establish authenticity of software and data. Cryptosystems implement authentication, but can be vulnerable to cryptographic and implementation attacks. With the threat of quantum cryptographic attacks, “post-quantum” cryptosystems (PQCs) must be henceforth used in these systems. However, the new cryptography needs new ways to, rigorously and machine-checkably, prove systems free of vulnerabilities. We propose a retargetable capability to rapidly instantiate proven correct postquantum cryptosystems through novel proof-carrying synthesis and proof-automation technique, extending those proven successful on existing systems. This capability is crucial to meeting the cryptographic requirements for future high-consequence systems. Since specifications for high consequence cryptography are presently captured in a domain specific language known as Cryptol. While this can enable convenient fully automated reasoning about Cryptol specificaitons and implementations via the Software Analysis Workbench (SAW), Cryptol has expressivity gaps, so that cryptosystems with probabilistic programming features like Falcon cannot be fully expressed in the language. Moreover, SAW’s automation fails for programs and specificaitons with inductive and recursive structure, as in the Sphincs+ PQC. Finally, Cryptol and SAW together represent some 200,000 lines of unverified Haskell, so that the any guarantees about high consequence cryptography are presently contingent on a large, unverified, yet trusted computing base. The first step of the larger project of agile, assured crpytography is therefore to provide a formal, mechanized semantics for Cryptol, so that the specifications expressed by cryptographers in Cryptol can be reasoned about and compiled into performant implementations with a foundational, machine checkable certificate of correctness. This report describes our work on this first step, culminating in the design of a certified denotational interpreter, in Coq, for core Cryptol.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Partial Support of the Fast-Track Consensus Study on Foundational Research Gaps and Future Directions for Digital Twins (Final Report)

This study from the National Academies of Sciences, Engineering, and Medicine was launched to explore the foundational research gaps and opportunities for digital twins. As part of the information gathering process, the committee organized three targeted workshops—in engineering, climate sciences, and biomedical sciences—to better understand domain-specific nuances and barriers to developing digital twins. These sessions enabled cross-sector experts to surface field-specific needs, challenges, and open questions related to digital twins. Thousands of participants across multiple domains engaged in the discussions, which workshops were summarized in three separate Proceedings-in-Brief.

42 ENGINEERING↗
DOE OSTI2025

Evaluating Tools and Technologies for Monitoring Baleen Whales During Offshore Wind Foundation Installation

Impacts to baleen whales are of particular concern in the context of offshore wind development because of their conservation status, the overlap of their habitat with current and planned offshore wind energy facilities, and their expected sensitivity to low-frequency sounds, such as those produced during pile driving. Therefore, this report focuses on monitoring technologies capable of detecting this species group. The scope of this report is to assess the current state of technologies and methods for monitoring baleen whales in low- and no-light conditions in conjunction with offshore wind foundation installation. This work considers the performance of various sensing technologies that can be used to observe the presence of baleen whales near offshore construction activities. The scope of work includes: 1. Technology Performance Metrics – Identify metrics that can be used to assess technology performance. 2. Technology Evaluation – Synthesize the past performance of technologies with respect to the performance metrics based on available literature. 3. Technology Characterization Framework – Describe a potential framework to characterize technology performance with a standardized approach. 4. Technology Research and Development Needs – Identify future needs and opportunities for research, development, and deployment to improve technologies.

17 WIND ENERGY↗
DOE OSTI2026

Knowledge-Based Hazardous Waste Determinations for Solar Photovoltaic (PV) Modules: A Foundational Study

This report explores using "generator knowledge" to determine whether a solar photovoltaic (PV) module must be managed as hazardous waste prior to recycling or landfilling. Generator knowledge is a legal term and existing regulatory pathway for making a hazardous waste determination that has been used by other industries but is a relatively unknown option to the PV industry. In the United States, a hazardous waste determination often acts as a pre-requisite to recycle or landfill a PV module. The results of the hazardous waste determination dictate whether the PV module must be managed as hazardous waste or nonhazardous solid waste. Managing a PV module as hazardous waste requires compliance with stringent U.S. federal and state hazardous waste law. In addition to increased management costs, which can be ten times higher, legal liability for PV modules regulated as hazardous waste is also heightened with both civil and criminal penalties for noncompliance which includes making an inaccurate or faulty hazardous waste determination. The most common reason a PV module would be regulated as hazardous is if it contains a regulated metal in an amount that equals or exceeds the toxicity characteristic limits. To determine whether a PV module exhibits a hazardous characteristic, the regulated person/entity must "apply knowledge...in light of the materials and processes used." In the absence of adequate knowledge to determine whether the PV module is hazardous, it must be tested using Test Method 1311 Toxicity Characteristic Leaching Procedure (TCLP) or an equivalent EPA-approved method. Although TCLP is the predominant method used to today to make a hazardous waste determination for PV modules, evidence from this study concludes it is not practical to TCLP test every PV module even in a single utility-scale installation, and a scalable solution is needed. This study finds that knowledge-based hazardous waste determinations may allow a regulated person/entity to make a hazardous waste determination for more than one PV module at one time - making this regulatory pathway a potential scalable solution. Through legal analysis and interviews with 44 experts, the authors explore what it means to make an accurate knowledge-based hazardous determination for PV modules considering sources and forms of information as well as potential limitations. The work aims to provide a foundation for building consensus on whether knowledge-based hazardous determinations are a viable, scalable industry approach for solar.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

