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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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329 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mechanochemically responsive polymer enables shockwave visualization

Abstract Understanding the physical and chemical response of materials to impulsive deformation is crucial for applications ranging from soft robotic locomotion to space exploration to seismology. However, investigating material properties at extreme strain rates remains challenging due to temporal and spatial resolution limitations. Combining high-strain-rate testing with mechanochemistry encodes the molecular-level deformation within the material itself, thus enabling the direct quantification of the material response. Here, we demonstrate a mechanophore-functionalized block copolymer that self-reports energy dissipation mechanisms, such as bond rupture and acoustic wave dissipation, in response to high-strain-rate impacts. A microprojectile accelerated towards the polymer permanently deforms the material at a shallow depth. At intersonic velocities, the polymer reports significant subsurface energy absorption due to shockwave attenuation, a mechanism traditionally considered negligible compared to plasticity and not well explored in polymers. The acoustic wave velocity of the material is directly recovered from the mechanochemically-activated subsurface volume recorded in the material, which is validated by simulations, theory, and acoustic measurements. This integration of mechanochemistry with microballistic testing enables characterization of high-strain-rate mechanical properties and elucidates important insights applicable to nanomaterials, particle-reinforced composites, and biocompatible polymers.

Science & Technology - Other Topics↗
DOE OSTI2026

Active learning using hybrid surrogate tool life modeling for machining process optimization

Here, this paper describes an active learning approach for part-to-part iterative machining process optimization using a hybrid surrogate tool life model. A probabilistic interpolating tool life model is developed by combining the empirical Taylor-type tool life equation and the model fit error. The probabilistic tool life model is then used to calculate the machining cost per part distribution. The optimal machining parameters are selected using an expected improvement in machining cost per part criterion. The method is validated numerically using experimental results; the results show a median convergence error of 2.2% after three tests over 400 simulations. The method is validated experimentally on two industrial applications for Ti-6Al-4V roughing resulting in a cost per part reduction greater than 23% after two tests. The described method is a robust solution for rapid convergence to optimal machining parameters in an industrial production environment.

Active learning↗
DOE OSTI2024

Insights into the thermo-hydraulic properties of compacted MX80 bentonite during hydration under elevated temperature

In high-level radioactive waste geological repositories, compacted bentonite undergoes coupled thermo-hydraulic processes due to heat released from a central waste canister and groundwater imbibition from the surrounding host rock. An understanding of these processes is essential for long-term simulations of radionuclide migration and canister corrosion, which requires an understanding of temperature effects on the coupled thermo-hydraulic properties governing these processes. In this study, a tank-scale radial infiltration test was used to investigate water imbibition processes in compacted bentonite under a central heater temperature of 200 °C that simulates high thermal gradients in a repository. Interpretation of this test focuses on evaluation of the liquid water wetting front during hydration and the interpretation of the temperature-dependent transient soil water retention curve (SWRC), thermal conductivity function (TCF), and hydraulic conductivity function (HCF). The SWRC during imbibition follows a temperature-dependent wetting path. Temperature effects on the hydraulic conductivity of bentonite in saturated conditions had the greatest effect on the shape of the HCF, with minimal temperature effects at higher suctions. The transient thermal conductivity data matched well with a new TCF linked with the SWRC shape. Although the bentonite layer was restrained, local deformations during hydration may have affected the shapes of the TCF and HCF.

Engineering↗
DOE OSTI2026

Prime Time for Model-Predictive Control? Assessing the Technical and Market Readiness of Advanced Controls in Buildings

Despite three decades of extensive research and field testing that have consistently validated the benefits of Model Predictive Control (MPC) in building applications, the technology has seen limited market adoption. This paper evaluates the readiness of MPC for widespread deployment, showcases recent demonstrations and field tests across diverse building types, including residential, small commercial, large commercial, and campus settings. Our results demonstrate that MPC can optimize system operations to achieve load shifting, minimize curtailment of on-site generation, and reduce energy costs by up to 80 %, while maintaining or improving occupant comfort. We also show that MPC can effectively control large assets, such as MW-sized thermal storage systems, and respond to dynamic pricing signals. However, achieving scale remains difficult due to labor-intensive workflows, reliance on a “PhD-in-the-loop” for MPC design and maintenance, susceptibility to fragile data infrastructure, and persistent workforce education and acceptance barriers. To bridge this gap, we outline a transition from bespoke, labor intensive prototypes toward streamlined, segment-targeted deployment strategies that leverage model templates, semantic tools, and generative AI. By automating control configuration and reducing engineering effort, these recommendations provide a pathway for transforming successful research demonstrations into scalable, market ready solutions for MPC-based controls.

