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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The state of algal genome quality and diversity

The genomic era of biology has created unprecedented opportunity to study how life works, including understanding evolutionary principles, bioprospecting for novel antibiotics, and genetic manipulation of bioeconomically-relevant species. While genome sequencing and genomic analysis was previously restricted to large-scale projects and consortia, sequencing has become democratized. However, as genomics has become commonplace, the cataloging of sequenced organisms has become challenging, and standardized practices for sequencing, assembly, and annotation have not been adopted. This is equally true in research fields such as algal biology, despite the growing importance of algae in a bio-based economy. Here, in this study, we provide a comprehensive review of the state of eukaryotic algal genomics, explore the quality of algal genome assemblies, and identify the biases and gaps in the current species distribution to inform the development of future genome projects. Overall, we find a trend of declining quality of genomic resources, including a reduction in assembly quality, gene annotation quality, and genome completeness. Potential solutions to improve genome quality include widespread utilization of long read and scaffolding technologies, implementation of standards for assembly quality, evidence-based gene annotation and requisite publication, and support of continued development of gene prediction and genome assessment software.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Theoretical study of intrinsic defects in cubic silicon carbide 3C-SiC

Using the local moment counter charge (LMCC) method to accurately represent the asymptotic electrostatic boundary conditions within density functional theory supercell calculations, we present a comprehensive analysis of the atomic structure and energy levels of point defects in cubic silicon carbide (3C-SiC). Finding that the classical long-range dielectric screening outside the supercell induced by a charged defect is a significant contributor to the total energy. we describe and validate a modified Jost screening model to evaluate this polarization energy. This leads to bulk-converged defect levels in finite size supercells. With the LMCC boundary conditions and a standard Perdew-Burke-Ernzerhof (PBE) exchange correlation functional, the computed defect level spectrum exhibits no band gap problem: the range of defect levels spans ~2.4 eV, an effective defect band gap that agrees with the experimental band gap. Comparing with previous literature, our LMCC-PBE defect results are in consistent agreement with the hybrid-exchange functional results of Oda et al. [J. Chem. Phys. 139, 124707 (2013)] rather than their PBE results. The difference with their PBE results is attributed to their use of a conventional jellium approximation rather than the more rigorous LMCC approach for handling charged supercell boundary conditions. The difference between standard dft and hybrid functional results for defect levels lies not in a band gap problem but rather in solving a boundary condition problem. The LMCC-PBE entirely mitigates the effect of the band gap problem on defect levels. The more computationally economical PBE enables a systematic exploration of 3C-SiC defects, where, most notably, we find that the silicon vacancy undergoes Jahn-Teller-induced distortions from the previously assumed T d symmetry, and that the divacancy, like the silicon vacancy, exhibits a site-shift bistability in p -type conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Production of Carbon Nanomaterials and Sorbents from Domestic U.S. Coal (Final Report)

