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DOE OSTI2026

Decadal-Scale Hydrothermal Alteration of Basalt: Implications for Long-Term Reactivity in Subsurface Technologies

Global demands to secure critical mineral supply chains and managing water resources require innovative resource management strategies. Subsurface basalt reservoirs offer a dual-purpose application, where CO2 enhanced critical metal recovery can be coupled with water remediation strategies for the extraction of economically important and environmentally relevant elements. This study utilizes static batch experiments conducted on Columbia River Basalt Group samples to evaluate long-term fluid–rock interactions relevant to coupled subsurface applications. Samples were reacted under elevated temperature and pressure conditions, for 296 and 4,061 days, providing a unique dataset to assess geochemical evolution, element partitioning, and aqueous chemistry over decadal timescales. The alteration was dominated by silicate, aluminosilicate, and oxide phases. Progressive hydrothermal alteration increased the cation exchange capacity through the formation of secondary minerals (e.g. clays and zeolites), influencing solute retention, ion exchange behavior, and aqueous chemistry. Grain-scale and bulk analyses revealed selective cation release and retention patterns, establishing a mechanistic baseline for predicting element mobility. These geochemical constraints inform the prospective use of CO2-enhanced metal recovery for critical resources (e.g. Co, Ni, Mn, Mg, Ti, Fe) and associated water-quality impacts, providing a foundation for the design and management of engineered fluid–rock systems in basalt reservoirs.

Gibson, Marie N.↗

DOE OSTI2024

Dark energy survey year 3 results: likelihood-free, simulation-based w CDM inference with neural compression of weak-lensing map statistics

We present simulation-based cosmological wcold dark matter (wCDM) inference using dark energy survey year 3 weak-lensing maps, via neural data compression of weak-lensing map summary statistics: power spectra, peak counts, and direct map-level compression/inference with convolutional neural networks (CNN). Using simulation-based inference, also known as likelihood-free or implicit inference, we use forward-modelled mock data to estimate posterior probability distributions of unknown parameters. This approach allows all statistical assumptions and uncertainties to be propagated through the forward-modelled mock data; these include sky masks, non-Gaussian shape noise, shape measurement bias, source galaxy clustering, photometric redshift uncertainty, intrinsic galaxy alignments, non-Gaussian density fields, neutrinos, and non-linear summary statistics. We include a series of tests to validate our inference results. This paper also describes the Gower Street simulation suite: 791 full-sky pkdgrav3 dark matter simulations, with cosmological model parameters sampled with a mixed active-learning strategy, from which we construct over 3000 mock dark energy survey lensing data sets. For wCDM inference, for which we allow –1 < w < –$\frac{1}{3}$⁠, our most constraining result uses power spectra combined with map-level (CNN) inference. Using gravitational lensing data only, this map-level combination gives Ω m = 0.283$^{+0.020}_{–0.027}$⁠, S 8 = 0.804$^{+0.025}_{–0.017⁠}$, and w < –0.80 (with a 68 per cent credible interval); compared to the power spectrum inference, this is more than a factor of two improvement in dark energy parameter (Ω⁠ DE , w⁠) precision.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Development of a Framework and Methodology for an Advanced Reactor Materials Environmental Effects Design Guide

Advanced non-light-water reactor components may operate at elevated temperature while experiencing cyclic loading, significant neutron irradiation, and exposure to reactor coolant. ASME Boiler and Pressure Vessel Code, Section III, Division 5, provides design rules for elevated-temperature service but does not include specific procedures to account for environmental effects on material properties. This report develops an initial framework and methodology for an Environmental Effects Design Guide (EEDG) focused on neutron irradiation; coolant-environment effects are reserved for future work. The proposed approach treats irradiation as a property-based overlay on the existing Division 5 design process, with two routes: a sparse-data route applying two reduction factors — FCR on creep-rupture strength and FF on fatigue life — for the creep-fatigue evaluations that typically control the design of advanced high-temperature reactor components, and a fuller framework developing the property-to-rule chain across the four Division 5 checks (primary load, strain limits and ratcheting, creep-fatigue, and buckling), together with swelling and weldments as scope items. Both routes are scoped by an in-pile qualification that restricts the use of post-irradiation-examination-derived properties in regimes where an in-pile mechanism could control the design outcome. Illustrative outputs derived on a compiled annealed Type 316 database — FCR ≈ 0.78–0.86 and FF ≈ 0.4 — demonstrate the calculation method within that specific dataset. The framework is an initial, testable design-rule concept; it identifies a practical path for preliminary design evaluations under sparse data and the material data and testing needed to develop the framework further.

