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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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NASA NTRS2026

PROTECT: Production and Reuse of Thermally Efficient Ceramic Thermal Protection Systems

PROTECT (Production and Reuse Of Thermally Efficient Ceramic TPS) is a NASA Early Career Initiative focused on developing the next generation of reusable ceramic thermal protection systems (TPS). This project addresses key challenges in TPS design, including temperature capability, thermal stability, and refurbishment time, by integrating novel material development with predictive modeling. Leveraging enhanced capabilities in NASA’s Porous Microstructure Analysis (PuMA) software, PROTECT introduces new modeling tools to predict the thermal and mechanical behavior of fibrous ceramic materials. These tools enable accurate prediction of performance metrics such as thermal conductivity and structural integrity, reducing reliance on costly physical testing. Preliminary advances in these areas will be presented. To support model validation, PROTECT is building a comprehensive database of raw material properties using advanced characterization techniques, including micro computed tomography (CT) scanning in collaboration with the University of Illinois Urbana-Champaign (UIUC). The presentation will detail the sampling workflows and analysis methods used to generate this detailed microstructural data and how it is used to develop improved models in PuMA. This multi-center collaboration, spanning NASA (JSC, ARC, KSC, GRC), Oak Ridge National Laboratory, UIUC, and SpaceX, is developing tailored TPS solutions for LEO, lunar, and Martian missions. By bridging heritage systems with the demands of modern spaceflight, PROTECT contributes to the advancement of reusable TPS technologies for future exploration missions.

Propulsion, Refractory, and Coating Materials↗
DOE OSTI2025

High-voltage water-scarce hydrogel electrolytes enable mechanically safe stretchable Li-ion batteries

Soft Li-ion batteries, based on conventional organic electrolytes, face performance degradation challenges due to moisture penetration and safety concerns due to possible leakage of toxic fluorine compounds and flammable solvents under mechanical damage. We design a water-scarce hydrogel electrolyte with fluorine-free lithium salt to achieve wide electrochemical stability window (up to 3.11 volts) in ambient air without hermetic packaging while balancing high stretchability (1348%), ion conductivity (41 millisiemens per centimeter), and self-healing capabilities for mechanically and chemically safe stretchable Li-ion batteries. Molecular synergy between hydrophilicity and lithiophilicity of zwitterionic polymer backbone is revealed by molecular dynamics simulations. The battery exhibits capacity retention under harsh mechanical stresses—enduring stretching, twisting, folding, and multiple through-punctures by a needle—while self-healing from repeated through cuts by a razor blade. Stable ambient operation for 1 month over 500 charge-discharge cycles (average coulomb efficiency, 95%) is achieved. A prototype self-healing electronic system with embedded soft batteries demonstrates practical application as a durable embodied energy source.

Science & Technology - Other Topics↗
DOE OSTI2026

Reduced-order CFD modeling of cryogenic hydrogen isotope extrusion for pellet fueling

This study presents a reduced-order model (ROM) for computational fluid dynamics (CFD) simulations of cryogenic hydrogen isotope extrusions, focusing on protium (H₂) and deuterium (D₂) piston extruders. Using a 2D axisymmetric ROM in ANSYS-Polyflow, significant computational savings were achieved (runtime reduced from 9∼24 h to 3∼5 min), with extrusion force discrepancies between the 2D ROM and 3D models being on the order of 1%. Parametric studies identified optimal cutoff shear rates in the viscosity model (0.01/s for H₂ and 0.001/s for D₂), providing recommendations for future simulations. Finally, a comprehensive comparison of ROM results with experimental data was performed across varying geometries, cryogenic materials, temperatures, extrusion lengths, and piston velocities. Predictions at low extrusion temperatures met the objective of providing quick and efficient solutions with an acceptable extrusion force error of approximately 10% or less, validating the effectiveness of the 2D ROM approach. However, at high temperatures closer to the triple point, extrusion force error grows, which necessitates developing an improved model that accounts for temperature effects, e.g. melting. Nevertheless, the findings still represent a significant improvement in efficiency of CFD modeling of cryogenic hydrogenic extrusion. The ROM framework can also be extended to tritium (T2) and screw extruders, which will ultimately provide a fast and effective tool for optimizing pellet injector design for ITER and future reactor systems.

Fan, Joy [ORNL] (ORCID:0000000229751735)↗
DOE OSTI2025

Cyclic Peptides for Lanthanide Binding

Lanthanide ions are difficult to separate from one another due to their similar chemical properties. The discovery of lanthanide-binding peptides and proteins in nature has led to an increased interest in the possibility of utilizing the strong binding of peptides to lanthanide ions for their separations; as such, there has been an effort to identify or design peptides with improved lanthanide binding and selectivity toward particular lanthanide ions. Here, in this study, we designed and characterized lanthanide-binding cyclic peptides (LBCPs) with molecular dynamics simulations, electronic structure calculations, and emission spectroscopy. Luminescent decay measurements were done to determine the number of water molecules coordinated to the Eu 3+ ion in Eu-LBCP complexes and compare to the predicted number of water molecules by computation to assess the lanthanide-binding affinity of LBCPs. Measured stability constants show binding of the LBCPs to the Eu 3+ ion with stronger than micromolar affinity. We were able to identify multiple peptides that selectively bind to middle lanthanides. We describe the structural basis of the lanthanide-binding selectivity trend with strongest binding to the middle lanthanides, followed by the heavier lanthanides, and finally to the lighter ions.