The main goal of this project was to produce high-value carbon nanomaterials and carbon sorbents from domestic coal resources in a cost-effective manner. Four types of domestic coal samples were processed through a combination of deashing, devolatilization, oxidation, reduction, and activation treatments to produce graphene oxide (GO), reduced graphene oxide (RGO), and activated carbon (AC). The precursors and developed materials were extensively characterized by various methods to investigate the impact of the coal feedstock type on the yield and quality of each product. A commercial graphite-based GO sample was included in the experimental work as the baseline material for comparison with the coal-based materials developed in this work. The performed work also included a technoeconomic analysis and cost estimation for a plant processing 20 tons/day coal, a market evaluation for the graphene materials, and a technology gap analysis. A simple process by concentrated nitric acid oxidation is used to oxidize coal precursors for the production of GO. Fine oxidized coal particles that were separated from larger oxidized coal particles had significantly higher oxygen contents and were identified as coal-based GO samples. Coarse oxidized coal particles were used as precursors for production of AC. Based on the Raman spectroscopy results, coal-based GO samples exhibited G and D bands similar to those of graphite-based GO samples. X-ray photoelectron spectroscopy revealed that coal-based GO samples had surface oxygen contents of ~26-35% that were higher than the oxygen contents of graphite-based GO samples. Larger particles of oxidized coal samples were activated under different conditions to produce high surface area functionalized AC. Prepared materials had surface areas exceeding 1,500 m 2 /g and pore volumes more than 1 cm 3 /g with different pore size distributions. Reduced graphene oxide samples were prepared by thermal reduction of both coal-based and graphite-based GO samples at 170-2800 ºC. Coal-based and graphite-based RGO samples exhibited similar carbon contents, Raman spectra, and XRD profiles. Heat treatment above 1500 ºC shifted RGO to synthetic graphite. Among anthracite, bituminous, subbituminous, and lignite coals tested, anthracite was the best precursor to produce carbon nanomaterials exhibiting properties similar to those of graphite-based materials. Anthracite-based carbon nanomaterials also had the highest production yields. Technoeconomic analysis estimated the production cost of GO and RGO for anthracite-based samples at about 2,600 and 4,200 $/ton, respectively, which is about two orders of magnitude lower than the current estimated price of graphite-based materials. Several gaps to further develop the proposed technology were identified and discussed that include process and equipment optimization, process integration, need for additional bench- and pilot-scale experiments, and other items to reduce the scale up risk. Market analysis reports suggested a compound annual growth rate of 40% for graphene and related materials. Short-term applications include composites, inks, and coatings. However, energy storage applications appear to be the dominant potential long-term applications. Different applications of coal-based GO and RGO need to be explored and clear metrics and standards for each application need to be developed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

EnergyPlus Model Context Protocol Server (EnergyPlus-MCP) v0.1

EnergyPlus-MCP is the first open-source Model Context Protocol server specifically designed for EnergyPlus building energy simulation. This innovative software enables AI assistants and other applications to interact programmatically with EnergyPlus through a standardized, secure interface, eliminating traditional technical barriers in building energy modeling. The software provides specialized tools across five functional domains: server management, model configuration and loading, comprehensive building component inspection, systematic model modification, and simulation execution with results visualization. Key features include automated HVAC system discovery and topology mapping, advanced schedule analysis, intelligent model validation, and interactive visualization capabilities. EnergyPlus-MCP's layered architecture ensures robust separation between protocol communication and domain expertise, enabling scalable deployment across organizations, educational institutions, and research teams. Unlike direct LLM approaches that suffer from inconsistent results and security gaps, EnergyPlus-MCP provides validated, reliable interactions while maintaining scientific rigor. This democratizes sophisticated building energy analysis, making EnergyPlus accessible to broader audiences through conversational interfaces and streamlined workflows.

Li, Han [Lawrence Berkeley National Laboratory (LB↗
DOE OSTI2020

ZPPR-15 Criticality Measurements

A reference critical configuration was established for each phase of the ZPPR-15 experimental program. The reference critical configuration for each phase corresponds to a configuration in which the measured excess reactivity was adjusted to a standard set of reporting conditions with an average reactor temperature of 293 K, a zero interface gap and all operational control rods parked 30 inches from the axial centerline of the core. The ZPPR staff published the measured excess reactivity and the statistical uncertainty in the measurement. In reality, the published uncertainty for each reference critical configuration is only a small component of the total uncertainty for that configuration. Additional uncertainties related measurement technique, configuration geometry and material compositions exist. The geometry and material composition uncertainties are the dominant uncertainties for ZPPR-15. A full uncertainty analysis was performed for each ZPPR-15 reference critical configuration. The significant uncertainties related to measurement technique, configuration geometry and material compositions were quantified, and a total uncertainty was derived for each reference critical configuration. The ZPPR-15 experimental records were used to create detailed as-built Monte Carlo models for the reference critical configurations established in ZPPR-15A loading 15, ZPPR-15B loading 88, ZPPR-15C loading 166 and ZPPR-15D loading 185. The as-built models neglect the small, non-uniform gap between matrix halves at full closure, any structures outside the matrix tubes and minor components, e.g., impurities, in some materials. The biases associated with the neglected items were quantified. The experimental value of keff and its associated uncertainty for each reference critical configuration were adjusted to account for biases introduced by items that are neglected in the as-built model for that configuration.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2022

