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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Machine Learning for Optimized Polarization at Jefferson Lab

Polarized cryo-targets and polarized photon beams are widely used in experiments at Jefferson Lab. Traditional methods for maintaining the optimal polarization involve manual adjustments throughout data taking by human shift takers. This may introduce some level of inconsistency simply due to the wide variety of experience and expertise of the shift takers themselves. Implementing machine learning-based control systems can improve the stability of the polarization without relying on human intervention. The cryo-target polarization is influenced by temperature, microwave energy, the distribution of paramagnetic radicals, as well as operational conditions including the radiation dose. Diamond radiators are used to generate linearly polarized photons from a primary electron beam. The energy spectrum of these photons can drift over time due to changes in the primary electron beam conditions and diamond degradation. As a first step towards automating the continuous optimization and control processes, uncertainty aware surrogate models have been developed to predict the polarization based on historical data. This talk will provide an overview of the use cases and models developed, highlighting the collaboration between data scientists and physicists at Jefferson Lab.

Jeske, Torri [Thomas Jefferson National Accelerato↗
DOE OSTI2026

Ion Cyclotron Heating in a Levitated Dipole Fusion Reactor

OpenStar Technologies is pursuing the levitated dipole (LD) as a highly modular, loosely-coupled system that leverages their expertise in high temperature superconductor (HTS) technology. The next generation experiment at OpenStar, Tahi (Ma¯ori for “first”), will demonstrate the generation and confinement of fast ions in a levitated dipole for the first time. Ion cyclotron range of frequency (ICRF) heating is a leading candidate for energetic ion formation in Tahi. A frequency in the 10 MHz range will be used for H minority heating or D majority heating with waves launched from an antenna located above the floating coil. Unlike a tokamak, where the targeted cyclotron resonance is typically a vertical path through the center of the plasma, in a dipole the resonance location follows a C-shaped path from the separatrix to the center of the plasma. The value of B also varies significantly within the confined plasma resulting in a large number of cyclotron harmonics present in the low field region. Furthermore, levitated dipoles contain a “first closed flux surface” surrounding the floating coil, in addition to the traditional separatrix /last closed flux surface. Simulation e ff orts using full-wave ICRF codes show that ICRF heating of a levitated dipole reactor is feasible using a pair of toroidal current straps phased to launch the appropriate parallel ( i.e. poloidal) refractive index.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Templates of expected measurement uncertainties for prompt fission neutron spectra

In this paper, we provide templates of uncertainty sources expected to appear for three measurement types of prompt fission neutron spectra (PFNS): (1) shape measurements, (2) clean-ratio shape, that is the monitor PFNS are measured in nearly exactly the same surrounding as the PFNS of interest, and (3) indirect ratios, where the detector efficiency is backed out from PFNS monitor measurements. Information is also listed that is needed to faithfully include PFNS in nuclear data evaluations to guide experimenters on how to best report data and metadata for their measurements. These templates also suggest a typical range of pertinent uncertainty values and their correlations in case realistic uncertainties cannot be estimated from information on the measurement itself. The templates were based on a literature review, information found in EXFOR for 252 Cf, 235, 238 U, and 239 Pu PFNS, and enhanced by expertise from experimenters contributing to these PFNS templates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

FEW questions, many answers: using machine learning to assess how students connect food–energy–water (FEW) concepts

There is growing support and interest in postsecondary interdisciplinary environmental education which integrate concepts and disciplines in addition to providing varied perspectives. There is a need to assess student learning in these programs as well as rigorous evaluation of educational practices, especially of complex synthesis concepts. This work tests a text classification machine learning model as a tool to assess student systems thinking capabilities using two questions anchored by the Food-Energy-Water (FEW) Nexus phenomena by answering two questions (1) Can machine learning models be used to identify instructor-determined important concepts in student responses? (2) What do college students know about the interconnections between food, energy and water, and how have students assimilated systems thinking into their constructed responses about FEW? Reported here are a broad range of model performances across 26 text classification models associated with two different assessment items, with model accuracy ranging from 0.755 to 0.992. Expert-like responses were infrequent in our dataset compared to responses providing simpler, incomplete explanations of the systems presented in the question. For those students moving from describing individual effects to multiple effects, their reasoning about the mechanism behind the system indicates advanced systems thinking ability. Specifically, students exhibit higher expertise for explaining changing water usage than discussing tradeoffs for such changing usage. This research represents one of the first attempts to assess the links between foundational, discipline-specific concepts and systems thinking ability. These text classification approaches to scoring student FEW Nexus Constructed Responses (CR) indicate how these approaches can be used, in addition to several future research priorities for interdisciplinary, practice-based education research. Development of further complex question items using machine learning would allow evaluation of the relationship between foundational concept understanding and integration of those concepts as well as more nuanced understanding of student comprehension of complex interdisciplinary concepts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Evolving data standards for cryo-EM structures