Pritoni, Marco↗
DOE OSTI2026

Model-based, in-situ, non-destructive qualification and certification of parts made by autonomous additive manufacturing

To address the significant productivity challenges associated with the qualification and certification (Q&C) tasks of additively manufactured (AM) parts, which have traditionally relied on rigorous post‐build inspection and testing, we propose an integrated framework that combines model‐based qualification and certification (MBQ&C) with autonomous additive manufacturing (AAM). MBQ&C employs high‐fidelity predictive models, developed within the Integrated Computational Materials Engineering (ICME) paradigm, to simulate process–structure–property–performance relationships for assessing a part’s fitness for use. Since predictive models are commonly machine learning (ML)-based or reduced-order surrogates of validated physics models, they run efficiently, enabling timely inference. In parallel, the self-driving AAM utilises ML-based adaptive, closed‐loop control strategies to avoid, mitigate, or repair defects and anomalies during fabrication, thereby increasing the likelihood of producing acceptable parts. A key feature of the combined AAM-MBQ&C framework is that predictive models explicitly incorporate defects or anomalies that persist after the build, using instance-specific data captured via in-situ sensing. This customisation enables a build‐specific assessment of fitness for use, rather than relying on nominal or generic parameters. Such individualised evaluation provides a robust basis for Q&C-related acceptance decisions relating to each build. Additionally, the rapid solution capabilities of ML or reduced-order models enable the determination of a part’s suitability for service shortly after build completion. As the framework matures, it has the potential to substantially reduce reliance on conventional point‐design approaches—such as time‐consuming post‐build computed tomography scanning and costly destructive testing. Thus, the AAM-MBQ&C framework represents a transformative, scalable strategy for quality assurance of AM components, as parts produced within a stable, validated, and certified envelope can be certified with reduced testing. Key benefits include: (1) significant gains in Q&C productivity through efficient, model-centric assessment; (2) performance-based classification of defects into critical and non-critical categories; (3) the ability to predict potential deviations in the performance of parts affected by real-time, adaptive process control interventions relative to those produced under a certified process, and (4) the enabling of virtual Q&C for service environments that are difficult, hazardous, or impractical to access or reproduce experimentally. Collectively, these capabilities strengthen the business case for AM, particularly for high‐consequence and mission‐critical applications. Finally, although this work focuses on powder-based AM, the proposed techniques could be extended to AM processes employing alternative feedstock forms.

Gunasegaram, Dayalan↗
DOE OSTI2026

Characterization of NBCMA—A DAPO Precursor

As part of our investigation into the process optimization of 2,6-diaminopyrazine-1-oxide (DAPO), small-scale sensitivity testing (impact, friction, and ESD) was conducted on the precursor, N-nitroso-bis(cyanomethyl)amine (NBCMA). NBCMA exhibited moderate sensitivity to friction, whereas no sensitivity to impact or spark was observed.

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

Large Language Model for Validation, Optical Calibration, and Learning (VOCAL) Distributed Temperature Sensing Interface