Automation & Autonomy Standards and Guidelines for Space Vehicles

The NASA Office of the Chief Health and Medical Officer (OCHMO) requested HRP conduct a survey of industry and government standards and guidelines for the interaction of automation/autonomy with humans. Guidance for verification testing of human-automation designs was also requested. A rapid response was requested so that the deliverables could be provided as part of a future NASA solicitation for automated systems for HLS. The project began with a broad review and analysis of prior NASA work in this area, as well as external standards related to human interaction with automation/autonomy. The team reviewed approximately 200 documents, and interviewed multiple industry and government subject matter experts (SMEs). “Gold standard” documents were selected for focus and key categories were identified. A cross-walk of standards was created, and common standards and guidelines were selected and rephrased (where necessary) to be information-rich, concise, and usable. Verification guidelines and examples were also developed. The final report includes an introduction to automation and autonomy, selected standards and guidelines, verification method guidance, and research gaps. In addition to the report, the team delivered a list of candidate standards for autonomous vehicles, as well as a list of candidate standards for a future NASA-STD-3001 update on automation/autonomy. The presentation will describe the rapid response project approach and methods, examples of standards and guidelines identified and delivered to OCHMO, and research needed to develop additional automation/autonomy design guidance where gaps currently exist.

automation↗
DOE OSTI2024

Review and Gap Analysis of Heliostat Components and Controls

This investigation provides a comprehensive literature review pertaining to heliostat components and controls as part of the U.S. Department of Energy (DOE), Heliostat Consortium (Heliocon) program. Here, this work presents a detailed assessment of subcomponents, controls and wireless communications elements that comprise various designs of helisotats within concentrating solar power (CSP) installations. Additionally, this work also provides the results of an industry survey, intended to compliment the literature discussion, to provide a gap analysis of the primary technology and cost areas that need to be addressed to help improved to spur concentrating solar power (CSP) bankability. Although the results of the study determined several key areas for development, three strategic areas identified were: (1) the use of advanced composite materials to replace a need for expensive steel within the structure and mirror substrate, (2) employment of closed-loop controls for automated calibration, reduction of commissioning time and O&M hours, reduction of drive requirements, as well as overall cost reduction, and (3) the need for more Heliostat-centric codes and standards to facilitate engineering confidence in the development of new features, cost reductions, or other design iterations to be seamlessly introduced without optical performance problems.

14 SOLAR ENERGY↗
DOE OSTI2023

Indoor Occupancy Sensing via Networked Nodes (2012–2022): A Review

In the past decade, different sensing mechanisms and algorithms have been developed to detect or estimate indoor occupancy. One of the most recent advancements is using networked sensor nodes to create a more comprehensive occupancy detection system where multiple sensors can identify human presence within more expansive areas while delivering enhanced accuracy compared to a system that relies on stand-alone sensor nodes. The present work reviews the studies from 2012 to 2022 that use networked sensor nodes to detect indoor occupancy, focusing on PIR-based sensors. Methods are compared based on pivotal ADPs that play a significant role in selecting an occupancy detection system for applications such as Health and Safety or occupant comfort. These parameters include accuracy, information requirement, maximum sensor failure and minimum observation rate, and feasible detection area. We briefly describe the overview of occupancy detection criteria used by each study and introduce a metric called “sensor node deployment density” through our analysis. This metric captures the strength of network-level data filtering and fusion algorithms found in the literature. It is hinged on the fact that a robust occupancy estimation algorithm requires a minimal number of nodes to estimate occupancy. This review only focuses on the occupancy estimation models for networked sensor nodes. It thus provides a standardized insight into networked nodes’ occupancy sensing pipelines, which employ data fusion strategies, network-level machine learning algorithms, and occupancy estimation algorithms. This review thus helps determine the suitability of the reviewed methods to a standard set of application areas by analyzing their gaps.

