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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 OSTI2022

DarkQuest: A dark sector upgrade to SpinQuest at the 120 GeV Fermilab Main Injector

Expanding the mass range and techniques by which we search for dark matter is an important part of the worldwide particle physics program. Accelerator-based searches for dark matter and dark sector particles are a uniquely compelling part of this program as a way to both create and detect dark matter in the laboratory and explore the dark sector by searching for mediators and excited dark matter particles. This paper focuses on developing the DarkQuest experimental concept and gives an outlook on related enhancements collectively referred to as LongQuest. DarkQuest is a proton fixed-target experiment with leading sensitivity to an array of visible dark sector signatures in the MeV-GeV mass range. Because it builds off of existing accelerator and detector infrastructure, it offers a powerful but modest-cost experimental initiative that can be realized on a short timescale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Cybersecurity Operational Research, Experimentation, Innovation, and Integration (COREII)

The Department of Energy’s Cybersecurity, Energy Security, and Emergency Response Office (CESER) has partnered with Idaho National Laboratory (INL) and energy companies to develop COREII. This research initiative aims to align with the national cybersecurity strategy, enhance the resilience of critical energy infrastructure, facilitate efforts to improve grid-enhancing technologies (GET) and major effects from other critical and emerging technologies, and to enable discovery of innovative solutions for emerging cybersecurity challenges

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Fusion Energy Sciences Network Requirements Review: Mild-cycle Update

The US Department of Energy (DOE) Office of Science (SC) world-class research infrastructure provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance core DOE mission science for its sponsor SC program and to stimulate a rich discovery and innovation ecosystem. Research communities gather and flourish around each user facility, bringing together diverse perspectives. The continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Federated IRI Science Testbed (FIRST): A Concept Note

The Department of Energy’s (DOE’s) vision for an Integrated Research Infrastructure (IRI) is to empower researchers to smoothly and securely meld the DOE’s world-class user facilities and research infrastructure in novel ways in order to radically accelerate discovery and innovation. Performant IRI arises through the continuous interoperability of research workflows with compute, storage, and networking infrastructure, fulfilling researchers’ quests to gain insight from observational and experimental data. Decades of successful research, pilot projects, and demonstrations point to the extraordinary promise of IRI but also indicate the intertwined technological, policy, and sociological hurdles it presents. Creating, developing, and stewarding the conditions for seamless interoperability of DOE research infrastructure, with clear value propositions to stakeholders to opt into an IRI ecosystem, will be the next big step. Governance, funding, and resource allocation are beyond the scope of this document: it seeks to provide a high-level view of potential benefits, focus areas, and the working groups whose formation would further define the testbed’s design, activities, and goals.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Real-Time Coupling of Geographically Distributed Research Infrastructures: Taxonomy, Overview, and Real-World Smart Grid Applications

Novel concepts enabling a resilient future power system and their subsequent experimental evaluation are experiencing a steadily growing challenge: large scale complexity and questionable scalability. The requirements on a research infrastructure (RI) to cope with the trends of such a dynamic system therefore grow in size, diversity and costs, making the feasibility of rigorous advancements questionable by a single RI. Analysis of large scale system complexity has been made possible by the real-time coupling of geographically separated RIs undertaking geographically distributed simulations (GDS), the concept of which brings the equipment, models and expertise of independent RIs, in combination, to optimally address the challenge. This article presents the outputs of IEEE PES Task Force on Interfacing Techniques for Simulation Tools towards standardization of GDS as a concept. First, the taxonomy for setups utilized for GDS is established followed by a comprehensive overview of the advancements in real-time couplings reported in literature. The overview encompasses fundamental technological design considerations for GDS. The article further presents four application oriented case studies (real-world implementations) where GDS setups have been utilized, demonstrating their practicality and potential in enabling the analysis of future complex power systems.

