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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
NASA NTRS2011

NASA Tech Briefs, August 2011

Topics covered include: Miniature, Variable-Speed Control Moment Gyroscope; NBL Pistol Grip Tool for Underwater Training of Astronauts; HEXPANDO Expanding Head for Fastener-Retention Hexagonal Wrench; Diagonal-Axes Stage for Pointing an Optical Communications Transceiver; Improvements in Speed and Functionality of a 670-GHz Imaging Radar; IONAC-Lite; Large Ka-Band Slot Array for Digital Beam-Forming Applications; Development of a 150-GHz MMIC Module Prototype for Large-Scale CMB Radiation; Coupling Between Waveguide-Fed Slot Arrays; PCB-Based Break-Out Box; Multiple-Beam Detection of Fast Transient Radio Sources; Router Agent Technology for Policy-Based Network Management; Remote Asynchronous Message Service Gateway; Automatic Tie Pointer for In-Situ Pointing Correction; Jitter Correction; MSLICE Sequencing; EOS MLS Level 2 Data Processing Software Version 3; DspaceOgre 3D Graphics Visualization Tool; Metallization for Yb14MnSb11-Based Thermoelectric Materials; Solvent/Non-Solvent Sintering To Make Microsphere Scaffolds; Enhanced Fuel-Optimal Trajectory-Generation Algorithm for Planetary Pinpoint Landing; Self-Cleaning Coatings and Materials for Decontaminating Field-Deployable Land and Water-Based Optical Systems; Separation of Single-Walled Carbon Nanotubes with DEP-FFF; Li Anode Technology for Improved Performance; Post-Fragmentation Whole Genome Amplification-Based Method; Microwave Tissue Soldering for Immediate Wound Closure; Principles, Techniques, and Applications of Tissue Microfluidics; Robotic Scaffolds for Tissue Engineering and Organ Growth; Stress-Driven Selection of Novel Phenotypes; Method for Accurately Calibrating a Spectrometer Using Broadband Light; Catalytic Microtube Rocket Igniter; Stage Cylindrical Immersive Display; Vacuum Camera Cooler; Atomic Oxygen Fluence Monitor; Thermal Management Tools for Propulsion System Trade Studies and Analysis; Introduction to Physical Intelligence; Technique for Solving Electrically Small to Large Structures for Broadband Applications; Accelerated Adaptive MGS Phase Retrieval; Large Eddy Simulation Study for Fluid Disintegration and Mixing; Tropospheric Correction for InSAR Using Interpolated ECMWF Data and GPS Zenith Total Delay; Technique for Calculating Solution Derivatives With Respect to Geometry Parameters in a CFD Code; Acute Radiation Risk and BRYNTRN Organ Dose Projection Graphical User Interface; Probabilistic Path Planning of Montgolfier Balloons in Strong, Uncertain Wind Fields; Flight Simulation of ARES in the Mars Environment; Low-Outgassing Photogrammetry Targets for Use in Outer Space; Planning the FUSE Mission Using the SOVA Algorithm; Monitoring Spacecraft Telemetry Via Optical or RF Link; and Robust Thermal Control of Propulsion Lines for Space Missions.

Source record↗
DOE OSTI2025

Iterative Reconstruction for Multimodal Neutron Tomography

Here, we describe a unified framework for model-based iterative 3-D reconstruction of multimodal neutron transmission, hydrogen-scatter, and induced-fission images from low resolution data recorded using 14.1-MeV neutrons and the associated-particle imaging (API) technique. The framework, which was developed to facilitate use in challenging field-deployment scenarios, is centered around physics-based system models and a total variation (TV) constrained implementation of the simultaneous iterative reconstruction technique (SIRT). Modified to solve a statistically weighted least squares (WLS) problem, the SIRT algorithm is accelerated using ordered subsets and Nesterov’s momentum for which we derive a near-optimal value of the governing Lipschitz constant. The approach enables the reconstruction of images that are high resolution compared to the acquired data and is robust to both limited statistics and a limited number of projection angles. Moreover, the framework is fast enough to be practical. Example images are provided that demonstrate both the ability to perform fast-neutron imaging of high-atomic-number materials with low radiation dose and the benefit of multimodal neutron imaging to identify key materials.