Emad-Ud-Din, Muhammad (ORCID:0000000279515538)↗
NASA NTRSDate not supplied

Training and Validation of Spectral Gap Filling Algorithm for Cpf-Ceres Intercalibration

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission is set to launch an SI-traceable reflective solar (RS) spectrometer aboard the International Space Station to measure Earth-reflected solar radiation with a radiometric uncertainty of 0.3% (k=1). The CPF intercalibration team has devised a cutting-edge methodology to accurately transfer the benchmark CPF calibration reference to the shortwave (SW) channel (200-5000 nm) of the Clouds and the Earth’s Radiant Energy System (CERES) instrument. The spectral range of CPF measurements spans from 350-2300 nm, while the CERES SW channel measures the Earth-reflected broadband solar radiances between 200 nm to 5 μm. To conduct precise CPF-CERES intercalibration analysis, the CPF-like spectral radiances outside the CPF spectral range need to be estimated to match the CERES SW spectral range. In response, the team has developed a fast algorithm that leverages spectrally redundant information within the CPF-measured portion through principal component analysis (PCA) and utilizes pre-established spectral correlation relationships among wavelengths to extend the CPF spectrum below 350 nm and above 2300 nm. Our results show that the algorithm achieves excellent accuracy in generating the missing energy in the UV and IR portions. The RMS error in the UV region is less than 4.5x10-3 W/m2/sr/nm, while in the IR region, it is smaller than 8x10-5 W/m2/sr/nm. Our methodology was validated using measured EMIT radiance data, which covers the spectral range from 0.381 μm to 2.493 μm. We employed EMIT radiances within the wavelength range of 0.43 – 2.25 μm to generate radiances for both the shorter wavelength range (0.381 – 0.43 μm) and longer wavelength range (2.25 – 2.493 μm). The generated radiances agree very well with the measured EMIT radiances. The standard deviation in the integrated broadband radiances was about 0.1%, and the bias is less than 0.004% for over 1.5 million EMIT measured samples. These statistics show that the spectral gap filling algorithm is robust and effective in substantially reducing the spectral difference-induced uncertainty in the CPF-CERES intercalibration samples.

Qiguang Yang↗
DOE OSTI2026

Plant Bioengineering Atlas: A Knowledge Graph of Genes, DNA Constructs, and Plant Traits.

Plant bioengineering has generated tens of thousands of genotype-to-phenotype relationships, but this knowledge remains fragmented across narrative literature and difficult to use computationally. Inconsistent descriptions of DNA constructs, host species, and traits, including variable species names, omitted regulatory elements, and inconsistent gene symbols, impede data reuse, comparative analysis, and design-build-test-learn cycles. Here, we present the Plant Bioengineering Atlas, a literature-mined, ontology-grounded knowledge base assembled using an artificial intelligence (AI)-aided extraction pipeline. A large language model parsed open-access primary research articles to generate structured, provenance-anchored records of engineered genes, modification types, promoter-gene-terminator constructs, host species, target traits, and reported phenotypes, with every record traceable to its source. The current release contains 14,358 curated records encompassing 6,998 distinct genes across 436 plant species from 6,452 papers published between 2000 and 2026. Corpus analysis reveals that experiments are concentrated in a small group of model and crop species, disease and pathogen resistance is the most frequently engineered trait class, and constitutive regulatory parts (particularly the CaMV 35S promoter and NOS terminator) remain pervasive. Two in five records omit one or both flanking regulatory elements (i.e., promoter and terminator), while only 23.4% describe cassettes in which both elements resolve to named part classes, exposing a systematic reproducibility gap. We organize these data into a knowledge graph linking genes, constructs, species, and traits; provide access through an interactive web portal; and propose an AI-compatible documentation standard for AI-ready reporting. The Plant Bioengineering Atlas provides a foundation for data-driven hypothesis generation and AI-aided plant biodesign.