ions↗
NASA NTRS2026

Hermal Evolution of Volatile-Rich Planetesimals: Implications for Lithological Diversity in Ryugu and CI Chondrites

Ryugu samples and CI chondrites record aqueous alteration processes in primitive, volatile-rich planetesimals and exhibit a wide range of lithologies defined by mineral assemblages and alteration degrees as proposed to be types I–VI in [4]. The similarity in lithological diversity and proportions between Ryugu and CIs suggests that they originated from parent bodies with comparable internal structures and thermal histories. However, the mechanism responsible for generating such lithological diversity within a single parent body remains unclear.

S Yamazaki↗
DOE OSTI2026

Domestically Manufactured Fuel Cells for Heavy Duty Applications

This project, funded by the U.S. Department of Energy under Award DE-EE0009248, advances the domestic development of fuel-cell stack technologies for heavy-duty transportation applications. The work directly supports the Million-Mile Fuel Cell Truck (M2FCT) initiative by improving performance, durability, and manufacturability—key requirements for next-generation hydrogen fuel-cell systems.

08 HYDROGEN↗
DOE OSTI2026

Nanoscale Compositional and Strain Gradients Enable High‐Speed and Amplitude‐Resolved Pyroelectric Sensing

The frequency response of pyroelectric sensors is fundamentally governed by thermal time constant (τth, determined by thermal mass and thermal conductance) and electrical impedance arising from film capacitance and readout circuit. Conventional bulk LiTaO3 detectors are optimized for high responsivity at low modulation frequencies (0.1-10 Hz), possessing a large τth that thermally averages rapid temperature oscillations at elevated modulation frequencies, limiting fidelity in resolving dynamic varying thermal signals. Here, compositional and strain gradients are introduced into 100-nm-thick relaxor-ferroelectric films reducing τth to ≈2 µs and producing built-in potentials (≈1.45 V or 145 kV cm-1) that enhance the pyroelectric coefficient and suppress the dielectric constant. This enables complementary dual-mode operation by enhancing current-mode electrical responsivity and improving the voltage-mode figure of merit - advantageous for superior temperature resolution (ΔTmin ≈ 30 µK). The responsivity peak shifts to near 1 kHz (>2500-times higher than conventional bulk sensors), with measurable responsivity extending to a carrier frequency of 100 kHz and amplitude-resolved detection at modulation frequencies up to 15 kHz. These results establish nanoscale internal-field engineering can reshape electro-thermal trade-off in pyroelectric thin films toward zero-bias, high-thermal-sensitivity, and amplitude-resolved thermal sensing across a wide frequency bandwidth.

Lin, Ching‐Che↗
DOE OSTI2023

Optimizing Renewable Ammonia Production for a Sustainable Fertilizer Supply Chain Transition

Local renewable ammonia production using electrolytic hydrogen is an emerging approach to alleviate emissions attributed to synthetic nitrogen fertilizer production while also insulating against fluctuations in fertilizer prices and mitigating transportation costs and emissions. However, replacing ammonia currently produced using fossil fuels will not be immediate. To this end, we develop a supply chain transition model, which first optimizes the design and hourly operation of new renewable ammonia facilities to minimize production costs and then optimizes the annual installation timing, production scale, and location of these new renewable facilities along with ammonia transportation to meet county resolution demands. The objective is to augment and eventually replace conventional ammonia market imports in an economically competitive manner. We performed a case study for Minnesota's ammonia supply chain and found that a full transition to in-state renewable production by 2032 is optimal. This is incentivized by the U.S. federal government's clean hydrogen production credits. This transition results in 99 % reduction in carbon intensity along with stable supply costs below $475 per metric tonne. New renewable production facilities are an order of magnitude smaller than existing conventional plants. They use both wind and solar resources and operate dynamically to minimize expensive battery and hydrogen storage capacities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Thermal-Fluid Analysis of a Liquid-Cooled Battery Module for Electrified Aircraft

The development of safe, energy-dense batteries is critical to advancing hybrid electric and fully electrified aircraft propulsion. Achieving this capability requires a thermal management system that can maintain battery performance and safety under demanding operational conditions. The objective of this project is to support the maturation of next-generation lithium-ion batteries for electrified aircraft by conducting performance testing on integrated battery modules, specifically a 2-cell series configuration module housed within an aluminum enclosure. Designed to operate at a nominal 7.2 V with discharge rates up to 2.5C, the module will eventually be used to power an electric motor and DC-DC converter, generating substantial thermal loads that must be effectively managed to increase the usable energy and power density of electrified aircraft. To address these thermal challenges, this study presents the development and thermal-fluid analysis of a liquid-cooled thermal management system. While the full aircraft architecture utilizes an eight-string configuration, the present work evaluates a representative single-string water coolant loop to characterize baseline performance. The active cooling loop circulates water through a reservoir, pump, the battery module, and a variable area flow meter. Key performance metrics including component-level temperatures, mass flow rates, and pressure drops are quantified across the loop. Across discharge rates ranging from 0.5C to 2.5C, the active thermal loop consistently and effectively removed heat from the module, validating the design approach and confirming readiness for further development. The validated thermal performance indicates a path toward scalable battery modules that could enable energy and power dense systems for hybrid electric aircraft.