AI-Assisted Conceptual Development of a Pre-Geometric Cosmological Model - An Exercise in AI-Assisted Conceptual Framework Generation, Paper I: Foundations and Replication Dynamics

We develop a pre-geometric cosmological framework in which existence is identified with a finite amount of unstructured energy possessing vibration as its only intrinsic property. This vibrational substrate occupies an open, bounded spectral interval $(\omega_{\min},\omega_{\max})$, ensuring finiteness of total energy and excluding infinitely stable configurations. The substrate evolves under two fundamental and competing tendencies---excitation, which amplifies coherence, and randomization, which scrambles it. Their balance produces a metastable unstructured regime in which rare fluctuations may form long-lived self-consistent spectral configurations. Because the substrate is finite and subject to competing order--disorder dynamics, no coherent configuration can be perpetually stable. We show that the only mechanism capable of sustaining long-lived organization is a replication instability: a coherent unit may reproduce into multiple offspring according to a general $1\!\to n$ rule. Replication consumes energy from the finite substrate, breaks the metastable symmetry, and induces a discrete notion of event time through the replication tick $\Delta\tau$. Temporal succession is defined through correlation ordering of spectral microstates, producing an intrinsic pre-causal structure. The compactness of the spectral domain imposes minimal and maximal timescales, bounds the internal coherence of emergent units, and limits their proliferation. These spectral constraints serve as precursors for the emergence of geometry, adjacency, and a limiting propagation speed, developed in subsequent papers of this series. Paper I provides the foundational axioms (PG1--PG9) governing the spectral substrate, its metastable dynamics, the formation of coherent units, and the necessity of replication, establishing a fully pre-geometric stage from which causal and geometric structure naturally emerge.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The Foundational Industry Energy Dataset: Unit-level Characterization and Derived Energy Estimates for Industrial Facilities in 2017

The Foundational Industry Energy Dataset (FIED) addresses several of the areas of growing disconnect between the demands of industrial energy analysis and the state of industrial energy data by providing unit-level characterization by facility. Each facility is identified by a unique registryID, based on the U.S. Environmental Protection Agency (EPA) Facility Registry Service, and includes its coordinates and other geographic identifiers. Energy-using units are characterized by design capacity, as well as their estimated energy use, greenhouse gas emissions, and physical throughput using 2017 data from the EPA's National Emissions Inventory and Greenhouse Gas Reporting Program. An overview of the derivation methods is provided in a separate technical report which will be linked after publication. The Python code used to compile the dataset is available in a GitHub repository. An updated 2020 version is under development.

Array↗
DOE OSTI2023

Energy Efficiency as a Foundational Technology Pillar for Industrial Decarbonization

The U.S. government aims to achieve net-zero greenhouse gas emissions by 2050 to reduce the severe impacts of climate change. The U.S. industrial sector will become a focal point for decarbonization since it accounts for 33% of the nation’s primary energy use and 30% of its energy-related CO2 emissions. Industrial emissions are also expected to increase by 15% through 2050, making the industrial sector a logical target for decarbonization efforts. Energy efficiency technology pathways provide low-cost, foundational routes to decarbonization that can be implemented immediately. Energy efficiency technology pathways, such as strategic energy management, system efficiency, smart manufacturing, material efficiency, and combined heat and power, are well established and would immediately reduce energy use and emissions. However, their role in the aggressive net-zero decarbonization pathway for the industrial sector is still unclear. This study aims to address energy efficiency pathways for decarbonization, and reviews studies related to these technologies for industrial decarbonization through 2050. This study identifies different strategies for the industrial sector in general and that are specific to six energy-intensive industries: iron and steel; chemical; food and beverage; petroleum refining; pulp and paper; and cement. Finally, a path toward the successful implementation of energy efficiency technologies is outlined.

Strategic energy management↗
DOE OSTI2025

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics

Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the development of scientific foundation models (FMs). However, applying this capability to experimental particle physics is challenging due to the sparse, spatially distributed nature of detector data, which differs dramatically from natural language. This work addresses if an FM for particle physics can scale and generalize across diverse tasks. We introduce a new dataset with more than 11 million particle collision events and a suite of downstream tasks and labeled data for evaluation. We propose a novel self-supervised training method for detector data and demonstrate its neural scalability with models that feature up to 188 million parameters. With frozen weights and task-specific adapters, this FM consistently outperforms baseline models across all downstream tasks. The performance also exhibits robust data-efficient adaptation. Further analysis reveals that the representations extracted by the FM are task-agnostic but can be specialized via a single linear mapping for different downstream tasks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