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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul [National Renewable Energy Lab. (NREL↗
DOE OSTI2024

The cluster decomposition of the configurational energy of multicomponent alloys

Abstract The cluster expansion method (CEM) is a widely used lattice-based technique in the study of multicomponent alloys. Despite its prevalent use, a clear understanding of expansion terms is lacking. We present a modern mathematical formalism of the CEM and introduce thecluster decomposition—a unique and basis-independent decomposition for functions of the atomic configuration in a crystal. We identify the cluster decomposition as an invariant ANOVA decomposition; and demonstrate how functional analysis of variance and sensitivity analysis can be used to interpret interactions among species. Furthermore, we show how the mathematical structure of the cluster decomposition enables numerical evaluation that scales with the number of clusters and is independent of the number of species. Overall, our work enables rigorous interpretations of interactions among species, provides opportunities to explore parameter estimation beyond linear regression, introduces a numerical efficient implementation, and enables analysis of cluster expansions based on established mathematical and statistical principles.

Chemistry↗
DOE OSTI2026

Final Report: Process Intensification of Hydrogen Production through Sorption-Enhanced Gasification of Biomass

The University of Utah, in partnership with Idaho National Laboratory (INL), evaluated Sorption-Enhanced Gasification (SEG) as a transformative pathway for producing hydrogen with the potential for negative CO 2 emissions. SEG integrates gasification, water-gas shift, and in-situ carbon capture within a dual fluidized bed reactor to enable efficient clean hydrogen production. Key challenges related to biomass variability and process complexity were addressed through feedstock engineering, reaction optimization, and process validation. A co-pelletized biomass–limestone feedstock was developed to simplify feeding and introduction of makeup limestone. Kinetic and sorbent studies identified optimal operating conditions and confirmed the suitability of low-cost limestone, while catalysts were developed to reduce tar formation. Reactor modeling and techno-economic analysis indicated that SEG can achieve competitive hydrogen production costs, particularly when combined with carbon incentives, supporting its potential for scale-up and carbon-negative operation.

08 HYDROGEN↗
DOE OSTI2025

The glass-ceiling convective regime and the origin and diversity of coronae on Venus

Venus and Earth are rocky planets of roughly the same size and bulk density, yet their surface volcanic and tectonic features appear substantially different. On Venus, the coexistence of large volcanic highlands—interpreted as the surface expression of long-lived mantle plumes—alongside coronae, smaller features thought to be caused by transient thermal diapirs, remains enigmatic. Using two-dimensional numerical models of mantle convection with sharp and broad mineral phase transitions for pyrolite, we show that both scales of upwellings can be generated in a stagnant lid planet with an interior temperature 250 to 400 K warmer than Earth’s. The smaller plumes originate from a ~600 km deep internal layer that exists as a consequence of the different sequence of mineral phase transitions that occur in warmer mantles less processed and differentiated by partial melting and volcanism. Future models that include melting will provide further tests of our hypothesis.

Science & Technology - Other Topics↗
DOE OSTI2025

Crystal Growth Scale-Up and Stability of RbSr 2 X 5 :Eu Scintillators

The discovery and development of new scintillation materials support national security needs. In these applications, large volumes of scintillator crystals are needed to achieve efficient screening for contraband. Therefore, one important step in the discovery of new scintillator compositions is testing their feasibility for scale-up and their stability. In this work, high-quality Ø22 mm crystals of two new scintillators RbSr 2 Br 5 :Eu and RbSr 2 I 5 :Eu were grown via the Vertical Bridgman method, and their scintillation properties were characterized. Here, the Ø22 mm RbSr 2 I 5 :Eu crystals could be grown with fast translation rates up to 3.5 mm/h. Both RbSr 2 Br 5 :Eu and RbSr 2 I 5 :Eu had high scintillation performance, including light yields of 46,000 and 61,000 ph/MeV, respectively, for Ø22 × 35 mm crystals. Additionally, properties related to physical stability were investigated, including the coefficients of thermal expansion via high-temperature X-ray diffraction (HTXRD) as well as moisture sensitivity. HTXRD confirmed the absence of solid–solid phase transitions and showed that RbSr 2 Br 5 had minimal thermal expansion anisotropy compared to RbSr 2 I 5 and some other inorganic metal halide scintillators, which favors the growth of large-sized crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Liquified SO 2 induced solid/cathode electrolyte interphase for lithium ion batteries