Hydrogen scatter↗
DOE OSTI2023

Evolution of artificial intelligence for application in contemporary materials science

Abstract Contemporary materials science has seen an increasing application of various artificial intelligence techniques in an attempt to accelerate the materials discovery process using forward modeling for predictive analysis and inverse modeling for optimization and design. Over the last decade or so, the increasing availability of computational power and large materials datasets has led to a continuous evolution in the complexity of the techniques used to advance the frontier. In this Review, we provide a high-level overview of the evolution of artificial intelligence in contemporary materials science for the task of materials property prediction in forward modeling. Each stage of evolution is accompanied by an outline of some of the commonly used methodologies and applications. We conclude the work by providing potential future ideas for further development of artificial intelligence in materials science to facilitate the discovery, design, and deployment workflow. Graphical abstract

Materials Science↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Reinforcement Learning

To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. The goal of reinforcement learning is for an agent to learn a policy (task strategy) through interactions with an environment. When the agent performs an action, a change occurs in environment state and a numerical reward is received which informs the agent whether the action performed was good or not. Since reinforcement learning algorithms learn through trial-and-error, a simulation is a desirable first environment for development and learning. We developed two simulations, the first is a 2D excavation simulation developed to facilitate parameter selection, and a 3D simulation developed using a game physics engine, to simulate simplified soil interactions and increase the fidelity of the dynamic models of the robotic agents. The development of this 3D simulation has enabled the training of additional sensing capabilities and research both at the granular mechanics and operations levels. We experimented with various virtual sensor payloads to identify a combination that enabled efficient excavation operation and learning. Our reward function is based on how much material is excavated per step. A penalty is also received for leaving the dig site and to smooth the acceleration of the drum arms. We implemented pseudo time-of-flight sensors to report distance from each drum to ground and the height above ground which was found to be more efficient than existing solutions. Our findings suggest that reinforcement learning for autonomous operations has learned viable trenching strategies within 3000 training episodes in our simplified 2D environment and helped identify desirable sensing capabilities, arrangements, and considerations such as the positioning of time-of-flight sensors. Future work includes expanding our simulation to more complex environments and scenarios, and transfer learning from simulation to RASSOR 2.0 hardware for deployment in the Regolith Test Bin at NASA's Kennedy Space Center.

rassor↗
DOE OSTI2022

Design optimization of integrated cooling inserts in modular Fischer-Tropsch reactors

Sustainable production of liquid fuels and feedstocks from atmospheric CO 2 through carbon recycling technologies is necessary to broaden decarbonization efforts and further reduce global emissions. Fischer–Tropsch (FT) reactors can address this challenge by providing storable, high-value liquid hydrocarbon fuels and feedstocks from syngas generated through reductive CO 2 utilization. FT technology, however, is most cost effective at large-scale, fixed-site plants and does not effectively address the smaller, globally distributed CO 2 point sources. Alternatively, smaller, modular reactors can be composed together to the specific scale of the emission source, yielding a flexible solution that enables more widespread deployment. In these modular reactors, thermal management using a finned cooling insert embedded within the catalyst matrix is critical to maintaining the performance and viability. Thus, in this work, topology optimization is used to determine the cooling insert geometry that maximizes reactor productivity while preventing auto-thermal runaway. Optimal designs are generated for varying number of constituent fins and over a range of maximum operating temperatures. Constraints including minimum feature length-scales and prescribed cooling insert material are imposed on the designs to enhance manufacturability. The impact of design features such as insert tapering and increased length scale hierarchy is automatically revealed by the systematic design framework employed. Here, this approach thus generates novel optimal geometries while automating, accelerating, and enhancing the design process compared to traditional heuristic approaches for cooling insert design in modular FT reactors.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Integration of sensors through additive manufacturing leading to increased efficiencies of gas turbines for power generation and propulsion