distributed laboratories↗
DOE OSTI2022

Next generation experimental data access at NSLS-II

The NSLS-II network and computing infrastructure has been significantly updated recently. The re-IP process in 2020-2021 enabled the NSLS-II network to be routable to the rest of the BNL campus. Then, standardization of the operating systems and deployment procedures helped to deliver a consistent environment to workstations and servers used by all NSLS-II beamlines. In particular, the RedHat Enterprise Linux 8 was deployed to 700+ machines using the RedHat Satellite infrastructure management product, and all critical services (IOCs, databases, etc.) were migrated to the new OS. NFS users’ home directories are consistent across all of the machines, which eliminates the need for the individual configuration of the user environment on each host. The standard suite of software packages is available to the beamline staff and users, which includes the system packages (deployed via RPM) as well as the conda environments for data acquisition and analysis. Security measures were implemented to comply with the industry standards, which include multi-factor authentication (using Duo), secure screen lock for the beamline machines, and advanced access control to the experimental data that is stored in shared central storage available on all hosts. These major enhancements facilitated sharing the experimental data (currently for a number of selected beamlines, with a plan to extend it to the whole facility in the nearest future) with the users via an externally facing JupyterHub instance. The beamlines keep using the Bluesky data acquisition framework to orchestrate their experiments, and the new infrastructure enabled them to use a next-generation data access library called tiled.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Membrane lipids drive formation of KRAS4b-RAF1 RBDCRD nanoclusters on the membrane

The oncogene RAS, extensively studied for decades, presents persistent gaps in understanding, hindering the development of effective therapeutic strategies due to a lack of precise details on how RAS initiates MAPK signaling with RAF effector proteins at the plasma membrane. Recent advances in X-ray crystallography, cryo-EM, and super-resolution fluorescence microscopy offer structural and spatial insights, yet the molecular mechanisms involving protein-protein and protein-lipid interactions in RAS-mediated signaling require further characterization. This study utilizes single-molecule experimental techniques, nuclear magnetic resonance spectroscopy, and the computational Machine-Learned Modeling Infrastructure (MuMMI) to examine KRAS4b and RAF1 on a biologically relevant lipid bilayer. MuMMI captures long-timescale events while preserving detailed atomic descriptions, providing testable models for experimental validation. Both in vitro and computational studies reveal that RBDCRD binding alters KRAS lateral diffusion on the lipid bilayer, increasing cluster size and decreasing diffusion. RAS and membrane binding cause hydrophobic residues in the CRD region to penetrate the bilayer, stabilizing complexes through β-strand elongation. These cooperative interactions among lipids, KRAS4b, and RAF1 are proposed as essential for forming nanoclusters, potentially a critical step in MAP kinase signal activation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Integrated Research Infrastructure Architecture Blueprint Activity (Final Report 2023)

The complexity of scientific pursuits is increasing rapidly with aspects that require dynamic integration of experiment, observation, theory, modeling, simulation, visualization, machine learning (ML), artificial intelligence (AI), and analysis. Research projects across the Department of Energy (DOE) are increasingly data and compute intensive. Innovative research teams are accelerating the pace of discovery by using high-performance computational and data tools in their research workflows and leveraging multiple research infrastructures. Additionally, several recent high-level U.S. government reports underscore the necessity of a new advanced computing ecosystem for international competitiveness and national security. International competitors are moving forward with major research infrastructure integration efforts that seek to capture a competitive advantage in the global innovation race. Owing to its unparalleled constellation of world-class experimental and observational facilities and high-performance and extreme-scale computational, data, and networking infrastructure, DOE is positioned to be a global leader in this new era of integrated science. However, this new integration paradigm will demand continuing evolution to ensure the U.S. remains a global leader in research and innovation. The DOE Office of Science (SC) has seized on the strategic importance of integration and has adopted a vision for Integrated Research Infrastructure (IRI): To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation. To respond to the evolving computational requirements of research and the competitive international innovation landscape, experimental facilities could be connected with high performance computing resources for near real-time analysis, and resources should be provided for merging enormous and diverse data for AI/ML techniques and analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