Distributed temperature sensing (DTS) using fiber optic sensors (FOS) offers a promising method for temperature measurements in advanced reactors, such as sodium fast reactors and molten salt cooled reactors. To support the calibration and validation of DTS measurements, Argonne National Laboratory developed the Validation, Optical Calibration, and Learning (VOCAL) software package. This report describes the integration of a local large language model (LLM) with a retrieval-augmented generation (RAG) system into the VOCAL interface to serve as an interactive user assistant. The LLM framework enhances the VOCAL platform’s accessibility to users by explaining interface components, clarifying inputs and outputs, and answering user queries dynamically in real-time. The accuracy of the LLM assistant performance was evaluated with 20 queries regarding the interface and its parameters using experimental data from the Thermal Hydraulic Experimental Test Article (THETA) facility. Results demonstrate that the LLM achieved a 95% accuracy rate, with a BERTScore of 0.8816 and SBERT value of 0.7417. Furthermore, validation of the RAG system within the LLM framework showed optimal accuracy with k-values between 1 and 2 using the k-refinement convergence test. The prompt perturbation analysis demonstrated good initial consistency for the RAG system, exhibiting the highest accuracy under punctuation variations and the greatest sensitivity under query reordering. Notably, the model’s errors were limited to data retrieval failures rather than factual hallucinations, reinforcing its baseline reliability. The integration of LLM provides a highly accurate, userfriendly enhancement to the VOCAL platform without disrupting its core computational capabilities for FOS calibration and validation.

Hong, Evan↗
DOE OSTI2026

Fast Growth of Ga2O3 on Highly Offcut (100)-Oriented Substrates

Beta-Ga2O3 has emerged as a leading candidate for next-generation power electronics, radio frequency (RF) switches, and extreme environment electronics due to a wide band gap (4.6 - 4.9 eV), high dopability (approximately 40 meV activation energy for an isolated silicon donor), and melt growth characteristics resulting in commercially available 4-inch substrates and commercial demonstrations of 6-inch substrates by multiple techniques. The (100) surface of Ga2O3 is highly desirable from a device and epitaxy standpoint - bulk growth of (100) material is more scalable than (010), the surface is nearly lattice-matched to p-type partner NiO, and Al2O3 incorporates at higher concentrations without phase separation. More importantly, the impact ionization coefficients along the [100] direction are low, leading to the highest possible critical fields. This is advantageous compared to the current state of the art, (001), due to reduced surface defects and increased possible breakdown voltage. However, the epitaxial growth rate on (100) surfaces is less than 10% of other faces due to weak bonding and favorable desorption, and on-axis (100) growth easily forms twin domains. Recent demonstrations have shown growth rate improvements from 0.4 nm/min to 1.5 nm/min by growing on (100) wafers that are offcut 6 degrees in the -c direction. These films show step-flow growth from (20-1) step-edges and high electron mobility due to suppressed twins. Despite these exciting results, offcuts greater than 6 degrees have not been explored due to the waste associated with grinding and polishing large offcuts. In this talk we will discuss the molecular beam epitaxy (MBE) growth and properties of Beta-Ga2O3 grown on (100) substrates offcut in the -c direction up to 13.4 degrees. These large offcuts are enabled by edge-fed film-defined growth (EFG) where the offcut is grown into the surface by pulling the crystal through the EFG die with the seed crystal rotated by the desired offcut angle. We will demonstrate that 13.4 degrees offcut substrates still exhibit a terraced (100) surface, and that a >10x increase (>5 nm/min) in growth rate is achieved. As previously reported on lower offcuts, we observe reversal of substrate twin domains around the (001) direction at the substrate-epilayer interface. We will discuss electrical properties including record-low (by MBE) unintentional doping densities of < 5E15 cm-3 and critical breakdown field in Schottky barrier diodes comparable with state-of-the-art (001) Ga2O3 without edge termination.

36 MATERIALS SCIENCE↗
DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler [National Renewable Energy Lab. (NR↗
DOE OSTI1988