Barua, Bipul (ORCID:0000000247184113)↗

NASA NTRS2026

Spacecraft Water Impurity Monitor, a System for Water Quality Analysis on Exploration Missions Beyond Low Earth Orbit

Exploration missions beyond low-earth-orbit (LEO) will require advanced instrumentation to monitor water quality. Traveling beyond LEO means the transfer of water samples to an Earth-based laboratory for detailed analysis is not feasible. Detailed analysis of water composition during exploration is still necessary, because having the capability to determine the specific organic chemical causing a change in total organic carbon (TOC) or the specific metal or ionic species causing a change in conductivity has the potential to inform the crew health and system management decisions. On a new vehicle such as a lunar or Mars surface habitat or a Mars transit vehicle, finding “new” impurities not seen on ISS should be expected. The key is to identify the impurity so the correct action can be taken. On ISS we can measure TOC, conductivity, and other physical properties but do not have the capability for detailed analysis using vehicle instrumentation. This is acceptable because ISS can send samples down to Earth for further analysis and obtain the detailed composition. The Spacecraft Water Impurity Monitor (SWIM) will provide detailed water quality analysis for missions in which sample down mass is not available. SWIM is a system comprising organic and inorganic analysis modules. For organic chemicals, a gas chromatograph mass spectrometer (GCMS) detects and identifies organic impurities. For inorganic species, a capillary electrophoresis capacitively coupled contactless conductivity detection (CE-C4D) system as well as ion specific electrodes detect and identify metal ions and other inorganic salts / acids. The SWIM technology demonstration project has completed a System Requirements Review (SRR) to finalize detection requirements and is currently working to refine vehicle interface requirements for a future technology demonstration. The project also has begun preliminary flight design activities for the core analyzers in the instrument suite.

Water Monitoring↗

NASA NTRSDate not supplied

Softening the Gap between Wöhler and Paris – New Approaches for Fatigue Analysis –

Fatigue analysis tools can vary across industries. For example, automotive engineers often use the Wöhler (S-N) approach to design for safe-life, while aerospace engineers prioritize damage tolerance and inspection intervals, relying instead on crack growth models such as Paris’ law. Although both approaches may deal with the control of cracks in similar materials, their analysis tools and material characterizations are fundamentally distinct. This divide mirrors the classic split between stress-based strength analysis and linear elastic fracture mechanics. However, modern nonlinear models that incorporate material softening, such as cohesive laws, blur this boundary and capture fracture behaviors across scales. This presentation describes the CF23 fatigue model, which uses cohesive softening to link S-N crack initiation with crack propagation rates. CF23 spans the full fatigue spectrum, from initial propagation transients to steady-state growth and threshold conditions, offering a unified framework that bridges Wöhler and Paris-based methodologies. Example applications include fatigue crack propagation transients in adhesive interfaces and skin/stiffener separation.

cohesive elements↗

DOE OSTI2026

Value of Geothermal Energy Storage for Supply-Side and Demand-Side Applications

This report presents the results of a study examining the value potential for geothermal energy storage (GES), a long-duration energy storage resource that stores thermal and/or geomechanical energy in the subsurface. GES could benefit the overall U.S. power system by temporally shifting electricity generation (supply-side) or meeting building heating and cooling load (demand-side). This report analyzes supply-side and demand-side opportunities independently because of differences in applications and models. Currently there is significant uncertainty about the development costs for GES, with only a limited number of demonstration plants for electric energy storage and building heating and cooling storage developments. In this report, we estimate the value of supply-side and demand-side GES to the bulk power system in the contiguous United States. Because of the significant uncertainty about GES development costs, this analysis does not consider GES deployment costs but instead focuses on the value of GES to the U.S. electricity system. The estimated values of GES provide reference points for economically competitive commercial cost targets. Supply-side GES is modeled as part of an enhanced geothermal system (EGS) generation plant in NREL's Regional Energy Deployment System (ReEDS) capacity expansion model (Ho et al. 2021). In contrast to conventional geothermal plants, which generate constant power, EGS plants have unique features that may allow for in-reservoir energy storage for flexible generation. Demand-side GES for heating and cooling, including seasonal hot and cold storage and short-duration heat pump storage, is incorporated into a price-taker model using Cambium electricity marginal cost projections. To establish an upper bound for the value of GES, analysis focused on favorable scenarios for storage with high generation from zero marginal cost, variable renewable energy resources. High penetrations of variable renewable energy generation can increase hourly electricity price variability, which increases the value of temporal energy arbitrage for storage technologies like GES.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Cold Spray Cobalt Magnetostrictive Electromagnetic Acoustic Transducers for High Temperature Structure Monitoring