To realize the full capability of additively manufactured components in complex energy systems, it is imperative to minimize early component failures during development phases and during operation. Traditional field feedback timelines and offline inspection protocols significantly reduce the design-manufacturing iteration times. To address this specific question, the project developed and demonstrated a method for the integration of sensors into complex components through additive manufacturing. The team used gas turbine engines as a platform, which meets the need of both power generation and propulsion and offer opportunities for cost reductions and efficiency increases. The innovation of this intelligent integration of sensors into complex components uniquely customized to address questions of integrity and durability for additively manufactured components. With real-time sensing data from additively manufactured components, turbine manufacturers will realize higher efficiencies, reduced component failures, and a 30-50% acceleration in product deployment of high efficiency gas turbine components due to a faster reduction in component risk assessment under actual operating conditions. This is a transformative shift towards a data-driven design and qualification of additively manufactured gas turbine components. To directly integrate sensors into additively manufactured components with all the complexities of actual hardware, powder bed fusion (direct metal laser sintering) and laser metal deposition technologies was developed. Validation took take place in two university laboratories both of which contain actual engine hardware and closely simulate a gas turbine prior to demonstrating the technology in a turbine development test. Indeed, two major technologies from this research cold impact turbine systems in the near future: (1) higher efficiency materials and designs enabled by additive manufacturing with 50% faster design to manufacturing cycle time, to enable faster time-to-market targets; and (2) integration of sensors into additively manufactured components enabling broad health and condition based prognostics for faster component and engine risk reduction.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Post-build stress-relief optimization for laser powder bed fusion 316H stainless steel

Nuclear energy remains a critical component of a diversified and efficient energy portfolio, offering reliable, high-capacity, and low-carbon power. However, in the U.S., aging infrastructure and the slow qualification and deployment of advanced materials and manufacturing techniques hinder progress in next-generation reactor technologies. This study explores the application of laser powder bed fusion (LPBF) additive manufacturing for stainless steel 316H, with a focus on optimizing post-build heat treatments to enhance material properties for high-temperature nuclear applications. The research targets the optimization of stress-relief temperatures to alleviate postbuild residual stresses, ensuring improvements in the microstructural corelated properties. A series of microstructural and mechanical evaluations were performed on LPBF-printed SS-316H samples which were subjected to annealing at temperatures varying between 650 °C and 850 °C. X-ray diffraction, scanning electron microscopy, and transmission electron microscopy analyses revealed that increasing the heattreatment temperature accelerated dislocation recovery. Vickers microhardness measurements showed an initial reduction in values, followed by stabilization over extended durations at all the temperatures. While higher temperatures facilitated faster recovery, they also promoted carbide precipitation along grain and solidification cell boundaries, narrowing the safe processing window. In contrast, heat treatment at 650°C preserved the cellular substructure and enabled controlled carbide precipitation over time. In conclusion, these findings highlight the importance of time–temperature optimization and suggest that 650°C for up to 2 h provides the most favorable balance between recovery and carbide control for a stress-relief treatment.

316 stainless steel↗
DOE OSTI2025

Using Separation-Enhanced Isotope Ratio Mass Spectrometry to Enable Increased Renewable Carbon Content in Transportation Fuels (CRADA 525)