Formation of robust solid/cathode electrolyte interphases (S/CEI) is vital for long-term stability and high-performance operation of lithium-ion batteries (LIBs), particularly under high voltage regimes. However, engineering electrochemically stable S/CEIs that effectively suppress interfacial side reactions remains a key challenge. Herein, we introduce a liquefied sulfur dioxide (SO 2 )– ionic liquid complex as a fluorine-free multifunctional electrolyte additive for the first time that significantly improves the formation of sulfate/sulfite-rich S/CEI layers at both graphite and NMC811 interfaces. The unique SO 2 -N coordination with a 1,2,4-triazolide-based ionic liquid enables homogeneous SO 2 dissolution, resulting in controlled SO 2 decomposition during the initial electrochemical cycle. This decomposition yields sulfur-rich interphase species that stabilize the electrolyte-electrode interface, reduce impedance growth, and lessen electrolyte decomposition. Electrochemical tests show significantly improved cycle life, reduced polarization, and increased Coulombic efficiency for both anodes and cathodes. XPS confirms the presence of SO 2 -derived surface species that contribute to interfacial stability. In conclusion, this approach highlights a new direction for interphase engineering using liquefied gas additives and opens pathways for sulfur-based S/CEI chemistry in advanced battery systems.

Graphite↗
DOE OSTI2026

Staged Z-pinch experiment at the double-EAGLE pulsed power facility

The staged Z-pinch is a potential high-energy gain fusion concept where a high atomic number liner implodes on a deuterium target using a pulsed multi-MA current source. Over the past several years this concept has been studied on 0.5–1.0 MA facilities using Ar and Kr gas puffs injected at R = 1.2 cm. Neutron yield up to (2.5 ± 0.34) x 10 10 was measured, Ruskov et al (2023 IEEE Trans. Plasma Sci. 51 3310–6). Here, in this study, we present experimental results from the 4 MA, 110 ns current rise time Double-EAGLE facility at L3Harris (currently, Fisica Inc.) where a larger radius nozzle created gas density profiles peaked at R = 2.5 cm. Modeling with the MACH2 and FLASH codes indicates that the larger radius allows stronger acceleration of the liner plasma and generation of shock waves that preheat a target plasma layer next to the liner to temperatures $T_i >$1 keV. The resulting counter thermal pressure on the liner plasma limits the growth of the Magneto-Rayleigh–Taylor (MRT) instability at the liner-vacuum boundary and the implosion proceeds in a relatively stable manner. Near bang time the enormous target plasma thermal pressure smoothens the MRT perturbations developed during the earlier implosion stages. Time integrated x-ray pinhole images with cutoff energy of 100 eV confirm that a long (∼3 cm), stable and uniform high energy density plasma column is formed in the final implosion stage. Consistent neutron yield in the 10 10 –10 11 range was measured for both Ar and Kr liners imploding on a deuterium target.

Physics - Plasma physics↗
DOE OSTI2023

Composite Lithium Metal Structure to Mitigate Pulverization and Enable Long‐Life Batteries

In lithium metal batteries, non‐uniform stripping of lithium results in pit formation, which promotes subsequent non‐uniform, dendritic deposition. This viscous cycle leads to pulverization of lithium which promotes cell shorting or capacity degradation, symptoms further exaggerated by high electrode areal loading and lean electrolytes. Here, to address this challenge, a composite lithium metal anode is engineered that contains uniformly distributed, nanometer‐sized carbon particles. This composite lithium is shown to strip more uniformly since the growth of non‐uniform pits is intercepted by the carbon particles. This mechanism is corroborated by a continuum electrochemical model. Subsequent lithium deposition on carbon particles is also found to be more uniform than on the surface with irregular pits. Notably, the pulverization rate of composite lithium is 26 times slower than that of commercial lithium. Moreover, in a Li‐S battery with sulfurized polyacrylonitrile cathode, the use of the composite anode extends the cycle life by three times when the areal capacity is 8 mAh cm −2 . The approach of using an engineered lithium composite structure to address challenges during both stripping and plating can inform future designs of lithium metal anodes for high areal capacity operations.

