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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Commercial integration of advanced nuclear energy with Artificial Intelligence (AI): Possible implications

The integration of advanced nuclear technologies (both fission and fusion) with artificial intelligence (AI) presents unprecedented national security challenges and opportunities. As fusion energy approaches commercial viability alongside advanced Small Modular Reactors (SMRs), their integration with AI and Artificial General Intelligence (AGI) systems could fundamentally transform the global energy and AI landscapes — two pillars of national security. This document briefly examines how AI could accelerate nuclear energy development and deployment while altering existing power structures, a lot could be done to deepen the discussions. Simultaneously, it observes how nuclear-powered AI may expedite advances toward AGI and beyond. These issues are deeply interconnected and thus need to be examined as a whole and more comprehensively than what’s being summarized here. For instance, AI-powered autonomous operation of nuclear facilities could reduce human error but introduce new cybersecurity vulnerabilities and uncertainties. Further investigation would also address how AI-enhanced nuclear technologies might complicate proliferation concerns through advanced fuel cycle management, nuclear materials production and safeguard. The strategic advantage gained by first entities achieving successful AI-nuclear integration could reshape global and national security framework. Timely analysis of these implications may be crucial for policymakers seeking to harness these technologies' benefits while effectively mitigating their potential risks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

On Theories of Change: Rethinking the Ban Treaty and Disarmament Strategies

A week before Israel bombed Iran’s nuclear facilities, the Director General of the International Atomic Energy Agency (IAEA) Rafael Grossi had lunch with the Financial Times. In the interview, Grossi expressed both optimism and pessimism about the nuclear landscape: he was hopeful about prospects for diplomacy, including with Iran. But he also expressed longer-term concerns about a proliferation cascade and rising nuclear risks, in particular, Russia’s nuclear threats amidst the war in Ukraine. “In the past, this was quite taboo,” he said, “but now people talk about tactical nuclear weapons like something which could be contained or permissible.” Given subsequent events in Iran, along with the expiration of New START in 2026 and expanding nuclear arsenals in Russia and China, pessimism would seem to trump hope for prospects for nuclear disarmament.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
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 OSTI2026

Automated Ride Hailing - Status, Projections, and Critical Safety Review

Automated ride-hailing services, commonly known as 'robo-taxis' are beginning to proliferate and scale. Currently they are available in four major US cities with another 10 cities planning their implementation in the near future. In the US, automated ride-hailing services are dominated by a single provider, with announcements from several competitors of service offerings by end of calendar year 2025. Internationally, only three companies are currently in commercial operations, with many more planned. The scaling of robo-taxi services appears to be the leading application of automated vehicles (AVs), and provides evidence of their anticipated safety in comparison to conventional vehicles. This presentation will provide an overview of the status of deployments of fully operational AVs in ride-hailing services, projections of the number of trips, vehicles, and vehicle miles traveled for the immediate future, and a critical review of the safety data that has been reported, both in the US as well as internationally.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

AI-Ready Data Pilot Project Report

The proliferation of artificial intelligence in scientific research has created an urgent need to define "AI-ready data" for researchers and, more importantly, provide resources to help them produce AI-ready data. At Pacific Northwest National Laboratory, we conducted a pilot study with three data scientists evaluating three CSV datasets from different scientific domains, followed by semi-structured interviews capturing assessment practices. Our findings reveal that AI-readiness evaluation is intuition-based, with practitioners asking "How fast can I go from raw data to my machine learning pipeline?" Data scientists consistently prioritized workflow efficiency, human interpretability, and quality stewardship signals. From these insights, we developed a practical evaluation framework comprising data requirements, metadata standards, and validation tests that provides actionable criteria for producing and curating AI-ready datasets, addressing the gap between theoretical understanding and practical implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Integrated Multi-Fidelity Model and Co-Simulation Platform for Distribution System Transient and Dynamic Analysis—DistribuDyn