Stable isotope ratio measurements of carbon atoms using isotope ratio mass spectrometry (IRMS) can be an effective tool for quantifying biogenic carbon in co-processed fuels, with results approaching the precision and accuracy of accelerator mass spectrometry (AMS). The lower cost of an IRMS may enable deployment to refineries, improving access and analysis turnaround times (≤2 hours), and, by extension, provide data that can allow process optimization to maximize renewable carbon in desired refinery products. This project explored the integration of chemical separation with IRMS analyses to enable highly detailed tracking of biogenic carbon into fuel product streams separated by boiling point range, chemical class, or specific compound. Forty-nine fuels and fuel components of fossil and biogenic origin, spanning gasoline and diesel boiling point ranges, were received from three refiners and were analyzed for their δ 13 C values via IRMS. Results spanned a 13 C range from ca. 10‰ to 44‰ and reflect materials derived from sustainable sources (e.g., C4 or C3 plants, animal-based pathways, syngas) or from fossil-derived fuels. Common ranges are approximately 18‰ to 9‰ and approximately 30‰ to 20‰ for C4 and C3 plants, respectively, and approximately 34‰ to 24‰ and approximately 70‰ to 33‰ for petroleum-derived fuels and methane, respectively. Fuel-like standards were developed and tested using direct-injection elemental analyzer (EA) IRMS for liquid fuels. This method was compared with the published methods, yielding statistically similar results. Four blend curve sets were produced ranging from 0% to 100% of a fuel containing biogenic carbon, focusing on 0% to 10% biogenic carbon. Linear fits were the most applicable for two of the four blend curve sets; however, two sets were found to exhibit slightly quadratic behavior, which was more pronounced in low biogenic blend samples, necessitating second-order fits. The origin of the slight quadratic behavior remains unclear; however, the discussion points to possible interpretations. CanmetENERGY thoroughly characterized a majority of the samples using one- and two-dimensional gas chromatography (GC and GC×GC, respectively) and other analyses. Selected samples were subjected to solid phase extraction (SPE) for saturate, olefin, aromatic, and polar (SOAP) analysis, and the resulting solvent-diluted fractions containing saturates and aromatics were returned to Pacific Northwest National Laboratory (PNNL), where the solvent was removed via evaporation or physical separation using GC techniques. Characterization and separations provided an understanding of saturate and aromatic content, as well as boiling point ranges for each sample and sample fraction. Samples resulting from SPE were examined using EA-IRMS and gas chromatography combustion IRMS (GC-C-IRMS) analyses. Both approaches suggest that the range in values between end-members can be increased by selecting the paraffinic or aromatic fraction of the end-member or by selecting among individual compounds resulting from GC separation of the paraffinic fractions. Considerable work remains to put these approaches into practice and statistically validate the benefit for using a fraction or individual compound over bulk analysis of a sample. However, initial results suggest that separations provide advantages for samples having blend ratios of less than 10% biogenic blendstocks. 13 C results showed statistically similar biofuel blend results to those obtained at PNNL, although additional work is needed to obtain better reproducibility. Select samples were sent to Los Alamos National Laboratory (LANL) for IRMS measurements and Beta Analytics for AMS measurements. This work suggests that IRMS and AMS yield closely comparable results and in some circumstances, IRMS could serve as a surrogate for AMS. While additional work is needed to better resolve statistical advantages for separations and better show the comparable nature of IRMS and AMS in both the biogenic carbon analysis of bulk chemical classes, initial results from this study suggest that these should be pursued in order to proliferate this approach for quantifying biogenic carbon in transportation fuels to the refinery level, thereby potentially enabling process optimization in co-processing scenarios.

09 BIOMASS FUELS↗
DOE OSTI2024

AFC Metallic Fuel Research and Development 5-Year Plan

The mission of the U.S. Department of Energy (DOE) Advanced Fuel Campaign (AFC) program is conducting R&D on nuclear fuel technology that enables near- and long-term implementation of the reactor systems necessary to meet national nuclear energy objectives. Its primary goals align with goals of the DOE Office of Nuclear Energy in sustaining the current LWR fleet through Accident Tolerant Fuels program and Enabling Advanced Reactors. The latter goal is to be achieved through the following subgoals in order of logistical priority: • Establish the qualification basis for reference metallic fuel designs for sodium-cooled fast reactors. • Develop next generation metallic fuel fabrication and design for improved fissile utilization and management. • Develop accelerated fuel development and qualification methodologies. • Identify next generation fuel technologies. The purpose of this document is to serve as a five-year research and development (R&D) plan to achieve the goals identified to support enabling advanced reactor deployment related to metallic fuels starting in 2025. The specific objectives of this document are to: • align program R&D work across technical areas, national laboratories, and with stakeholder interests, and • aid yearly and outyear scope and budgetary planning activities. This plan lays the foundation of databases, capabilities, expertise, and research-commercial-regulatory integration for launching next-generation initiatives in advanced fuel technologies (fuel and cladding) and improved methodologies for achieving accelerated qualification of next generation fuel technologies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Technical and economic assessment of different options for minor actinide transmutation: the French case