The Department of Energy’s Advanced Sensors and Instrumentation program seeks to develop and qualify advanced sensors for the nuclear industry. Reliable high temperature and high radiation sensors for detection and characterization of structural flaws in pipes, vessels, and structurally critical components is a weakness for both conventional light water reactors with coolant T-hot approaching 350oC, and for advanced reactors with T-hot temperatures in excess of 500 to 800oC. Magnetostrictive Electromagnetic Acoustic Transducers using a cold spray cobalt coating have been proposed as a sensor design that can withstand these kinds of temperatures and radiation levels to serve as online sensors to detect flaws before cracks, pits, or erosion/corrosion flaws progress to through-wall failures. This report tests cold spray cobalt as part of a magnetostrictive EMAT for high temperature service. Cobalt is known to have strong magnetostrictive properties however the effect of cold spray application is not well studied. This program was surprised to discover that cold sprayed cobalt exhibited little or no magnetostrictive behavior until it was thermally annealed. Following annealing to 650oC however, cold spray cobalt did exhibit a magnetostrictive response. Work to date prior to this milestone report publication showed that magnetostrictive EMAT was successfully tested to 400oC with an alnico permanent magnet. The program plans to extend testing with an electromagnet to higher temperatures. This follow-on work will be reported under subsequent publications or as a revision to this report.

Glass, Samuel W.↗

DOE OSTI2024

The multifunctional use of an aqueous battery for a high capacity jellyfish robot

The batteries that power untethered underwater vehicles (UUVs) serve a single purpose: to provide energy to electronics and motors; the more energy required, the bigger the robot must be to accommodate space for more energy storage. By choosing batteries composed primarily of liquid media [e.g., redox flow batteries (RFBs)], the increased weight can be better distributed for improved capacity with reduced inertial moment. Here, we formed an RFB into the shape of a jellyfish, using two redox chemistries and architectures: (i) a secondary ZnBr 2 battery and (ii) a hybrid primary/secondary ZnI 2 battery. A UUV was able to be powered solely by RFBs with increased volumetric (Q~ 11 ampere-hours per liter) and areal (108 milliampere-hours per square centimeter) energy density, resulting in a long operational lifetime (T~ 1.5 hours) for UUVs composed of primarily electrochemically energy-dense liquid (~90% of the robot’s weight).

Science & Technology - Other Topics↗

DOE OSTI2026

Robust and High Throughput Tools for Characterization of Wet Cellulosic Biogas Feedstocks and Co-Products: Cooperative Research and Development Final Report, CRADA Number CRD-21-21472

This project will develop standardized analytical procedures to support understanding of the chemical composition of wet manure feedstocks, and the digestate formed following anaerobic digestion of organic waste to produce renewable natural gas (RNG). The developed methods will be validated to improve component mass closure, eliminate ambiguities around key constituents, and document the precision and accuracy of the methods. Following validation of the analytical laboratory methods for characterization of wet organic waste feedstocks and digestate, NLR will use the same samples to build and validate near-infrared (NIR) models for high throughput analysis, potentially deployable at commercial facilities, enabling increased production of low carbon intensity RNG from wet organic wastes.

09 BIOMASS FUELS↗

NASA NTRSDate not supplied

Thermostructural Testing of PICA-D for NASA Planetary Science Missions

Phenolic Impregnated Carbon Ablator–Domestic (PICA‑D) has been selected as the heatshield thermal protection system (TPS) material for two upcoming NASA planetary science missions: the Dragonfly mission to Titan and the Mars Sample Retrieval Lander (SRL). Early testing revealed differences between PICA‑D and heritage PICA, particularly in in‑plane (IP) tensile stiffness and thermal expansion. Thermostructural analyses using Finite Element Method (FEM) tools subsequently predicted the potential for IP compressive failure in the near‑surface layers of PICA‑D under both Dragonfly and SRL flight environments. Over the past three years, the Dragonfly and SRL teams have carried out an extensive thermostructural qualification campaign to address these concerns and validate PICA‑D for flight. This effort began with a comprehensive mechanical property characterization program at Kratos test laboratories, which significantly improved understanding of PICA‑D mechanical behavior and increased the fidelity of FEM predictions. The teams also conducted six large‑scale test entries at the National Solar Thermal Test Facility (NSTTF) solar tower, exposing PICA‑D articles—including gap fillers and representative design features or flaws—to combined thermal and mechanical loads. The talk will summarize key findings from these mechanical and thermostructural test campaigns and present the current status of PICA‑D qualification for NASA’s planetary science missions.