As inverter-based, distributed energy resources (DERs) and variable loads continue to proliferate across distribution systems, it is increasingly important to understand their impacts on system stability and reliability. However, most commercially available simulation tools for distribution planning primarily focus on steady-state and quasi-steady state analysis, offering limited capabilities to study transient and dynamic behaviors.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Baseline Hypothetical Facility for the Production of 131 I and 99 Mo using Activation Targets

This report describes a hypothetical facility for production of medical radioisotopes via activation under the Proliferation Resistance and Optimization (PRO-X) program. The facility uses neutron activation of non-special nuclear material (SNM) to produce the medical isotopes 131 I and 99 Mo at a throughput of 60 Ci/week of 131 I and 5 Ci/week of 99 Mo. The hypothetical design was carried out using a 10 MWt research reactor. The precursors used for the activation process were TeO2 for 131 I and MoO 3 for 99 Mo. The processes are performed in 3 hot cells used for target receipt, extraction, purification low specific activity (LSA) generator introduction, and packaging. A fourth hotcell is used for waste processing. The hot cell processing area takes up a footprint of 15.4 m 2 with the total footprint of the facility, including space for administrative offices, non-rad labs, quality assurance, and radiation buffer areas set at 763 m 2 . Waste is produced at a weekly rate of 257.8 g low activity solid waste and 8032.7 mL of low activity liquid waste, 8032 mL of which is water. This baseline hypothetical facility for production of medical isotopes via activation was then compared and contrasted to the hypothetical facility for production of medical isotopes via fission products to show the differences in approach for the two production modes. The two production modes had several highlighted differences including the overall facility and hot cell layout, the type and amount of waste produced by the respective facilities, and economic factors impacting production mode. Finally, a decision tree for which production mode might be more beneficial for an entrant into medical isotope production was developed based on the differences examined and the desired output of medical isotopes desired by the entrant.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Potential of Data Center Controls in Grid Services

The rapid proliferation of large data centers brings both challenges and opportunities for grid reliability. The data center resources and their potential flexibility have the potential to contribute resources to grid operations. Through capabilities like energy shifting and resource coordination, data centers can help reduce their net demand on the transmission network, as well as provide additional grid services to support reliable operation on the grid. While transient and long-term grid planning and operations are the scenarios that draw most attention, the quasi-steady state timeseries (QSTS) operation of data centers and grid bring interesting scenarios that can help evaluate the data center controls to aid grid services. This work is focused on modeling data centers for QSTS applications – incorporating the AI data center load profiles and building on the PNNL digital twin model for the thermal management loads to enable simulation studies to reveal the impact of data center controls on grid performance. This includes the integration of a QSTS battery and natural gas generator model to incorporate local resource impacts to the system. The simulation study is performed with a modified IEEE 24-Bus transmission system. Scenarios are focused on evaluating the data center load impacts on the transmission system and leveraging both data center and local generation controls to mitigate those impacts and provide additional grid services. The data center controls revealed the ability to contribute to two main kinds of grid services: preventing congestion on a weak grid by coordinating the data center resources with the collocated BESS and onsite generation; and the ability to help the grid operations during stressed times of operation like during a contingency. Leveraging these and other capabilities has the potential to help data centers become grid responsive assets, aiding in both their integration into the power system and grid reliability.

power grid simulation↗
DOE OSTI2025

POWER ELECTRONICS GRID TIED SYSTEM FINAL REPORT

Across the country, electric utilities are grappling with the persistent hurdles of integrating Distributed Energy Resources (DERs). Managing these assets safely and effectively is a complex endeavor, complicated by varying ownership structures, management philosophies, and the diversity of the technologies themselves. Consequently, the industry has seen a proliferation of bespoke system designs, control strategies, and communication frameworks—forcing utilities to spend significant time and resources developing one-off integration solutions. This project addressed these integration hurdles through a scalable demonstration of intelligent devices designed to coordinate and control diverse resources in low-voltage applications. This concept minimized the need for complex integration by transforming the separate DERs into a dispatchable virtual power plant (VPP) with integrated resiliency functions (called a Node). By collaborating with a utility partner, the project focused on developing rapidly implementable use cases that bridged the gap between theoretical control and real-world deployment