high areal capacity↗
DOE OSTI2026

ClassNMSW- a real-time classification approach for non-recycled municipal solid waste using hyperspectral imaging

Real-time classification of non-recycled municipal solid waste (NMSW) is essential for efficient valorization. This study introduces ClassNMSW, a comprehensive framework for classifying 22 NMSW subclasses under industrial constraints by using hyperspectral imaging (HSI). A primary innovation of this work is the development of a variance-controlled spectral extraction algorithm. Unlike traditional methods that rely on simple averaging, this approach systematically investigates the extent of pixel extraction to minimize the loss of critical chemical information while maximizing data reduction thus ensuring high spectral fidelity with low computational cost. The approach developed in this work integrates automated, computer-vision-based background removal, eliminating the need for the manual thresholding common in current literature. To resolve ambiguities among chemically similar subclasses, a tiered classification and multi-camera fusion strategy (NIR17 and NIR22) is implemented. Results demonstrate that ClassNMSW achieves an object-wise weighted accuracy of 98.70% for single-sensor configurations and 100% under sensor fusion. A novel rolling-window strategy satisfies desired end-to-end latency of <2 s, satisfying the strict deterministic requirements of high-speed industrial sorting environments. The ClassNMSW framework provides a scalable foundation for advancing circularity and resource recovery in large-scale waste valorization operations.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

High-Temperature SiC Cladding End Plug Irradiation Design and HFIR Readiness

This report documents the design of a High Flux Isotope Reactor (HFIR) irradiation experiment intended to evaluate irradiation effects on the hermeticity of silicon carbide (SiC) end plug specimens under a radial fast neutron flux gradient at representative light-water reactor (LWR) temperatures of approximately 300 °C. The overarching goal of this work is to statistically evaluate SiC end plug hermeticity and mechanical properties following irradiation using the high-throughput irradiation capability discussed here. Each specimen consists of a short section of SiC fiber–reinforced SiC (SiC/SiC) tube with a single monolithic SiC end plug joined to one end. The experiment allows up to 66 specimens to be irradiated in six different stacks within a dry, sealed irradiation capsule derived from the previously developed high-temperature SiC/SiC cladding bowing experiment. The neutronics basis, thermal analysis, and HFIR readiness of the experiment are discussed in this report for two possible design cases. The first design case is based on existing approval documentation and components that are on hand and approved for use, so the experiment insertion would require only specimen receipt, specimen pre-irradiation characterization, experiment assembly, and final fabrication package approval. The second design case provides improved thermal robustness and the preferred end plug geometry but requires fabrication of a modified holder and revisions to the HFIR approval documentation, in addition to the other activities required for the first design case, before insertion.

Hott, Daniel [Oak Ridge National Laboratory (ORNL)↗
DOE OSTI2026

Semi-Dynamic Leach Testing of Densified Silicon-based Iodine Waste Forms

Iodine waste forms (IWF) require a conceptual corrosion release model (CCRM) to provide iodine (I) release rates for performance modeling nuclear waste disposal repositories. To develop a CCRM, an understanding of the corrosion mechanisms of the IWF are required along with data from consistent test methods to parameterize the model. The present study has advanced both areas by providing and assessing the corrosion resistance of IWF types based on their processing history in minor variations of semi-dynamic leach tests. The test included a series of semi-dynamic leach tests using monolithic IWFs in deionized water (leachant). Several experiments were conducted under alternate test conditions with changes to temperature, leachant replacement, leachant pH, leachant volume, masking, and surface finish to elucidate if varying these conditions impacted IWF corrosion behavior. Tests were conducted on two classes of IWFs: (1) I-bearing silver-mordenite (AgZ) materials processed by hot isostatic pressing (HIP) at different temperatures, pressures, sizes, and times; and (2) I-bearing silver-functionalized silica aerogels (SFA) processed by either HIP or spark plasma sintering (SPS). The corrosion susceptibility of AgZ samples was influenced by HIP temperature and pressure. The SPS SFAs retained I far better than HIP SFAs. Additional findings in this study include: (1) The iodine dissolution rate decreased with decreasing temperature, (2) a common ion effect may occur and slow dissolution of the host phase if the leachant is not regularly replaced, (3) pH controls the dissolution rate, and (4) the iodine dissolution rate slows with extended test time (up to 224 days). Based on this work, these parameters should thus be represented when developing a CCRM.