Nuclear Safety [Vol. 29, No. 1, January-March 1988]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. THE CHERNOBYL ACCIDENT: 1 Core History and Nuclide Inventory of the Chernobyl Core at the Time of Accident by Gerald Kirchner and Cornelius C. Noack; GENERAL SAFETY CONSIDERATIONS: 6 Nonprescriptive Nuclear Safety Regulation: The Example of Loss of Offsite Power by M. W. Golay, V. P. Manno, and C. Vlahoplus, Jr., 20 Nuclear Power Safety Goals in Light of the Chernobyl Accident by C. Whipple and C. Starr; ACCIDENT ANALYSIS: 29 Containment Loads from Severe Accidents—U.S. Program by W. Kerr and M. K. Dey; PLANT SAFETY FEATURES: 36 Safety Characteristics of Modern High-Temperature Reactors: Focus on German Designs by W. Kröger, H. Nickel, and R. Schulten; ENVIRONMENTAL EFFECTS: 49 Radiation Hormesis and Nuclear Safety by C. C. Congdon; OPERATING EXPERIENCES: 58 Evaluation of Nonradiological Water Chemistry at Power Reactors by Harvey Zibulsky, James J. Kottan, Walter J. Pasciak, Mary Ann Castrogivanni, and Sujit Banerjee, 64 Reactor Shutdown Experience Compiled by J. W. Cletcher, 67 Operating U.S. Power Reactors Compiled by E. G. Silver; RECENT DEVELOPMENTS: 85 General Administrative Activities Compiled by E. G. Silver, 94 Reports, Standards, and Safety Guides by D. S. Queener, 100 Status of Power-Reactor Projects Undergoing Licensing Review Compiled by E. G. Silver, 103 Proposed Rule Changes as of Sept. 30, 1987; ANNOUNCEMENTS: 5 Northwestern University Short Course on Radiation Safety, 28 International Approach to Nuclear Safety (After Three-Mile Island and Chernobyl), 57 RPI Short Course on Modern Developments in Boiling Heat Transfer and Two-Phase Flow, 107 20th DOE/NRC Nuclear Air Cleaning Conference, 110 Third International Topical Meeting on Nuclear Power Plant Thermal Hydraulics and Operations, 108 The Authors, 111 Indexes to Nuclear Safety, Volume 28.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI1989

Nuclear Safety [Vol. 30, No. 3, July-September 1989]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 325 Safety of Framatome Advanced Nuclear Steam Supply Systems Designs by J. A. Charles and D. Lange, 333 Book Review of Nuclear Accidents: Intervention Levels for the Protection of the Public by H. B. Piper; ACCIDENT ANALYSIS: 335 Living PRA Computer Systems by S. C. Dinsmore and H.-P. Balfanz, 343 Summary of ICAP Assessments of RELAP5/MOD2 by W. E. Driskell and R. G. Hanson; CONTROL AND INSTRUMENTATION: 352 Thermal Performance Monitoring System at Maanshan Nuclear Power Plant by H.-J. Chao, Y.-P. Lin, G.-H. Jou, L.-Y. Liao, and Y.-B. Chen; DESIGN FEATURES: 358 Warning Systems for Nuclear Power Plant Emergencies by J. H. Sorensen and D. S. Mileti; WASTE AND SPENT FUEL MANAGEMENT: 371 Activities Related to Waste Management Compiled by E G. Silver; OPERATING EXPERIENCES: 382 Steam Generator Tube Performance: Experience with Water-Cooled Nuclear Power Reactors During 1985 by O. S. Tatone and R. L. Tapping, 400 Systems Interaction Analyses: Concepts and Techniques (Part II) by M. D. Muhlheim and G. A. Murphy, 413 Reactor Shutdown Experience Compiled by J. W. Cletcher, 416 Operating U.S. Power Reactors Compiled by E G. Silver; RECENT DEVELOPMENTS: 440 General Administrative Activities Compiled by E G. Silver, 460 Reports, Standards, and Safety Guides by D. S. Queener, 466 Status of Power-Reactor Licensing Activities Compiled by E G. Silver, 470 Proposed Rule Changes as of Mar. 31, 1989; ANNOUNCEMENTS: 334 Proceedings Published, 351 CEC Seminar on Methods and Codes for Assessing the Off-Site Consequences of Nuclear Accidents, 357 Short Course on Multiphase Flow and Heat Transfer: Bases and Applications in A: The Nuclear Power Industry B: The Process Industries, 357 International Conference on Probabilistic Safety Assessment and Management, 478 International Topical Meeting on the Safety, Status, and Future of Non-Commercial Reactors and Irradiation Facilities, 475 The Authors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Fluidized Bed Gasification For Conversion of Biomass and Waste Materials to Renewable Hydrogen