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Targeting Drugs Against Fibroblast Growth Factor(s)-Induced Cell Signaling

Background:: The fibroblast growth factor (FGF) family is comprised of 23 highly regulatedmonomeric proteins that regulate a plethora of developmental and pathophysiological processes,including tissue repair, wound healing, angiogenesis, and embryonic development. Binding ofFGF to fibroblast growth factor receptor (FGFR), a tyrosine kinase receptor, is facilitated by a glycosaminoglycan,heparin. Activated FGFRs phosphorylate the tyrosine kinase residues that mediateinduction of downstream signaling pathways, such as RAS-MAPK, PI3K-AKT, PLCγ, andSTAT. Dysregulation of the FGF/FGFR signaling occurs frequently in cancer due to gene amplification,FGF activating mutations, chromosomal rearrangements, integration, and oncogenic fusions.Aberrant FGFR signaling also affects organogenesis, embryonic development, tissue homeostasis,and has been associated with cell proliferation, angiogenesis, cancer, and other pathophysiologicalchanges. Objective:: This comprehensive review will discuss the biology, chemistry, and functions of FGFs,and its current applications toward wound healing, diabetes, repair and regeneration of tissues, andfatty liver diseases. In addition, specific aberrations in FGFR signaling and drugs that target FGFRand aid in mitigating various disorders, such as cancer, are also discussed in detail. Conclusion:: Inhibitors of FGFR signaling are promising drugs in the treatment of several types ofcancers. The clinical benefits of FGF/FGFR targeting therapies are impeded due to the activationof other RTK signaling mechanisms or due to the mutations that abolish the drug inhibitory activityon FGFR. Thus, the development of drugs with a different mechanism of action for FGF/FGFRtargeting therapies is the recent focus of several preclinical and clinical studies.

Pharmacology & Pharmacy↗
DOE OSTI2020

Multi-Agent Control of Lane-Switching Automated Vehicles for Energy Efficiency

The proliferation of automatic control systems and their connectivity accents the performance of their interactions. In particular, connected and automated vehicles could become high-impact examples thanks to their energy use and productivity effects. Ideally, a controller might collectively optimize all agents' control moves for a given objective. However, limits on computational complexity, incomplete knowledge of the central planner, and risks of a single point of failure make distributed control attractive as well. This paper proposes a collaborative heuristic to approach the performance of centralized control with decentralized-like computational effort. The related centralized controller is also described in detail and evaluated as a baseline. A collaboration-intensive obstacle avoidance scenario involving electric vehicles is simulated to demonstrate benefits over fully decentralized control. While centralized optimization performed best with an 8.6 % energy reduction, the collaborative decentralized scheme reached a favorable computation-performance tradeoff with a 6.7 % energy reduction.

Dollar, R. Austin↗
DOE OSTI2024

Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024). BC-HRRR's consistency with the legacy WIND Toolkit allows NREL to extend grid integration analysis to 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. As with historical datasets like the WIND Toolkit, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling) both independently and alongside the legacy WIND Toolkit.

Array↗
DOE OSTI2021

A Case Study on Condenser Water Supply Temperature Optimization with a District Cooling Plant

District cooling (DC) continues to proliferate due to increasing global cooling demands and economies of scale benefits; however, most district-scale modeling has focused on heating, and to the best of our knowledge, researchers have yet to model cooling plants featuring waterside economizers in DC settings. With the popular Modelica Buildings library expanding its capabilities to district scale, this study is one of the first to demonstrate how the open-source models can be used for detailed energy and control analysis of a DC plant. For a real-world case study, we developed and calibrated high-fidelity models for a DC system central plant at a college campus in Colorado, USA, and we optimized the condenser water supply temperature (CWST) setpoint for a DC plant across multiple time horizons using the Optimization library in Dymola. Results indicate that annual CWST optimization saves 4.7% annual plant energy, with less than 1% of additional energy savings gained through daily optimization. This confirms previous studies' findings that high frequency CWST optimizations are not necessary for the studied system.