Studies have been performed to assess the industrial perspectives of partitioning and transmutation of long-lived elements. These studies were carried out in tight connection with GEN-IV systems development. The results include the technical and economic evaluation of fuel cycle scenarios along with different options for optimizing the processes between the minor actinide transmutation in fast neutron reactors, their interim storage and geological disposal of ultimate waste. The results are analysed through several criteria (impacts on waste, on waste repository, on fuel cycle plants, on radiological exposure of workers, on costs and on industrial risks). These scenario evaluations take place in the French context which considers the deployment of the first Sodium-cooled Fast Reactor (SFR) in 2040. 3 management options of minor actinides have been studied: no transmutation, transmutation in SFR and transmutation in an accelerator-driven system (ADS). Concerning economics the study shows that the cost overrun related to the transmutation process could vary between 5 to 9% in SFR and 26 % in the case of ADS.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Materials Challenges and Opportunities for Energy Generation, Conversion, Delivery, and Storage (Applied Energy Tri-Laboratory Consortium Workshop Report)

This report documents the outcomes of the Tri-Laboratory Materials Workshop that was held July 31 and August 1, 2019 to begin addressing the needs, opportunities, and challenges associated with the development, fabrication, and testing of the needed materials and components for integrated hybrid energy systems (i.e., incorporating nuclear, fossil, and renewables for electric and thermal applications). This was accomplished by assembling the research program leads and principal investigators at Idaho National Laboratory (INL), National Energy Technology Laboratory (NETL), and National Renewable Energy Laboratory (NREL), who support the research and development of new technology and system integration. The team then identified and prioritized key materials development needs. This effort was intended to enhance communications and synergy among the Tri-Lab partners. Advanced functional and structural materials are central to transformative energy technologies for energy generation, conversion, delivery, and storage. With that in mind, the workshop focused on identifying and assessing the foundational materials research needs at both the basic and applied levels. Materials challenges include the ability to withstand harsh environments, such as high temperatures and pressures, corrosion, oxidation, or irradiation while maintaining flexible mission profiles and long service lifespans. Advanced energy system material challenges and needs range from materials for the capture, upgrading/concentration, storage, and delivery of low-grade heat to materials for high temperature environments that involve liquid metals, molten salt, and very high temperature gas heat delivery and storage systems. Material improvements are needed for hybrid energy systems due to accelerated corrosion and stress-fatigue failure of materials and equipment, which results from increased frequency and amplitude of thermal, mechanical, and electrical cycling of systems components. Multifunctional materials are needed for high temperature solid-oxide fuel cells, advanced electrochemical reactors, and in-process separation. Relative to materials manufacturing, application of advanced additive and subtractive methods need to be understood to develop both thin-layer homogenous materials and materials of graded composition. Materials modeling and machine learning will be critical to accelerate the design and production of power electronics, and nuclear reactor materials and fuel, as well as to gain an understanding of beneficial materials phenomena or deleterious microstructure evolution. There is also a need for standardized models, computational structures, data reporting protocols and modeling tools across the three laboratories. This would allow consistent results, analysis, and data sharing. Combining computational capabilities between the three laboratories (e.g., hardware, software) would greatly increase computational capabilities and throughput. The workshop identified the need for laboratories to anticipate and address problems that will occur during scale-up. Laboratory work must connect with industry to ensure that research focuses on processes that are scalable and marketable. Industry input and perspective are essential to guide laboratory research to meet these requirements and deploy new technology in industrial demonstrations. Another aspect of scale-up is the integration of multiple systems since new challenges often arise at the subsystem interfaces. Establishing a scale-up manufacturing demonstration/pilot plant, potentially as an industrial user facility, would be beneficial to the laboratories and industry. That modular scale-up manufacturing demonstration/pilot plant would allow researchers to find and resolve interface problems that cannot be identified by focusing only on individual parts. Communication exchanges among the organizers, attendees, and workshop survey responses indicate that the workshop was successful in achieving its goal to identify key technology gaps and research needs. Strong positive feedback was received on the sharing of ideas, capabilities, talent, and passion to move forward on the materials-related action items.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Full-Scale Crash Test of a MD-500 Helicopter with Deployable Energy Absorbers