This project was undertaken in order to study the potential for hydrogen production, at low cost, from mixtures of biomass and municipal solid waste (MSW). This approach allows for the production of hydrogen with a very low fossil carbon burden, while taking advantage of tipping fees (associated with MSW) to improved process economics. The team sourced three primary feedstocks (wood, MSW, and waste plastics) and characterized them comprehensively using established techniques with a long track record in the field of gasification. All three primary feedstocks were highly reactive and lost most of their mass during initial devolatilization. The production of tars, including heavy tars, was quite high, and was most problematic in the case of the MSW and Waste Plastics feedstocks. Little practical difference was identified between the MSW and Waste Plastics materials, and the addition of bed-forming materials (dolomite and brown alumina) to the feedstocks was found to reduce production of tars during devolatilization under thermogravimetric analysis and/or Fischer Assay conditions. A series of four tests in a lab-scale bubbling-fluidized-bed gasifier, at 50 psig of pressure and about 825 C, confirmed these findings. Pellet feedstocks, broken into fragments, were used for these tests, and pellets comprised of 50% MSW and 50% biomass were found to be the best option in terms of fossil carbon burden, economic potential, and gasification characteristics. Tests were then undertaken in a pilot-scale gasifier facility based on the GTI U-Gas fluidized-bed gasification technology. The feedstock handling train of the 20 TPD U-Gas pilot-scale gasifier located in Des Plaines, IL, was operated under simulated gasification conditions, and the 50/50 pellets were found to be very robust and unproblematic. An improved design for the forward end of the feedstock injection screw of the gasifier was developed and installed. The design approach was based on improved passive cooling of the front-most shroud at the end of the screw, since this approach was found in comprehensive modeling studies to be more than sufficient to accomplish the project objectives associated with this phase of the work, while also avoiding thermal gradients that could have caused heat-stress-induced damage to the refractory around the feedstock inlet if an active cooling approach had been applied. Careful technoeconomic analysis (TEA) of two possible 1000 TPD facilities was carried out. The TEA of conversion of MSW with corn stover in one case, and MSW with woody feedstock in the other case, showed that both had the potential to provide hydrogen at about $1/kg (minimum selling price, 2018 dollar basis). Of the two TEA cases, the one that was based on the conversion of wood in the southeastern USA was found to have slightly better economic potential. The other TEA case was based on a real location in Nebraska and called for corn stover feedstock conversion along with MSW. An underserved communities outreach program plan was developed in cooperation with personnel from the Nebraska Public Power District.

08 HYDROGEN↗
DOE OSTI2026

Biodegradable Biocomposite Development for Large Scale Additive Manufacturing

Oak Ridge National Laboratory (ORNL) worked with Mitsubishi Chemical America, Inc. to develop a highly biodegradable ~100% biobased feedstock for large format additive manufacturing (AM). Together, they developed an AM feedstock based on the biobased polyester, polybutylene succinate (PBS), that is typically used in agriculture and packaging projects. The motivation for this work was to leverage the high degradability of this polymer in AM to create a new avenue for end-of-life disposal of the product. A composite feedstock was developed from PBS, polylactic acid (PLA), and wood flour (WF). While WF improves printability, reduces feedstock cost, and can improve stiffness, it also often results in a loss in tensile strength which can inhibit/limit applications of the material. To recover the loss in tensile strength suffered by including large quantities, up to 30 wt.% WF in the composite, a chain extender was used to compatibilize the different composite constituents with each other. The feedstock was used to 3D-print a demonstration mold for precast concrete catch basins and was tested by casting 750 lbs of concrete. The mold survived the demonstration. Aerobic degradation testing of the composite feedstock showed that it was highly degradable, 40% biodegradation after 90 days, compared to other incumbent biobased feedstocks.