, Genes, DNA Constructs↗
DOE OSTI2023

DEEPEN Global Standardized Categorical Exploration Datasets for Magmatic Plays

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be developed for use in the weighted sum of the different favorability index models produced from geoscientific exploration datasets. This was done using two different approaches: one based on expert opinions, and one based on statistical learning. This GDR submission includes the datasets used to produce the statistical learning-based weights. While expert opinions allow us to include more nuanced information in the weights, expert opinions are subject to human bias. Data-centric or statistical approaches help to overcome these potential human biases by focusing on and drawing conclusions from the data alone. The drawback is that, to apply these types of approaches, a dataset is needed. Therefore, we attempted to build comprehensive standardized datasets mapping anomalies in each exploration dataset to each component of each play. This data was gathered through a literature review focused on magmatic hydrothermal plays along with well-characterized areas where superhot or supercritical conditions are thought to exist. Datasets were assembled for all three play types, but the hydrothermal dataset is the least complete due to its relatively low priority. For each known or assumed resource, the dataset states what anomaly in each exploration dataset is associated with each component of the system. The data is only a semi-quantitative, where values are either high, medium, or low, relative to background levels. In addition, the dataset has significant gaps, as not every possible exploration dataset has been collected and analyzed at every known or suspected geothermal resource area, in the context of all possible play types. The following training sites were used to assemble this dataset: - Conventional magmatic hydrothermal: Akutan (from AK PFA), Oregon Cascades PFA, Glass Buttes OR, Mauna Kea (from HI PFA), Lanai (from HI PFA), Mt St Helens Shear Zone (from WA PFA), Wind River Valley (From WA PFA), Mount Baker (from WA PFA). - Superhot EGS: Newberry (EGS demonstration project), Coso (EGS demonstration project), Geysers (EGS demonstration project), Eastern Snake River Plain (EGS demonstration project), Utah FORGE, Larderello, Kakkonda, Taupo Volcanic Zone, Acoculco, Krafla. - Supercritical: Coso, Geysers, Salton Sea, Larderello, Los Humeros, Taupo Volcanic Zone, Krafla, Reyjanes, Hengill. **Disclaimer: Treat the supercritical fluid anomalies with skepticism. They are based on assumptions due to the general lack of confirmed supercritical fluid encounters and samples at the sites included in this dataset, at the time of assembling the dataset. The main assumption was that the supercritical fluid in a given geothermal system has shared properties with the hydrothermal fluid, which may not be the case in reality. Once the datasets were assembled, principal component analysis (PCA) was applied to each. PCA is an unsupervised statistical learning technique, meaning that labels are not required on the data, that summarized the directions of variance in the data. This approach was chosen because our labels are not certain, i.e., we do not know with 100% confidence that superhot resources exist at all the assumed positive areas. We also do not have data for any known non-geothermal areas, meaning that it would be challenging to apply a supervised learning technique. In order to generate weights from the PCA, an analysis of the PCA loading values was conducted. PCA loading values represent how much a feature is contributing to each principal component, and therefore the overall variance in the data.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Agrivoltaic Racking Design Optimization Based on Wind and Snow Loading Finite Element Analysis

The racking structure of photovoltaic (PV) systems plays a critical role in ensuring the PV panels generate power properly as it provides integral structural support and sometimes even solar tracking ability. Distinct applications of PV systems require variations of racking structure designs, which yield different mechanical performances under external loading conditions from the environment, such as heavy wind and snow. Past works, such as Reddy et al. [1], have analyzed the pressure effects of wind and snow loading on the racking structure of conventional rooftop and utility PV systems, but there is little knowledge of how various agrivoltaic racking systems perform, in terms of stress and strain, under the same loading conditions. There is also a knowledge gap in the industry on a set of optimized agrivoltaic racking design standards. This study investigates the mechanical performance of various existing racking systems and proposes novel designs that are optimized for agrivoltaics applications under wind and snow loading.

Liao, Quanhuan↗
DOE OSTI2025

Cyber Informed Engineering Cie Analysis Tool

Main Benefits: • Collaborate on assessment via the web and access and share assessments on your mobile device. • Helps you maximize your cybersecurity investment and resources • Saves you significant time and money by eliminating the requirement to research each government and industry standard in order to understand your cybersecurity posture • Contains easy to follow, step by step instructions to guide you through the process of identifying the cybersecurity posture of your organization • Provides a place to begin with cybersecurity improvement and a way to prioritize your tasks and budgets. • Covers all major cyber relevant topic areas for a comprehensive assessment of your organization’s cybersecurity posture. • Dives deep into the details of each topic area. • Contributes to the organization's risk management and decision-making process • Highlights vulnerabilities and gaps in your organization's IT and control systems. • Raises awareness and facilitates discussion on cybersecurity within your organization • Educates the controls system community on cyber security.