National Ignition Facility. Facility and Infrastructure Systems Maintenance Plan

Ensuring the reliability of the NIF, including its support systems, laser systems, target diagnostic systems, and utilities, is essential to the availability of the NIF in its support of NNSA missions. NIF is a key capability in the DOE Stockpile Stewardship Program and supports high energy physics experiments for nuclear weapons, energy, and astrophysics applications. High system reliability provides opportunities for shots and scientific discoveries with opportunities to enhance and upgrade capabilities. This Maintenance Plan (MP) identifies the policies and procedures used to perform and support asset management of the NIF Facility and Infrastructure Systems (FInS), NIF Lasers & Alignment (LASE), NIF Target Experimental Operations (TOPS), NIF Target Area Science and Engineering (TASE), and NIF&PS Control Systems (NCS). The FInS systems include the facility, HVAC, contamination control, beampath, and Line Replaceable Units (LRUs) as well as utilities which create the beampath environments, such as vacuum, argon, or clean dry air. The LASE systems are Programmatic systems which include laser diagnostics, alignment, power conditioning, pulsed power, and input laser systems. The TOPS and TASE systems are also Programmatic systems which include target and diagnostic delivery systems and positioners, many different insertable and fixed target diagnostics, and cryogenic and target gas fill systems. Finally, the NCS systems include both software and hardware for industrial and shot operation control systems. Policies governing administrative and operational practices related to maintenance of FInS, LASE, TOPS, TASE, and NCS systems are described in this plan. In addition, the plan provides processes and procedures for managing, tracking, and documenting the work. This document, the NIF Operations Management Plan, NIF-5020544 (Ref. 1), and NIF Shot Operations Plan, NIF-5018506 (Ref. 2), together satisfy the requirements of the Conduct of Operations. Duties, responsibilities, and reporting requirements of the various positions associated with FInS, LASE, and TOPS maintenance are detailed in this plan. The FInS systems include both Real Property systems with asset management requirements specified in DOE Order 430.1C (Ref. 3) and Programmatic systems. In addition, for FInS, there is a list of the System Level Maintenance Plans (SLMPs) in NIF-1007419198 (Ref. 4) which provide the system descriptions and maintenance plan and schedule. In addition, the list includes the Reliability Centered Maintenance (RCM) and Experience Centered Maintenance (ECM) evaluations that have been performed for applicable FInS systems as well as reliability criticality per Section 3.5. The -AM version of the NIF Maintenance Plan focuses on the reliability program for FInS, LASE, TOPS, TASE, and NCS within the context of the overall NIF Reliability, Availability, and Maintainability (RAM) program and incorporates changes since the -AL version from August 2011 and has been updated to be fully consistent with the updates to Ref. 1. It also includes asset management considerations, updates to the Work Order (WO) process within the NIF Computerized Maintenance Management System (CMMS) which is EAM infor® System Maintenance and Reliability Tracking (SMaRT) (Ref. 5), and updates to metrics and key performance indicators (KPIs).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Synchrophasors-based Master State Awareness Estimator for Cybersecurity in Power Grid: Testbed Implementation & Field Demonstration

The integration of distributed energy resources(DERs) and expansion of complex network in the distribution grid requires an advanced distributed state estimator to monitor the grid health at micro-level. The distribution state estimator will improve the situational awareness and resiliency of distributed power system. This paper proposes a synchrophasors-based master state awareness (MSA) estimator to enhance the cybersecurity in distribution grid by providing a real-time estimation of system operating states to control center operators. In this paper, the proposed MSA estimator utilizes only phasor measurements, bus magnitudes and angles, from phasor measurement units (PMUs),deployed in local substations, to estimate the system states and also detects data integrity attacks, such as load tripping attack that disconnects the load. To validate the proof of concept, we implement the proposed methodology in cyber-physical testbed environment at the Idaho National Laboratory (INL) Electric Grid Security Testbed. Further, to address the “valley of death” and support technology commercialization, field demonstration is also performed at the Critical Infrastructure Test Range Complex(CITRC) at the INL. Our experimental results reveal a promising performance in detecting load tripping attack and providing an accurate situational awareness through an alert visualization dashboard in real-time

42 ENGINEERING↗
DOE OSTI2022

FY2022 Progress Report for Advanced Re-fabrication/Re-instrumentation Capability Development