TPS↗

NASA NTRS2026

Hyperspectral Detail Meets Radiometric Accuracy: A Foundational Reflected Solar Capability for the Coming Decade

Hyperspectral Earth-reflected solar measurements contain rich, detailed information about clouds, aerosols, and the atmosphere. This information compounds when paired with high, SI-traceable radiometric accuracy. Unlike spectral resolution, which can be resampled to coarser spectral resolutions, radiometric accuracy cannot be recovered once a measurement is made, making the choice to invest in this capability now a decision with lasting consequences for the climate record. CLARREO Pathfinder is demonstrating that this combination of hyperspectral sampling and benchmark-quality accuracy is achievable today, but no follow-on mission is currently planned within NASA's Earth Science Division portfolio, and the recent cancellation of the European Space Agency TRUTHS mission has heightened the urgency of sustaining this capability. We recommend prioritizing investment in a follow-on to CLARREO Pathfinder, along with dedicated support for the science community to fully exploit these measurements. This capability would reduce long-standing uncertainties in cloud feedback, aerosol forcing, and global energy imbalance, while providing a degradation-resistant, gap-resilient calibration foundation for the broader Earth observing system. Building on flight-proven technology and an engaged science community, this is a near-term, fiscally realistic opportunity to secure a foundational Earth observation capability for the coming decade.

satellite↗

DOE OSTI2026

Initial Feasibility Assessment and Broader Strategy Development for Fiber Integration via Advanced Manufacturing

Structural health monitoring is critical for ensuring the operational safety and cost-competitiveness of the developing advanced reactor designs. The extreme operational envelopes of these advanced architectures, having operating temperatures ranging 400°C–1,000°C and heightened displacement damage doses, render conventional commercially available piezoelectric transducers and resistive strain gauges unviable. Optical fiber sensors present an attractive solution for advanced radiation-hardened instrumentation due to their high thermal stability and distributed sensing capabilities. However, their deployment in embedded applications can be hindered by the severe thermomechanical strain driven by the coefficient of thermal expansion mismatch between fused silica glass and structural metal alloys like stainless steel (e.g., SS316L).

36 MATERIALS SCIENCE↗

DOE OSTI2025

Intensified atomic utilization efficiency of single-atom catalysts for nitrate conversion via electrified nanoporous membrane

Conventional electrochemical reactors for nitrate reduction typically suffer from limited reaction efficiency when applied for real-world water treatment due to poor utilization of electrocatalytic active sites. Here, we applied nanoporous electrofiltration to intensify atomic utilization by incorporating single-atom catalysts into an electrified membrane for reducing low-concentration nitrate to ammonia under realistic water conditions. We enhance the exposure of single atoms in nanopores by coating the catalysts on a carbon nanotube–interwoven membrane framework. Electrofiltration intensifies the transport and adsorption of nitrate in confined nanopores with highly exposed single-atom active sites to enhance reduction. The membrane enables a superior ammonia turnover frequency of 15.1 grams of nitrogen per gram of metal per hour, up to four orders of magnitude higher than that reported in the literature, under both high removal efficiency and Faradaic efficiency of over 86% when treating influents with a low nitrate concentration of 100 milligrams of nitrogen per liter in a residence time on the order of seconds.

Science & Technology - Other Topics↗

NASA NTRS2026

Spacecraft Disposal Rosetta Stone: Parametric Tool for Orbital Lifetime, Disposal, and Cost Assessment

This Technical Memorandum documents a simplified, parametric method for evaluating spacecraft orbital lifetime, disposal compliance, and disposal-related cost impacts during early mission formulation and preliminary design. The method captures the dominant drivers of orbital decay—effective ballistic coefficient, operating altitude, and solar-cycle variability—using conservative bounding assumptions. Solar maximum conditions are used to bound achievable mission lifetime, while solar minimum conditions are used to bound disposal timelines and compliance with orbital debris requirements. A single tabulated dataset provides orbital lifetime under both solar-cycle extremes together with representative disposal ΔV required to ensure compliant disposal, enabling rapid assessment of disposal feasibility, cost sensitivity, and system-level impacts prior to committing to higher-fidelity analyses.