Hansen, Barry [Idaho National Laboratory (INL), Id↗
DOE OSTI2026

A Methodology to Evaluate the Grid Reliability Impact of Oscillations Induced by Large Loads

The rapid growth of hyperscale AI data centers is bringing renewed attention to the reliability risk that sustained forced oscillations pose to bulk power systems, with cyclic computational workloads emerging as a new forcing source. Unlike the broadband, stochastic disturbances from traditional industrial loads such as arc furnaces, AI training and inference facilities can inject large active power swings concentrated at specific frequencies over extended durations - characteristics that existing grid planning practices do not account for. While the North American Electric Reliability Corporation (NERC) has recognized this gap and called for system-level studies of large load interconnections, no standardized methodology exists to screen, simulate, and quantify these risks at the planning stage. This report presents the Risk Assessment Tool for Large Load-induced Events (RATLLE), a Python-based, publicly available script suite developed at the Pacific Northwest National Laboratory to evaluate bulk power system reliability risks from data center-induced oscillations. RATLLE implements a three-module workflow: a screening module that identifies vulnerable interconnection locations and excitable system modes; a simulation module that models cyclic data center load behavior using a commercial positive sequence simulation platform; and an analysis module that computes risk metrics and generates interactive visualization dashboards. The risk metrics, formulated around simulation observables, map oscillation impacts to a three-stage severity scale spanning latent equipment fatigue through imminent cascading failure. The methodology is demonstrated on two Western Electricity Coordinating Council (WECC) system models: a publicly available 240-bus reduced representation and a detailed 2031 Heavy Winter planning case. Case studies illustrate that even modest 50 MW forced oscillations at resonant frequencies can produce wide-area power swings, N-1 security constraint violations, and cascading generator trips through protection actions - outcomes that would not occur under normal operating conditions without oscillations present. The results underscore the need for standardized oscillation impact assessment in large load interconnection studies and provide a reproducible, extensible framework for utilities to adopt or customize within their existing planning workflows.

Biswas, Shuchismita↗
DOE OSTI2022

NWGraph: A Library of Generic Graph Algorithms and Data Structures in C++20

The C++ Standard Library is a valuable collection of generic algorithms and data structures that improves the usability and reliability of C++ software. Graph algorithms and data structures are notably absent from the standard library, and previous attempts to fill this gap have not gained widespread adoption. In this paper we show that the richness of graph algorithms and data structures can in fact be captured by straightforward composition of existing C++ mechanisms. Generic programming is algorithm-oriented. Accordingly, we apply a systematic approach to analyzing a broad set of graph algorithms, “lift” unnecessary constraints from them, and organize the resulting set of minimal common type requirements, i.e., concepts, for defining their interfaces. By using the newly available ranges and concepts in C++20, the type requirements for generic graph algorithms can be succinctly expressed. The generic algorithms and data structures resulting from our analysis are realized in NWGraph, in a modern, composable, and extensible C++ library.

graphs and networks, programming language, C++20↗
NASA NTRSDate not supplied

Reanalysis of Rat Data from Spacelab Life Sciences 2 (SLS-2) to Reveal Research Gaps in Spaceflight Data

Using and analyzing the legacy data obtained in space life sciences missions has the potential to provide researchers a complete picture of the molecular changes associated with space without further experimentation. This project’s objective is to extract, filter, organize, and analyze all Rattus norvegicus data and metadata obtained from Columbia’s Spacelab Life Sciences 2 (SLS-2, STS-58) mission to explore the ways that we can compile information from model organisms, in our case rats, to create a reliable model to understand biological mechanisms in response to these space flight changes. By reusing rare space legacy data coupled with data analysis techniques, we can combine individual preexisting datasets with current ones to gain new, comprehensive insights about the effects of spaceflight on our bodies. Our methods can also lead to the creation of a standardized pipeline that could be applied to other space life science datasets for analysis. In this review, every biological experiment conducted on rats in the SLS-2 Mission was studied with our pipeline to create a new biological library and model that could be used by scientists from around the world to make novel discoveries and develop new hypotheses from this priceless information without the limitation of the costs of spaceflight experimentation.