A new externally deployable energy absorbing system was demonstrated during a full-scale crash test of an MD-500 helicopter. The deployable system is a honeycomb structure and utilizes composite materials in its construction. A set of two Deployable Energy Absorbers (DEAs) were fitted on the MD-500 helicopter for the full-scale crash demonstration. Four anthropomorphic dummy occupants were also used to assess human survivability. A demonstration test was performed at NASA Langley's Landing and Impact Research Facility (LandIR). The test involved impacting the helicopter on a concrete surface with combined forward and vertical velocity components of 40-ft/s and 26-ft/s, respectively. The objectives of the test were to evaluate the performance of the DEA concept under realistic crash conditions and to generate test data for validation of dynamic finite element simulations. Descriptions of this test as well as other component and full-scale tests leading to the helicopter test are discussed. Acceleration data from the anthropomorphic dummies showed that dynamic loads were successfully attenuated to within non-injurious levels. Moreover, the airframe itself survived the relatively severe impact and was retested to provide baseline data for comparison for cases with and without DEAs.

Kellas, Sotiris↗
DOE OSTI2016

Bisphenol-A sensors on polyimide fabricated by laser direct writing for on-site river water monitoring at attomolar concentration

This work presents an aptamer-based, highly sensitive and specific sensor for atto- to femtomolar level detection of bisphenol A (BPA). Because of its widespread use in numerous products, BPA enters surface water from effluent discharges during its manufacture, use, and from waste landfill sites throughout the world. On-site measurement of BPA concentrations in water is important for evaluating compliance with water quality standards or environmental risk levels of the harmful compound in the environment. The sensor in this work is porous, conducting, interdigitated electrodes that are formed by laser-induced carbonization of flexible polyimide sheets. BPA-specific aptamer is immobilized on the electrodes as the probe, and its binding with BPA at the electrode surface is detected by capacitive sensing. The binding process is aided by ac electroosmotic effect that accelerates the transport of BPA molecules to the nanoporous graphene-like structured electrodes. The sensor achieved a limit of detection of 58.28 aM with a response time of 20 s. The sensor is further applied for recovery analysis of BPA spiked in surface water. In conclusion, this work provides an affordable platform for highly sensitive, real time, and field-deployable BPA surveillance critical to the evaluation of the ecological impact of BPA exposure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Towards 50 Year Lifetime PV Modules: Double Glass vs. Glass/Backsheet

This award aims to increase the lifetime of c-Si modules by lowering the power degradation rate to the goal of 0.2 %/year, while also increasing the harvested irradiance per module using bifacial cells to achieve the 2030 SunShot goal of $0.03/kWh. Increasing the durability and lifetime of modules requires improved module packaging material choices and module architectures to exploit new cell improvements. Bifacial PERC cells (with backside aluminum fingers) are becoming a primary PV technology due to their decreased rear surface recombination and increased light absorption compared to traditional monofacial Al-BSF cells. Bifacial modules with double glass architectures have been deployed to capture the rear-side irradiance thereby increasing the light captured. The choice of a double glass (DG) or glass/backsheet (GB) module leads to two very different chemical (e.g., O 2 , H 2 O) and mechanical environments (e.g., mechanical stress levels) inside the PV module that impact the cell’s operational conditions. The recipient will fabricate 4-cell DG and GB minimodules with various module architectures or constructions (mono- & bifacial cells, transparent & white encapsulants), and conduct stepwise accelerated exposures and characterization.

14 SOLAR ENERGY↗
DOE OSTI2015

In-situ monitoring of flow-permeable surface area of high explosive powder using small sample masses

To ensure good performance of high explosive devices over long periods of time, initiating powders need to maintain their specific surface area within allowed margins during the entire duration of deployment. A common diagnostic used in this context is the Fisher sub-sieve surface area (FSSA). Furthermore, commercial permeametry instruments measuring the FSSA requires the utilization of a sample mass equal to the crystal density of the sample material, an amount that is often one or two orders of magnitude larger than the typical masses found in standard detonator applications. Here we develop a customization of the standard device that can utilize just tens of milligram samples, and with simple calibration yield FSSA values at ac curacy levels comparable to the standard apparatus. This necessitated a newly designed sample holder, made from a material of low coefficient of thermal expansion, which is conveniently transferred between an aging chamber and a re-designed permeametry tube. This improves the fidelity of accelerated aging studies by allowing measurement on the same physical sample at various time - instants during the aging process, and by obviating the need for a potentially FSSA-altering powder re-compaction step. We used the customized apparatus to monitor the FSSA evolution of a number of undoped and homolog-doped PETN powder samples that were subjected to artificial aging for several months at elevated temperatures. These results, in conjunction with an Arrhenius-based aging model were used to assess powder-coarsening - rates under long-term storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