100% biobased feedstock for large format additive ↗
DOE OSTI2023

A Self‐Healing System for Polydicyclopentadiene Thermosets

Self-healing offers promise for addressing structural failures, increasing lifespan, and improving durability in polymeric materials. Implementing self-healing in thermoset polymers faces significant manufacturing challenges, especially due to the elevated temperature requirements of thermoset processing. To introduce self-healing into structural thermosets, the self-healing system must be thermally stable and compatible with the thermoset chemistry. This article demonstrates a self-healing microcapsule-based system stable to frontal polymerization (FP), a rapid and energy-efficient manufacturing process with a self-propagating exothermic reaction (≈200 °C). A thermally latent Grubbs-type complex bearing two N-heterocyclic carbene ligands addresses limitations in conventional G2-based self-healing approaches. Under FP's elevated temperatures, the catalyst remains dormant until activated by a Cu(I) co-reagent, ensuring efficient polymerization of the dicyclopentadiene (DCPD) upon damage to the polyDCPD matrix. The two-part microcapsule system consists of one capsule containing the thermally latent Grubbs-type catalyst dissolved in the solvent, and another capsule containing a Cu(I) coagent blended with liquid DCPD monomer. Using the same chemistry for both matrix fabrication and healing results in strong interfaces as demonstrated by lap-shear tests. In an optimized system, the self-healing system restores the mechanical properties of the tough polyDCPD thermoset. Self-healing efficiencies greater than 90% via tapered double cantilever beam tests are observed.

36 MATERIALS SCIENCE↗
DOE OSTI2026

SAM Code Enhancements for Fission Product Tracking of Noble Gases and Metals in MSRs

This report documents fiscal year 2026 enhancements to the System Analysis Module (SAM) for modeling fission product transport in liquid-fueled molten salt reactors (MSRs). The work advances three principal areas: noble gas transport, noble metal deposition, and user interface improvements. The noble gas transport capability integrates drift-flux gas transport, Henry’s law two-film interphase mass transfer with pressure-based nucleation suppression, Knudsen-regime pore diffusion into porous graphite with a conjugate salt-graphite interface constraint, built-in material properties, five Sherwood-number mass transfer correlations including three derived from high-fidelity NekRS simulations, and xenon-135 reactivity feedback through SAM’s point-kinetics model. This work also presents a comprehensive verification test suite, including new analytically verified cases for pressure-dependent onset of interphase gas transfer in a stagnant vertical pipe, a postulated FLiBe-graphite Xe extraction permeator, a gravity riser with a fission-product source, and a descending pipe with gas redissolution driven by hydrostatic pressure. A machine learning framework for bubble rise velocity prediction in molten salt systems is developed and benchmarked on molten-salt and diverse aqueous bubble datasets. The best-performing fine-tuned transfer-learning networks achieve an 82% reduction in RMSE relative to the Clift correlation, and is implemented directly in SAM. The noble metal transport capability is developed, including a liquid-wall deposition model and a gas-surface flotation mechanism that transfers insoluble particles entrained by sparging gas to wetted structures. Verification tests and demonstration cases cover the surface deposition, flotation efflux, and flotation shedding. Finally, a new [SpeciesTransport] input structure replaces positional global vectors with selfcontained, order-independent, named species blocks, simplifies the specification of multiphase species and decay chains, and remains fully compatible with existing SAM input files. Together, these developments improve the physical fidelity, verification basis, and usability of SAM for system-level analyses of fissionproduct behavior in MSRs.

Mui, Travis (ORCID:0000000303736470)↗
DOE OSTI2008

Vehicle Technologies Program: Energy Storage R&D (2008 Annual Progress Report)

One of the primary objectives of the Energy Storage effort is the development of durable and affordable advanced batteries (and ultracapacitors) for use in a full range of vehicle applications, from start/stop to full-power HEVs, EVs, and PHEVs. The battery technology development activity spans three areas: system development of full battery systems; benchmark testing of emerging technologies in order to remain abreast of the latest industry developments; and Small Business Innovative Research (SBIR) to fund early-stage R&D for small businesses/entrepreneurs.

25 ENERGY STORAGE↗
DOE OSTI2026

Toyota Highlander FCHV (CRADA CRD-12-00469 Final Report)

This project relates to the loan of four Toyota Mirai FCEV-adv vehicles to NLR to provide a load (vehicles to fill with hydrogen) to our fueling station research facility to study hydrogen fueling infrastructure performance using 700 bar precooled hydrogen at ESIF’s Hydrogen Infrastructure Testing and Research Facility (HITRF) facility.

33 ADVANCED PROPULSION SYSTEMS↗