In support of performing follow-on irradiation experiments with previously irradiated materials, the Halden Reactor Project developed unique and state of the art capabilities to refabricate and re-instrument previously irradiated materials. Such materials were used in in-pile tests at the Halden reactor, and out-of-pile tests for example using furnaces as a heat source. The decision to close the Halden Reactor Project results in the loss of this refabrication and re-instrumentation capability. As a result, the United States (U.S.) Department of Energy (DOE) has determined to develop refabrication and re-instrumentation capability at the unique shielded facilities at Idaho National Laboratory (INL). The development of refabrication capability has been completed and demonstrated. This report focuses on the complementary aspects of reinstrumentation and the progress to-date. Halden spent nearly 30 years developing both refabrication and re-instrumentation. Collaboration with Halden is allowing Idaho National Laboratory (INL) to develop this capability much more rapidly. In FY-21 the results include development of the capability to drill annular center holes in ceramic UO2 fuel pellets, development of fuel rod end caps with feedthroughs for centerline instrumentation inside the rodlet, The procurement of both fuel drilling and welding demonstration equipment from Halden, evaluation of surface thermocouple attachments to support better understanding of temperature measurement uncertainties, and finally, the conceptual design of a new shielded enclosure where advanced refabrication and re-instrumentation equipment can be housed. In FY-22, the results include; Completing set up of the drilling and welding modules procured from Halden, and early experimental trials using that equipment.; Completing set up of an out-of-cell circumferential weld system to allow for further weld development to take place and support fabrication of fuel for fresh fuel experiments.; Evaluation of the Hot Fuel Examination Facility (HFEF) infrastructure to support future installation of advanced re-fabrication/re-instrumentation equipment, specifically related to necessary infrastructure for cryo-drilling.; Developments in dry-drilling alternative. Including experimental studies showing cordierite is the most suitable surrogate for UO 2 for performing drilling studies. That drilling performance is enhanced when a fuel-clad bonding condition is simulated.; Conceptual design completed for attaching surface thermocouples to irradiated fuel in support of TWIST capsule experiments. The authors would like to thank the numerous colleagues at INL and Halden who provided support in accomplishing this work. Their support both material and intellectual is invaluable in advancing the state of the art and establishing the capabilities for refabrication and re-instrumentation at INL.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

DSI Python API Demo May 2023 [Slides]

Data Science Infrastructure (DSI) is developing searchable databases and workflows for simulation and experimental data derived from ASC clients. Short term goal: Make data easily accessible through metadata indexing and querying while respecting data permissions. Longer term goal: Use this data for data science activities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Open Source Platform for Live Processing of High Data Rate Electron Microscopy (SBIR Phase I Award Topic 15, Subtopic B, Final Scientific / Technical Report)

4D scanning transmission electron microscopy (STEM) is experiencing a revolution both in terms of data size, and data veracity, as are many other areas of experimental data acquisition. This presents enormous opportunities to make new scientific discoveries, but is also hamstrung by aging software that is no longer fit for purpose. Experimental data acquisition platforms must make the same investments in software infrastructure that the simulation community made decades ago to take advantage of high-performance computing (HPC) if they hope to realize the full potential of the latest advances made in detector technology. This requires rethinking the design and deployment of hardware, moving away from small, fixed commodity computing capabilities with closed interfaces to open, modular, scalable systems designed for parallelism and throughput. The technical approach will leverage best-in-class open source technologies, and develop new approaches strategically to build an open source platform for experimental data acquisition targeting high data rate electron microscopy. The project will develop a software platform that uses the power and performance of modern HPC resources to ingest the large volume of data produced by electron microscopes using direct electron detectors. A set of configurable pipelines will be used to enable the processing to be tailored to the problem being investigated with builtin visualization of data at interactive rates. This project will leverage investments made by the DOE and other agencies to provide a powerful software platform for the experimental data community working with most powerful electron microscopes, such as 4D STEM detectors. It will create a platform that serves as a reference for the community. Permissive open source licensing will make the platform available to all, with a simple deployment strategy offering the ability to keep data close to where it is generated. This advanced software platform will require customization for each deployment, creating opportunities for software services that are typically offered to extend open source software platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Secure API-Driven Research Automation to Accelerate Scientific Discovery

The Secure Scientific Service Mesh (S3M) provides API-driven infrastructure to accelerate scientific discovery through automated research workflows. By integrating near real-time streaming capabilities, intelligent workflow orchestration, and fine-grained authorization within a service mesh architecture, S3M enables secure and flexible programmatic access to high performance computing (HPC) resources. This framework allows intelligent agents and experimental facilities to dynamically provision resources and execute complex workflows, accelerating experimental lifecycles, and enabling AI-augmented autonomous science. S3M establishes a modern foundation for scientific computing infrastructure that significantly reduces traditional barriers between researchers, computational resources, and experimental facilities.