Electron cryo-microscopy (cryo-EM) is increasingly being used to determine 3D structures of a broad spectrum of biological specimens from molecules to cells. Anticipating this progress in the early 2000s, an international collaboration of scientists with expertise in both cryo-EM and structure data archiving was established (EMDataResource, previously known as EMDataBank). The major goals of the collaboration have been twofold: to develop the necessary infrastructure for archiving cryo-EM-derived density maps and models, and to promote development of cryo-EM structure validation standards. We describe how cryo-EM data archiving and validation have been developed and jointly coordinated for the Electron Microscopy Data Bank and Protein Data Bank archives over the past two decades, as well as the impact of evolving technology on data standards. Just as for X-ray crystallography and nuclear magnetic resonance, engaging the scientific community via workshops and challenging activities has played a central role in developing recommendations and requirements for the cryo-EM structure data archives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Sharp, high numerical aperture (NA), nanoimprinted bare pyramid probe for optical mapping

The ability to correlate optical hyperspectral mapping and high resolution topographic imaging is critically important to gain deep insight into the structure–function relationship of nanomaterial systems. Scanning near-field optical microscopy can achieve this goal, but at the cost of significant effort in probe fabrication and experimental expertise. To overcome these two limitations, we have developed a low-cost and high-throughput nanoimprinting technique to integrate a sharp pyramid structure on the end facet of a single-mode fiber that can be scanned with a simple tuning-fork technique. The nanoimprinted pyramid has two main features: (1) a large taper angle (~70°), which determines the far-field confinement at the tip, resulting in a spatial resolution of 275 nm, an effective numerical aperture of 1.06, and (2) a sharp apex with a radius of curvature of ~20 nm, which enables high resolution topographic imaging. Optical performance is demonstrated through evanescent field distribution mapping of a plasmonic nanogroove sample, followed by hyperspectral photoluminescence mapping of nanocrystals using a fiber-in-fiber-out light coupling mode. Through comparative photoluminescence mapping on 2D monolayers, we also show a threefold improvement in spatial resolution over chemically etched fibers. These results show that the bare nanoimprinted near-field probes provide simple access to spectromicroscopy correlated with high resolution topographic mapping and have the potential to advance reproducible fiber-tip-based scanning near-field microscopy.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

DIII-D's role as a national user facility in enabling the commercialization of fusion energy

The path to fusion in the United States requires partnership between public and private sector. While the private sector provides the vigor to take some of the major steps necessary, there is a depth of expertise and capability in the public sector that is vital to resolving feasible approaches. As an open national user facility, DIII-D provides a crucial testbed to develop the required new technologies and approaches in relevant conditions. It has unparalleled potential to meet this challenge, thanks to its extreme flexibility and world leading diagnostics. This provides a basis to rapidly develop solutions that project to future reactors with confidence. The program has thus been redeveloped to enable public and private sector engagement and testing of new concepts. A new technology program has been launched to resolve plasma interacting technologies. With modest heating upgrades, the facility can confront the crucial “Integrated Tokamak Exhaust and Performance” gap, to resolve core, exhaust and technology solutions together. The device is also being redeveloped as a training facility, with dedicated student run time, a mentorship program, and open access to all opportunity roles, part of wider efforts to diversify and open pathways through inclusion, access, and equity. This exciting agenda is enabling scientists and technology researchers to pioneer the solutions needed for a Fusion Pilot Plant (FPP) and ITER this decade. As a national user facility, DIII D has singular potential to provide the tools, teams, and insight necessary, to do its part in moving the United States rapidly toward the commercialization of fusion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Artificial-intelligence-driven shot reduction in quantum measurement