Orbital debris mitigation↗

DOE OSTI2026

Comparing Thermal Neutron Scintillators for Use With SiPM-Readout Detectors

Scintillator-based thermal neutron detectors for scientific scattering facilities offer an effective combination of large-area coverage and good spatial resolution. At Oak Ridge National Laboratory, silicon photomultiplier (SiPM)-readout Anger cameras using 6 Li glass scintillators have been developed, but the spatial resolution of these detectors is limited by the relatively low light yield of the glass. Recently, several brighter scintillator compositions with sufficient 6 Li concentration have emerged as promising candidates for higher-resolution imaging. Here, in this work, we evaluate five scintillator materials: GS20, LiF/ZnS:Ag, LiF/ZnO:Zn, LiI:Eu, and Cs 2 LiYCl 6 :Ce, each mounted on a SiPM Anger camera. For each scintillator, the neutron detection efficiency, spatial resolution, and count rate capabilities were measured and compared. Each of the new compositions achieved a spatial resolution better than 0.5 mm, compared to 0.66 mm for GS20, with LiI:Eu reaching the best value of 0.32 mm. Although these compositions improve the spatial resolution of the Anger camera, their longer pulse decay times limit their use in high count rate applications, and the camera’s hardware must be optimized for the different properties of the new scintillators.

Neutron detectors↗

NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗

NASA NTRS1993

A SIMULINK Environment for Flight Dynamics and Control Analysis - Application to the DHC-2 'Beaver', Part 1. Implementation of a Model Library in SIMULINK

The design of advanced Automatic Aircraft Control Systems (AACS's) can be improved upon considerably if the designer can access all models and tools required for control system design and analysis through a graphical user-interface, from within one software environment. This MSc-thesis presents the first step in the development of such an environment, which is currently being done at the Section for Stability and Control of Delft University of Technology, Faculty of Aerospace Engineering. The environment is implemented within the commercially available software package MATLAB/SIMULINK. The report consists of two parts. Part I gives a detailed description of the AACS design environment. The heart of this environment is formed by the SIMULINK implementation of a nonlinear aircraft model in block-diagram format. The model has been worked out for the old laboratory aircraft of the Faculty, the De Havilland DHC-2 'Beaver', but due to its modular structure, it can easily be adapted for other aircraft. Part I also describes MATLAB programs which can be applied for finding steady-state trimmed-flight conditions and for linearization of the aircraft model, and it shows how the built-in simulation routines of SIMULINK have been used for open-loop analysis of the aircraft dynamics. Apart from the implementation of the models and tools, a thorough treatment of the theoretical backgrounds is presented. Part II of this report presents a part of an autopilot design process for the 'Beaver' aircraft, which clearly demonstrates the power and flexibility of the AACS design environment from part I. Evaluations of all longitudinal and lateral control laws by means of nonlinear simulations are treated in detail. The AACS design environment from part I proved to be a very useful tool for designing the control laws of the 'Beaver' autopilot within a very tight time-schedule. The autopilot design process itself will be used as a guideline for future AACS research at the Faculty of Aerospace Engineering. Flight tests of the 'Beaver' autopilot, done after evaluating the control laws in the SIMULINK package, proved to be quite successful. In the future, the AACS design package will evolve into a standardized, integrated design environment which can be applied to virtually any type of aircraft. The AACS design cycle will be shortened further by developing tools for automatically porting control laws from the MATLAB/SIMULINK environment to a piloted real-time flight simulator and the Flight Control Computers of the aircraft.

Aircraft Modelling↗

NASA NTRS2026

Ultrasonic Washer–Dryer System for Space Habitats: Design Upgrades and Parabolic Flight Readiness

Clothing makes up nearly 25% of all non-food supplies sent to the International Space Station (ISS). To support sustainable human missions in deep space, NASA’s Life Support and Habitation Systems Focus Area looks to advance technologies to support and improve logistics. Our team is creating a compact ultrasonic clothing washer/dryer system that bypasses traditional limitations and is suitable for space. Thermal drying uses a lot of energy to evaporate water, while our ultrasonic drying method offers a quicker, more efficient alternative. It uses piezoelectric transducers to vibrate textiles at the micron scale, mechanically removing water as cold mist rather than evaporating it. This speeds up drying and reduces energy use, no matter the fabric makeup. This paper details recent upgrades to a full-scale ultrasonic washer–dryer system, readying it for parabolic flight testing. Improvements include an enhanced human–machine interface, better packaging, and optimized performance and control. We also present extensive pre-flight ground tests conducted to ensure reliability and identify potential risks. Collaborating with P&G, we report preliminary cleaning tests using various detergents. These results lay a crucial foundation for the laundry system designed specifically for space. By cutting clothing-related payload and waste by over 97%, this technology supports long-term human exploration missions on the ISS, the Moon, Mars, and beyond.

Laundry↗