chiller plant↗
DOE OSTI2021

Ser 71 Phosphorylation Inhibits Actin-Binding of Profilin-1 and Its Apoptosis-Sensitizing Activity

The essential actin-binding factor profilin-1 (Pfn1) is a non-classical tumor suppressor with the abilities toboth inhibit cellular proliferation and augment chemotherapy-induced apoptosis. Besides actin, Pfn1 interacts with proteins harboring the poly-L-proline (PLP) motifs. Our recent work demonstrated that both nuclear localization and PLP-binding are required for tumor growth inhibition by Pfn1, and this is at least partially due to Pfn1 association with the PLP-containing ENL protein in the Super Elongation Complex (SEC) and the transcriptional inhibition of pro-cancer genes. In this paper, by identifying a phosphorylation event of Pfn1 at Ser 71 capable of inhibiting its actin-binding and nuclear export, we provide in vitro and in vivo evidence that chemotherapy-induced apoptotic sensitization by Pfn1 requires its cytoplasmic localization and actin-binding. With regard to tumor growth inhibition byPfn1, our data indicate a requirement for dynamic actin association and dissociation rendered by reversible Ser 71 phosphorylation and dephosphorylation. Furthermore, genetic and pharmacological experiments showed that Ser 71 of Pfn1 can be phosphorylated by protein kinase A (PKA). Taken together, our data provide novel mechanistic insights into the multifaceted anticancer activities of Pfn1 and how they are spatially-defined in the cell and differentially regulated by ligand-binding.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A consensus mathematical model of vaccine-induced antibody dynamics for multiple vaccine platforms and pathogens

Introduction: Vaccine platforms used in successful, licensed vaccines have varied among pathogens. However, antibody level is still the main clinical correlate of protection in most approved vaccines. Decisions as to the best vaccine platform to pursue for a given pathogen may be informed through improved understanding of the process of antibody generation and its temporal dynamics, as well as the relationship between these processes and the type of vaccine. Methods: We have analyzed the dynamics of antibody generation for different vaccine platforms against diverse pathogens, and developed a consensus mathematical model that captures antibody dynamics across these diverse systems. Initially, the model was fitted to a rich dataset of antibody and immune cell concentrations in a SARS-CoV-2 vaccine experiment. We then used concepts from machine learning, such as transfer learning, to apply the same model to a variety of systems, involving different pathogens, vaccine platforms, and booster dose use/timing, fixing most parameter values relating to the dynamics of the immune system. Results: The model includes B cell proliferation and differentiation, as well as the generation of plasma cells, which secrete large amounts of antibody, and memory B cells. Overall, the model describes antibody generation in all systems tested well and shows that the main differences across platforms are related to the dynamics of antigen presentation. Discussion: This model can be used to predict antibody generation in pairs of vaccine platform/pathogen, allowing for the use of in silico results to narrow down experimental burden in vaccine development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Insights into regulatory T-cell and type-I interferon roles in determining abacavir-induced hypersensitivity or immune tolerance

Introduction Clinical use of several small molecule drugs may lead to severe T-cell-mediated idiosyncratic drug hypersensitivity reactions (iDHR) linked to HLA alleles, including abacavir (ABC) with HLA-B*57:01. Due to study limitations in humans, pathogenic networks in iDHR remain elusive. HLA transgenic murine models have been proposed to bridge knowledge gaps in tolerance and susceptibility to drugs. Methods Mice expressing HLA-B*57:01 and Foxp3-DTR/EGFP were generated to selectively deplete regulatory T-cells (Treg) with diphtheria toxin. ABC was administered for 8 days alone or together with cell- and cytokine-depleting antibodies. Cellular and transcriptomic responses were analyzed by RNA, flow cytometry and fluorescence methods. Results While CD8 + T-cell responses to ABC require HLA presentation, ABC also triggered mitochondrial stress in macrophagesin vitro, independently of HLA.In vivo, Treg were the primary mechanism of drug tolerance controlling HLA presentation and costimulation by antigen presenting cells. Treg ablation uncovered immune adverse events linked to activation and proliferation of both drug-specific and bystander CD8 + T-cells through CD28-mediated pathways with support from CD4 + non-Treg. Type-I interferon (IFN-I) and cellular-stress pathways influenced the fate of lymph node cells responding to ABC, implicating innate immune cells such as macrophages and plasmacytoid dendritic cells in the development of T-cell responses against the drug. IFN-I and IL-2 were necessary for CD8 + T-cell differentiation and ABC-induced adverse reactions. Conclusions This study unveils novel immune mechanisms driven by drug and host-related factors required forin vivoreactions and sheds light on potential biomarker and therapeutic targets for managing and preventing severe and life-threatening iDHR.