State of Innovation 2025: Progress in Accelerating Next-Generation Cement and Concrete Technologies

The cement and concrete sectors are entering a decisive period as next-generation technologies advance from laboratory research to demonstration, early deployment, and first-of-a-kind commercial plants. Building on the 2024 State of Innovation report, the 2025 outlook highlights both the rapid acceleration of innovation and the urgent need for coordinated action across the value chain. Venture capital activity into the cement and concrete space stabilized following the record surge of 2022-2023, yet landmark financings, such as Sublime Systems' $200 million round and Terra CO2's $124 million Series B, signal continued investor confidence in companies approaching commercialization. Corporate procurement has become a powerful new catalyst, with Microsoft, Amazon, and CRH (Cement Roadstone Holdings) Ventures providing long-term commitments that underpin the first wave of next-generation cementitious products. The sector is shifting from early-stage experimentation toward the scaling of well-capitalized leaders capable of bridging the critical "capitalization gap." Early innovators continue to expand the toolkit through novel binders, electrochemical cements, biogenic limestone, and carbonate mineralization pathways. Going into 2026, cost competitiveness, durability validation, and scalability enabled by resilient supply chains remain the decisive factors for market adoption. At the 2025 Next Generation Cement and Concrete Critical Technologies Meeting, attendees emphasized dual-track funding strategies that integrate federal grants with private capital as key to enabling market breakthrough. State programs and corporate demand are sustaining momentum, while successful companies increasingly demonstrate both economic value and reduced dependence on imported materials. The National Concrete Pavement Technology Center and others underscored that broad integration of next-generation materials will hinge on standards compatibility, verified field performance, and workforce readiness. Colorado continues to serve as a proving ground through pilot programs that combine supplier training, phased implementation, and real-world data to de-risk innovation and provide replicable models for other regions. The 2025 Cement and Concrete Critical Technologies Workshop reinforced that scaling next-generation materials will require alignment among technology innovation, performance validation, and market demand. Stakeholders must move beyond siloed efforts toward collaborative frameworks that coordinate standards, funding, and infrastructure deployment. As a neutral convener and technical validator, the National Laboratory of the Rockies (NLR) plays a pivotal role in bridging innovation and market adoption through collaborative research, technology validation, and entrepreneurship programs. By uniting innovators, incumbents, policymakers, contractors, and investors, NLR and its partners are helping chart a credible pathway toward widespread commercialization in the decade ahead.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Accelerated beta radiation aging of interlayer titanium nitride in gallium nitride contacts

Currently, there is no good way to determine the influence of the radiation on the aging of betavoltaic electrical contacts. Here, this work tested a method to accelerate the aging of the contacts inside a betavoltaic by enhancing energy deposition within the interfacial region of interest. An electrical contact of gold-titanium on gallium nitride was aged by exposure to tritium betas and electrons in a beamline. The interface stoichiometry was compared to the electrical performance of the contact. The method to age the betavoltaic component could help predict lifetime performance of the internal electrical contacts and provide assurance of deployment reliability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Neural architecture codesign for fast physics applications

We develop a pipeline to streamline neural architecture codesign for physics applications to reduce the need for ML expertise when designing models for novel tasks. Our method employs neural architecture search and network compression in a two-stage approach to discover hardware efficient models. This approach consists of a global search stage that explores a wide range of architectures while considering hardware constraints, followed by a local search stage that fine-tunes and compresses the most promising candidates. We exceed performance on various tasks and show further speedup through model compression techniques such as quantization-aware-training and neural network pruning. We synthesize the optimal models to high level synthesis code for FPGA deployment with the hls4ml library. Additionally, our hierarchical search space provides greater flexibility in optimization, which can easily extend to other tasks and domains. We demonstrate this with two case studies: Bragg peak finding in materials science and jet classification in high energy physics, achieving models with improved accuracy, smaller latencies, or reduced resource utilization relative to the baseline models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