Skluzacek, Tyler [ORNL] (ORCID:0000000322424931)↗
DOE OSTI2026

Advancing specialized biofoundries via automated adaptive laboratory evolution

Adaptive laboratory evolution (ALE) is a powerful strategy for improving microbial phenotypes by harnessing natural selection under defined environmental conditions. Through applying selection regimes, beneficial mutations accumulate, enabling the generation of strains with enhanced properties. However, conventional ALE is labor-intensive and difficult to scale, limiting reproducibility and broader discovery of evolutionary principles. Recent advances in robotics, automation, and computational infrastructure are transforming ALE into a scalable, data-rich experimental paradigm. Automated platforms enable standardized and complex protocols, real-time monitoring, and highly parallel evolution campaigns, improving consistency while generating longitudinal datasets that reveal convergent adaptive mechanisms. Here, we discuss the role of specialized biofoundries in advancing automated ALE and enabling large-scale evolutionary engineering. We review major automated ALE formats and outline key design principles for effective ALE biofoundries, highlighting how automated ALE can support autonomous experimentation and AI-guided strain engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Intrinsic self-stressing and low carbon Engineered Cementitious Composites (ECC) for improved sustainability

Highlights: • A self-stressing criterion for ECC was established and experimentally verified. • An intrinsic self-stressing ECC was developed by utilizing LC3 and CSA cement. • Initial maximum expansion and later expansion loss were successfully tailored. • Expansion mechanism was identified by XRD patterns. • Self-stressing ECC has 64% of the carbon footprint of conventional concrete. Engineered Cementitious Composites (ECC) is an emerging cementitious composite material with ultra-high ductility. However, its higher cement dosage limits its material greenness and leads to concerns with drying shrinkage. In this research, an ECC utilizing limestone calcined clay cement (LC3) and calcium sulphoaluminate cement (CSA) is investigated, focusing on minimizing the material's embodied carbon while enhancing its durability with intrinsic self-stressing functionality. A self-stressing criterion is theoretically established and experimentally verified. X-ray diffraction patterns reveal an ettringite quantity that modulates the initial expansion and later expansion-reversal of LC3-CSA-ECC to support a persistent self-stressing mechanism. LC3-CSA-ECC has a lower (64%) carbon footprint and similar embodied energy compared to conventional concrete. When combined with the durability advantage (tiny crack, high ductility of 5.5%, and self-stressing function), this low carbon self-stressing ECC holds promise as a sustainable repair material that lowers the embodied and operational carbon in civil infrastructure.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Provenance infrastructure for multimodal x-ray experiments and reproducible analysis

Exploring relationships between material structures and desired properties for material discovery and synthesis requires mining machine-readable databases and linking experimental data with sufficiently rich annotations. There are vast gaps both in these data sources and in the connections between them. We present a provenance-based data management and analysis framework that enables capturing, persisting, and reanalyzing experimental data from the BNL National Synchrotron Light Source II (NSLS-II). Our system leverages NSLS-II Bluesky for experimental data acquisition, captures analysis parameters, and enriches the search space with results from the scientific literature. We describe in detail the challenges and benefits of data-driven approaches when comparing computational and experimental data, such as the multiple possible scenarios of interest in often ill-posed inverse problems and missing data. Our infrastructure utilizes the NSLS-II event model and includes discovery mechanisms across multiple beamlines. A text and data mining module using natural language processing classification techniques extracts relevant information from the literature that is added to data sources. We describe a provenance acquisition and analysis rerun workflow based on a directed acyclic graph that keeps track of process and data provenance and allows to replay analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

NRIC FY 2025 Collaboration Initiatives Annual Report

The National Reactor Innovation Center (NRIC) is a national program established by the U.S. Department of Energy (DOE) in 2019 and led by Idaho National Laboratory (INL). Its mission is to work with industry and national laboratories to bridge the gap between concept, demonstration, and commercialization of advanced nuclear technology. NRIC works to inspire stakeholders and the public, empower innovators, and deliver successful outcomes through efficient collaboration and coordination with partners. NRIC is partnered with industry to accelerate the demonstration and deployment of advanced nuclear technology using DOE’s national laboratory infrastructure and expertise. NRIC’s vision is to establish four new experimental facilitates and two large reactor test beds for integrated technology demonstrators and experimentation by 2028 and complete two advanced nuclear technology tests by 2030.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