Variational Quantum Eigensolver (VQE) provides a powerful solution for approximating molecular ground state energies by combining quantum circuits and classical computers. However, estimating probabilistic outcomes on quantum hardware requires repeated measurements (shots), incurring significant costs as accuracy increases. Optimizing shot allocation is thus critical for improving the efficiency of VQE. Current strategies rely heavily on hand-crafted heuristics requiring extensive expert knowledge. This paper proposes a reinforcement learning (RL)-based approach that automatically learns shot assignment policies to minimize total measurement shots while achieving convergence to the minimum of the energy expectation in VQE. The RL agent assigns measurement shots across VQE optimization iterations based on the progress of the optimization. This approach reduces VQE's dependence on static heuristics and human expertise. When the RL-enabled VQE is applied to a small molecule, a shot reduction policy is learned. The policy demonstrates transferability across systems and compatibility with other wavefunction Ansätze. In addition to these specific findings, this work highlights the potential of RL for automatically discovering efficient and scalable quantum optimization strategies.

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

Reward based optimization of resonance-enhanced piezoresponse spectroscopy

Dynamic spectroscopies in scanning probe microscopy (SPM) are critical for probing material properties, such as force interactions, mechanical properties, polarization switching, electrochemical reactions, and ionic dynamics. However, the practical implementation of these measurements is constrained by the need to balance imaging time and data quality. Signal to noise requirements favor long acquisition times and high frequencies to improve signal fidelity. However, these are limited on the low end by contact resonant frequency and photodiode sensitivity and on the high end by the time needed to acquire high-resolution spectra or the propensity for sample degradation under high field excitation over long times. The interdependence of key parameters such as instrument settings, acquisition times, and sampling rates makes manual tuning labor-intensive and highly dependent on user expertise, often yielding operator-dependent results. These limitations are prominent in techniques like dual amplitude resonance tracking in piezoresponse force microscopy that utilize multiple concurrent feedback loops for topography and resonance frequency tracking. Here, a reward-driven workflow is proposed that automates the tuning process, adapting experimental conditions in real time to optimize data quality. Furthermore, this approach significantly reduces the complexity and time required for manual adjustments and can be extended to other SPM spectroscopic methods, enhancing overall efficiency and reproducibility.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Learning dynamical systems from data: An introduction to physics-guided deep learning

Modeling complex physical dynamics is a fundamental task in science and engineering. Traditional physics-based models are first-principled, explainable, and sample-efficient. However, they often rely on strong modeling assumptions and expensive numerical integration, requiring significant computational resources and domain expertise. While deep learning (DL) provides efficient alternatives for modeling complex dynamics, they require a large amount of labeled training data. Furthermore, its predictions may disobey the governing physical laws and are difficult to interpret. Physics-guided DL aims to integrate first-principled physical knowledge into data-driven methods. It has the best of both worlds and is well equipped to better solve scientific problems. Recently, this field has gained great progress and has drawn considerable interest across discipline Here, we introduce the framework of physics-guided DL with a special emphasis on learning dynamical systems. We describe the learning pipeline and categorize state-of-the-art methods under this framework. We also offer our perspectives on the open challenges and emerging opportunities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Foreword: Special issue on the U.S. Department of Energy Microreactor Program

This is a foreword for a sponsored Nuclear Technology Special Issue that is focused on the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) Microreactor Program and associated research and development (R&D) activities. Led by Idaho National Laboratory (INL), the DOE-NE Microreactor Program is one of four, national advanced reactor campaigns under the Advanced Reactor Technologies umbrella in the Office of Nuclear Reactor Deployment. The other three national advanced reactor campaigns are focused on Molten Salt, High Temperature Gas, and Fast reactor concepts providing a robust portfolio of national laboratory and university expertise and R&D infrastructure in support of enabling and accelerating commercial deployment of advanced reactor (generally non-light water cooled) concepts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Analysis of AP1000 Small-Break Loss-of-Coolant Accident Using Reactor Transient Simulator