corrosion↗
DOE OSTI2026

A generative machine learning model for designing metal hydrides applied to hydrogen storage

Developing new metal hydrides is a critical step toward efficient hydrogen storage in carbon-neutral energy systems. However, existing materials databases, such as the Materials Project, contain a limited number of well-characterized hydrides, which constrains the discovery of optimal candidates. This work presents a framework that integrates causal discovery with a lightweight generative machine learning model to generate novel metal hydride candidates that may not exist in current databases. Using a dataset of 450 samples (270 training, 90 validation, and 90 testing), the model generates 1000 candidates. After ranking and filtering, six previously unreported chemical formulas and crystal structures are identified, four of which are validated by density functional theory simulations and show strong potential for future experimental investigation. Overall, the proposed framework provides a scalable and time-efficient approach for expanding hydrogen storage datasets and accelerating materials discovery.

generative model↗
DOE OSTI2023

Dense nuclear matter equation of state from heavy-ion collisions

The nuclear equation of state (EOS) is at the center of numerous theoretical and experimental efforts in nuclear physics. With advances in microscopic theories for nuclear interactions, the availability of experiments probing nuclear matter under conditions not reached before, endeavors to develop sophisticated and reliable transport simulations to interpret these experiments, and the advent of multi-messenger astronomy, the next decade will bring new opportunities for determining the nuclear matter EOS, elucidating its dependence on density, temperature, and isospin asymmetry. Among controlled terrestrial experiments, collisions of heavy nuclei at intermediate beam energies (from a few tens of MeV/nucleon to about 25 GeV/nucleon in the fixed-target frame) probe the widest ranges of baryon density and temperature, enabling studies of nuclear matter from a few tenths to about 5 times the nuclear saturation density and for temperatures from a few to well above a hundred MeV, respectively. Collisions of neutron-rich isotopes further bring the opportunity to probe effects due to the isospin asymmetry. However, capitalizing on the enormous scientific effort aimed at uncovering the dense nuclear matter EOS, both at RHIC and at FRIB as well as at other international facilities, depends on the continued development of state-of-the-art hadronic transport simulations. Furthermore, this white paper highlights the essential role that heavy-ion collision experiments and hadronic transport simulations play in understanding strong interactions in dense nuclear matter, with an emphasis on how these efforts can be used together with microscopic approaches and neutron star studies to uncover the nuclear EOS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Analysis of Liquids Using the Submerged Plasma for Isotopic Detection and Elemental Resolution (SPIDER)

We developed a sensor called the Submerged Plasma for Isotopic Detection and Elemental Resolution (SPIDER) probe, which uses an atmospheric pressure glow discharge below the surface of liquids to excite species in the liquid. Through emission spectroscopy of molten salts, liquid metals, and heavy water, we demonstrated the SPIDER probe’s high resolution, accuracy, and versatility. We successfully identified trace concentrations of transition and rare-earth metals in molten salts and detected the isotopic shift of the H β → D β emission line. Our analysis revealed unconventional spectral alkali line shapes, indicating two competing excitation modes: film explosion and droplet vaporization. The film explosion mode, characterized by dense plasma, exhibited self-reversal and broadband continuum emission, while the droplet vaporization mode, associated with diffusive plasma, produced narrow-line emissions. Furthermore, by analyzing circuit transients alongside individual plasma events, we observed that film explosions generate higher currents, likely due to a shorter plasma length as the current preferentially flows through the thin liquid layer. Altogether, our results highlight the SPIDER probe’s efficacy and flexibility, making it well-suited for online material quantification of liquids in extreme environments.