rats↗
DOE OSTI2026

Online and Offline Analytical Techniques to Quantify Chloride Salts

This report serves as the deliverable for Milestone- M3FT-26AN080502017: Summary of Accomplishments for Online and Offline Analytical Qualification of Chloride Fuel Salts. The qualification of chloride fuel salts is a critical challenge for the development and deployment of molten salt reactors (MSRs), requiring precise control and verification of chemical and isotopic composition to ensure predictable neutronics, manageable radiological behavior, and safe plant operation. Currently, there is no universally accepted standard for fuel salt qualification, particularly for chloride-based systems, which underscores the need for robust, science-based analytical methodologies. This report presents a comprehensive evaluation of both online and offline techniques for quantifying chloride fuel salts, including multielectrode array voltammetry, differential thermal analysis (DTA) probes, inert gas fusion (IGF) analyzers, and gamma spectrometry using the Mirion NAIS-2x2 NaI(Tl) detector. The integration of these methods enables real-time monitoring of actinide concentrations, redox state, and thermophysical properties, as well as high-precision measurement of impurities and isotopic composition. The acquisition of advanced instruments such as the Bruker Leonardo G6 for IGF and the Mirion NaI detector enhances analytical capabilities, supporting the establishment of operational envelopes and impurity thresholds. These approaches provide essential data for neutronic impact evaluation, feedstock documentation, and compliance with nuclear safety standards. The methodologies developed and validated in this report lay the groundwork for future standardized protocols, bridging the gap between laboratory research and commercial reactor operation, and advancing the safe and efficient deployment of chloride-fueled MSRs.

Polke, Amber↗
DOE OSTI2025

Cybersecurity Considerations for Hydrogen Infrastructure in Airport Environments

This report explores key cybersecurity concerns and best practices within environments that serve as reference points for the development of hydrogen fueling infrastructure for aviation. This cybersecurity analysis leverages prior NREL studies: 1) hydrogen fueling station component validation to identify vulnerabilities and failure events documented in physical equipment, and 2) electric aircraft charging infrastructure analysis to explore primary cybersecurity vulnerabilities. It reviews the criticality of digitized technologies in sustaining hydrogen fuel production, storage, and fueling systems, noting cybersecurity concerns that are universal to power systems and industrial control systems in general. In considering cybersecurity vulnerabilities within a future landscape of hydrogen energy for aviation applications, a reference architecture was intended to reveal the points of connection between assets and the potential sensors that are vulnerable to manipulation in the event of compromised access or communication within a SCADA system. A generalized reference architecture can help stakeholders, engineers, or strategists understand connections, criticalities, and standard practices when it comes to designing and planning for new systems. There are several gaps to account for in assessing the future of hydrogen production, storage, and fueling for aviation. Engaging stakeholders, including aircraft manufacturers, electric utilities, site property owners, and local communities, will inform decision-making around site structure, operations, and resources for future hydrogen fueling infrastructure to understand operational needs and cybersecurity awareness. Cybersecurity mitigation strategy must consider physical attack vectors that emerge with the integration of hydrogen systems into existing airport security requirements. The cybersecurity risk assessment contained in this report is an entry point into potential future granular-level analyses to be conducted as part of hazard and risk assessments for safe aviation hydrogen infrastructure, determining how the scale of hydrogen fuel infrastructure for aviation impacts the volume of cyber attack vectors, and what, if any, are the vulnerabilities associated with different types of on-board hydrogen systems. In this nascent development phase, assessing how best to integrate cybersecurity practices into an evolving U.S. aviation landscape provides critical insights into building increased awareness and stakeholder engagement to support a cyber-resilient infrastructure.

08 HYDROGEN↗