The Westinghouse Electric Company’s Advanced Passive Reactor (AP1000) is characterized by the incorporation of passive safety systems (PSSs) designed to ensure core cooling during transient events. The assessment of PSSs requires evaluation of their performance through a combination of experiments and simulations employing various thermal-hydraulic codes. In addition, detailed evaluation of PSSs for a specific reactor system transient analysis such as loss-of-coolant-accident analysis supports understanding representative integral effects test facility development and the further evolution model development and assessment process. Developing a reactor system code is a complex and time-consuming process that requires significant engineering expertise and effort. It can take several months to even years to complete in the early stages of reactor system design and analysis. However, this process can be expedited through the use of transient simulator models for similar reactor systems, which can be used for lesson learning and training purposes. This study uses the Personal Computer Transient Analyzer (PCTRAN) code. The main advantage of PCTRAN is its ease of use and ability to run faster than real time. This study presents the results obtained for a small-break loss-of-coolant accident (SBLOCA) for two breaks using the full version (licensed) of PCTRAN. The purpose of this investigation is to evaluate the overall system behavior during the postulated SBLOCA event as well as assess the capability of the PCTRAN code to reproduce the system response during transient events. The obtained results were compared with the Westinghouse NOTRUMP system code. The PCTRAN code proved to be reliable in predicting the qualitative behavior of the system in both transient cases. As for the system response, it was found that it is contingent on the activation time of the PSSs. The differences in reactor coolant system pressure between the two codes were attributed to the critical flow model and simplification of mass and energy balance. Despite PCTRAN’s limitations, it can still provide a reasonable prediction of various reactor parameters such as pressure, mass flow rate, and void fraction during a SBLOCA scenario. It is worth noting that PCTRAN currently employs a bulk approach similar to that of the Modular Accident Analysis Program (MAAP) and MELCOR codes. However, the upcoming version of PCTRAN will include an artificial intelligence–based detection and accident prevention system, as well as different models for different reactor components. Consequently, PCTRAN has the potential to be upgraded to match the system thermal-hydraulic codes of the U.S. Nuclear Regulatory Commission and become more widely used in cybersecurity to safeguard nuclear power plants from cyberattacks.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

What Composition of High-Energy Physics Collaborations is Epistemically Optimal?

Computer simulations have recently come to the fore as a crucial tool for studying epistemic dynamics of scientific collectives. One pressing issue in big-ticket, long-term, and crowded particle physics research is the optimal organization of collaborations. This research developed a computation model of collaborations in high-energy physics and performed simulations to investigate the epistemic efficiency of groups and its dependence on the size of such groups and their composition: namely, percentages of pure, partially theoretically competent, and fully theoretically competent experimentalists. The present study reveals that in both small (100-member) and large (3000-member) groups, epistemic payoff as the measure of epistemic efficiency of collaborations is, generally, positively correlated with an increase in both the number of theoretically fully competent and pure (incompetent) experimentalists. Here, we are less certain of such conclusion in the case of the small collaborations. Although the subcommunity of experimentalists who are partially expert is not found to be immediately epistemically beneficial for collaborations, nevertheless they also crucially serve as a transitional community between the theorists and the experimentalists. Predicated on the toy model simulations, I suggest that institutions should provide measures to assist members of the latter subgroup in progressing toward developing a full theoretical expertise.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Incorporating uncertainty for enhanced leaderboard scoring and ranking in data competitions

Data competitions have become a popular and cost-effective approach for crowdsourcing versatile solutions from diverse expertise. Current practice relies on the simple leaderboard scoring based on a given set of competition data for ranking competitors and distributing the prize. However, a disadvantage of this practice in many competitions is that a slight difference in the scores due to the natural variability of the observed data could result in a much larger difference in the prize amounts. In this article, we propose a new strategy to quantify the uncertainty in the rankings and scores from using different data sets that share common characteristics with the provided competition data. By using a bootstrap approach to generate many comparable data sets, the new method has four advantages over current practice. Furthermore, during the competition, it provides a mechanism for competitors to get feedback about the uncertainty in their relative ranking. After the competition, it allows the host to gain a deeper understanding of the algorithm performance and their robustness across representative data sets. It also offers a transparent mechanism for prize distribution to reward the competitors more fairly with superior and robust performance. Finally, it has the additional advantage of being able to explore what results might have looked like if competition goals evolved from their original choices. The implementation of the strategy is illustrated with a real data competition hosted by Topcoder on urban radiation search.