AES↗
DOE OSTI2026

Data-Driven Discovery and Experimental Validation of Solvent Polarity Effects on Conjugated Polymer Solution-to-Film Assembly Pathways

Understanding how solvent properties influence the solution-to-film assembly of conjugated polymers remains a critical challenge due to the complex and intertwined nature of polymer–solvent interactions. In this study, we integrate a data-driven framework with experimental validation to identify key parameters influencing the assembly and performance of poly[2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl)thieno[3,2-b]thiophene)] (DPP-DTT) in organic field-effect transistors (OFETs). A machine learning (ML) approach identified the normalized Reichardt polarity parameter (E T N ) as a significant descriptor correlated with DPP-DTT hole mobility (μ). Systematic DPP-DTT devices fabricated using solvents across a wide E T N range revealed that higher E T N solvents yield enhanced μ. To elucidate the structural origins of high μ, we conducted comprehensive analyses using UV–vis–NIR spectroscopy and grazing incidence wide angle X-ray scattering (GIWAXS) measurements. The results revealed that films processed from high E T N solvents exhibit reduced paracrystallinity. By analyzing the solution-state behavior using optical microscopy and solution WAXS, we revealed polymer solubility differences in the various solvents and associated distinct polymer assembly pathways, elucidating why the high E T N solvent produces long-range ordered films. Notably, the high E T N solvent shows a pronounced preference for liquid-crystal (LC)-mediated assembly, providing a mechanistic explanation for the enhanced structural order. Therefore, these results demonstrate that solvent polarity, as evaluated by E T N , serves as an important parameter that plays a significant role in the DPP-DTT assembly pathway and resultant solid-state morphology. This work provides a strategy for integrating data science with experiments to identify critical parameters associated with complex polymer systems and helps guide rational process design for high-performance organic electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Internet of Things Data Characterization Process: Pattern of Life Behavioral Data Study

The HoneyBee™ TARDIS LDRD team completed a data scoping study that identified the initial processes and procedures to baseline the normal and expected behaviors during operability and interoperability of Internet of Things (IoT) device networks. This research is the initial step in developing a process (or methodology) to inform a much broader information framework incorporating machine learning to determine device pattern-of-life which enables the detection of abnormal IoT behaviors on an individual device, as well as in the context of a larger network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Observed Land Surface Influence on Atmospheric Heat and Moisture Profiles During Interstorms

Land-atmospheric (L-A) feedbacks have historically been studied using models whose structure and parameterizations influence outcomes and insights. The representation of L-A feedbacks based on observations alone remains an ongoing challenge for understanding boundary layer development and precipitation. To address this gap, we use ground-based passive remote sensing and in-situ observations to present an analysis of the atmosphere during 103 interstorm soil moisture drydown events spanning nine warm seasons (2016–2024) in the U.S. Southern Great Plains region. By separating events based on local L-A coupling signals and characterizing the profiles of atmospheric heat and moisture to surface energy flux behavior, we investigate the physical mechanisms linking land surface processes to boundary layer development. We find that during interstorm drydowns, the atmospheric column follows a consistent pattern: moisture increases within the boundary layer, peaks near its top, and declines rapidly above, while warming occurs through the depth. Drydowns that shift toward evaporation produce stronger and deeper thermodynamic responses than cases dominated by sensible heating, which are weaker and shallower. Additionally, moisture is accumulated faster within the boundary layer during shorter drydowns, with longer drydowns representing slower, moisture-limited growth. Drydowns with wetter initial soil moisture will sustain stronger moistening within and above the boundary layer, accelerating buoyancy growth and convective potential toward the next storm. These results provide observational evidence linking surface flux evolution to boundary layer thermodynamics and offer a process-level benchmark for evaluating coupled L-A representations in models and demonstrating the influence of soil moisture on short-term weather forecasting skill.

Zhang, M. S. [Massachusetts Inst. of Technology (M↗