Immunology↗
DOE OSTI2025

Feed status and skin injury modulate immunopathology, global gene expression, and survival in channel catfish during virulent Aeromonas hydrophila infection

Introduction VirulentAeromonas hydrophilais a major pathogen in channel catfish (Ictalurus punctatus), that causes motileAeromonassepticemia and significant economic losses. We investigated the effect of feeding status and skin integrity on the host immune response, disease survival, and gastrointestinal pathology following a vAh challenge. Methods Using a bath immersion model, channel catfish were divided into four treatment groups: fin clipped and fed (FCF), fin clipped but not fed (FCN), not fin clipped but fed (NCF), and not fin clipped nor fed (NCN) alongside non-challenged control groups The FCF and NCF groups were fed 2 h prior to the challenge, but the FCN and NCN groups were not. Survival analysis, histopathological assessment, and RNA sequencing were conducted across groups at different time intervals throughout the vAh challenge. Results Survival rates were lowest in the FCF and FCN groups (30% and 23% survival, respectively), suggesting that both feeding and skin damage contributed to disease severity. Histopathological analyses revealed more severe intestinal and gastric lesions in fed groups, characterized by epithelial necrosis, hemorrhage, and edema. Transcriptomic analysis among the groups identified significant differentially expressed genes associated with inflammation, apoptosis, and metabolic stress, with notable upregulation of interleukin 1-beta (il-1β), and complement C3 (c3). Gene ontology enrichment highlighted distinct immune activation patterns between fed and unfed groups, with enhanced pathogen recognition and pro-inflammatory responses in unfed fish. Discussion These findings suggest feeding prior to infection may exacerbate disease pathology, potentially by creating a physiological state conducive to facilitate pathogen proliferation and dampened early immune responses, whereas short-term fasting appears to promote early immune activation. This study provides novel insights into the complex interplay between feed status, physical injury, and immune response to vAh infection.

Immunology↗
DOE OSTI2021

NEAr Transporter (NEAT) Domains: Unique Surface Displayed Heme Chaperones That Enable Gram-Positive Bacteria to Capture Heme-Iron From Hemoglobin

Iron is an important micronutrient that is required by bacteria to proliferate and to cause disease. Many bacterial pathogens forage iron from human hemoglobin (Hb) during infections, which contains this metal within heme (iron–protoporphyrin IX). Several clinically important pathogenic species within the Firmicutes phylum scavenge heme using surface-displayed or secreted NEAr Transporter (NEAT) domains. In this review, we discuss how these versatile proteins function in the Staphylococcus aureus Iron-regulated surface determinant system that scavenges heme-iron from Hb. S. aureus NEAT domains function as either Hb receptors or as heme-binding chaperones. In vitro studies have shown that heme-binding NEAT domains can rapidly exchange heme amongst one another via transiently forming transfer complexes, leading to the interesting hypothesis that they may form a protein-wire within the peptidoglycan layer through which heme flows from the microbial surface to the membrane. In Hb receptors, recent studies have revealed how dedicated heme- and Hb-binding NEAT domains function synergistically to extract Hb’s heme molecules, and how receptor binding to the Hb-haptoglobin complex may block its clearance by macrophages, prolonging microbial access to Hb’s iron. The functions of NEAT domains in other Gram-positive bacteria are also reviewed.

59 BASIC BIOLOGICAL SCIENCES↗