42 ENGINEERING↗
DOE OSTI2026

MCP-enabled agentic AI workflow for building energy modelling: framework and use cases

Traditional building energy modelling workflows remain labor-intensive and error-prone, requiring specialized expertise that limits broader adoption. This paper introduces a novel Model Context Protocol (MCP)-enabled framework that connects AI assistants to EnergyPlus through MCP, a standardized interface for tool invocation and context management. Two complementary integration paradigms are presented and compared: conversational integration, where users interact through natural language while an AI assistant orchestrates MCP tools on demand, and agentic workflow integration, where specialized agents coordinate autonomously to complete multi-step tasks. Using an experimental testbed for residential buildings, the end-to-end workflows are demonstrated. The conversational approach reduced typical inspection and modification tasks from 1-2 h to under 15 min, while maintaining full transparency through visible tool invocations. The agentic approach automated parametric analysis. These demonstrations establish MCP as a foundational layer for AI-assisted building energy modelling, enabling natural language interactions with simulation tools while preserving professional oversight and decision-making authority.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

The 2023 terahertz science and technology roadmap

Abstract Terahertz (THz) radiation encompasses a wide spectral range within the electromagnetic spectrum that extends from microwaves to the far infrared (100 GHz–∼30 THz). Within its frequency boundaries exist a broad variety of scientific disciplines that have presented, and continue to present, technical challenges to researchers. During the past 50 years, for instance, the demands of the scientific community have substantially evolved and with a need for advanced instrumentation to support radio astronomy, Earth observation, weather forecasting, security imaging, telecommunications, non-destructive device testing and much more. Furthermore, applications have required an emergence of technology from the laboratory environment to production-scale supply and in-the-field deployments ranging from harsh ground-based locations to deep space. In addressing these requirements, the research and development community has advanced related technology and bridged the transition between electronics and photonics that high frequency operation demands. The multidisciplinary nature of THz work was our stimulus for creating the 2017 THz Science and Technology Roadmap (Dhillon et al 2017 J. Phys. D: Appl. Phys. 50 043001). As one might envisage, though, there remains much to explore both scientifically and technically and the field has continued to develop and expand rapidly. It is timely, therefore, to revise our previous roadmap and in this 2023 version we both provide an update on key developments in established technical areas that have important scientific and public benefit, and highlight new and emerging areas that show particular promise. The developments that we describe thus span from fundamental scientific research, such as THz astronomy and the emergent area of THz quantum optics, to highly applied and commercially and societally impactful subjects that include 6G THz communications, medical imaging, and climate monitoring and prediction. Our Roadmap vision draws upon the expertise and perspective of multiple international specialists that together provide an overview of past developments and the likely challenges facing the field of THz science and technology in future decades. The document is written in a form that is accessible to policy makers who wish to gain an overview of the current state of the THz art, and for the non-specialist and curious who wish to understand available technology and challenges. A such, our experts deliver a ‘snapshot’ introduction to the current status of the field and provide suggestions for exciting future technical development directions. Ultimately, we intend the Roadmap to portray the advantages and benefits of the THz domain and to stimulate further exploration of the field in support of scientific research and commercial realisation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Future of condensed matter physics for the next 10 years

This perspective outlines a selection of research directions that members of the JPCM editorial board anticipate may shape the frontier of condensed matter physics over the next decade. Rather than a comprehensive review or formal roadmap, this perspective reflects a set of informed views drawn from diverse areas of expertise. Our intention is to spark curiosity, provoke discussion, and encourage readers to imagine—and pursue—the exciting possibilities that lie ahead.

chemical physics↗
DOE OSTI2020

An implementation of the phase-field model based on coupled thermomechanical finite element solvers for large-strain twinning, explicit dynamic fracture and the classical Stefan problem

The implementation of a phase-field model in finite elements usually requires significant expertise and involves the development of a user element with additional degrees of freedom. An alternative implementation of the phase-field model within a thermo-mechanical finite element simulation package was presented in (Cho et al 2012 Int. J. Solids Struct. 49 1973–1992), where the phase-field variable is treated as the temperature degree of freedom. However, this approach has only been used for small strain phase-field modelling of martensitic transformations and quasistatic phase-field modelling of fracture. Here, we present a phase-field finite element implementation via the temperature degree of freedom for several additional cases from the literature: (i) the large-strain phase-field description of deformation twinning presented in (Clayton and Knap 2011 Physica D 240 841–858), (ii) phase-field description of brittle fracture with inertial effects based on the theory from (Molnár and Gravouil 2017, Finite Elem. Anal. Des. 130 27–38) and (Miehe et al 2010 Int. J. Numer. Methods Eng. 83 1273–1311) and (iii) the classical Stefan problem of solidification presented in (Mackenzie and Robertson 2002 J. Comput. Phys. 181 526–544). The last problem involves the temperature and phase-field variables as unknowns.

36 MATERIALS SCIENCE↗