Electrified Aircraft↗
DOE OSTI2025

Internally Catalyzed Hydrogen Atom Transfer (I-CHAT)—A New Class of Reactions in Combustion Chemistry

The current paradigm of low-T combustion and autoignition of hydrocarbons is based on the sequential two-step oxygenation of fuel radicals. The key chain-branching occurs when the second oxygenation adduct (OOQOOH) is isomerized releasing an OH radical and a key ketohydroperoxide (KHP) intermediate. The subsequent homolytic dissociation of relatively weak O–O bonds in KHP generates two more radicals in the oxidation chain leading to ignition. Based on the recently introduced intramolecular “catalytic hydrogen atom transfer” mechanism (J. Phys. Chem. 2024, 128, 2169), abbreviated here as I-CHAT, we have identified a novel unimolecular decomposition channel for KHPs to form their classical isomers—enol hydroperoxides (EHP). The uncertainty in the contribution of enols is typically due to the high computed barriers for conventional (“direct”) keto–enol tautomerization. Remarkably, the I-CHAT dramatically reduces such barriers. The novel mechanism can be regarded as an intramolecular version of the intermolecular relay transfer of H-atoms mediated by an external molecule following the general classification of such processes (Catal. Rev.-Sci. Eng. 2014, 56, 403). Here, we present a detailed mechanistic and kinetic analysis of the I-CHAT-facilitated pathways applied to n-hexane, n-heptane, and n-pentane models as prototype molecules for gasoline, diesel, and hybrid rocket fuels. We particularly examined the formation kinetics and subsequent dissociation of the γ-enol-hydroperoxide isomer of the most abundant pentane-derived isomer γ-C5-KHP observed experimentally. To gain molecular-level insight into the I-CHAT catalysis, we have also explored the role of the internal catalyst moieties using truncated models. All applied models demonstrated a significant reduction in the isomerization barriers, primarily due to the decreased ring strain in transition states. In addition, the longer-range and sequential H-migration processes were also identified and illustrated via a combined double keto–enol conversion of heptane-2,6-diketo-4-hydroperoxide as a potential chain-branching model. To assess the possible impact of the I-CHAT channels on global fuel combustion characteristics, we performed a detailed kinetic analysis of the isomerization and decomposition of γ-C5-KHP comparing I-CHAT with key alternative reactions—direct dissociation and Korcek channels. Calculated rate parameters were implemented into a modified version of the n-pentane kinetic model developed earlier using RMG automated model generation tools (ACS Omega, 2023, 8, 4908). Simulations of ignition delay times revealed the significant effect of the new pathways, suggesting an important role of the I-CHAT pathways in the low-T combustion of large alkanes.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Radiative divertor detachment and impurity transport with nitrogen and neon seeding in KSTAR H-mode plasmas

Achieving core-edge compatible divertor detachment is a critical requirement for stable operation in future fusion devices. This study compares nitrogen and neon seeding in KSTAR H-mode plasmas with carbon walls, combining experiments and SOLPS-ITER modelling to evaluate their radiative dissipation and core-edge compatibility. Experimentally, N seeding achieved stronger divertor detachment, with larger reductions in target particle and heat fluxes, a higher divertor radiation fraction, and a lower core radiation fraction than Ne. In contrast, Ne seeding triggered a significant rise in core radiation followed by H–L back transitions, limiting the maximum total radiated power fraction to roughly half that of N. SOLPS-ITER simulations reproduced the experimental trends and revealed that the better core-edge compatibility of N arises from its higher divertor retention in addition to its higher cooling factor. The relative positions of the stagnation points of impurity poloidal velocity and ionization sources did not explain the different divertor compression. Instead, in the present modelling, the higher impurity parallel particle flux, resulting from the higher parallel impurity velocity, explains the stronger nitrogen impurity compression in the divertor region. The parallel temperature distribution with N was more favourable for achieving higher impurity parallel velocity than with Ne, because the impurity velocity is governed by modifications of the main ion flow due to friction and thermal forces, both of which strongly depend on the temperature. Ultimately, this behaviour is attributed to the strongly divertor-localized radiation of N. These results demonstrate that N is more effective than Ne in achieving radiative divertor detachment while maintaining low core contamination in KSTAR, consistent with observations in other present tokamaks.

KSTAR↗
DOE OSTI2026

A Data-Driven Method for Modeling Creep-Fatigue Stress- Strain Behavior Using Neural ODEs

In this paper, we introduce a data-driven machine learning approach for modeling one-dimensional stress–strain behavior under cyclic loading, utilizing experimental data from the nickel-based Alloy 617. The study employs uniaxial creep–fatigue test data acquired under various loading histories and compares two distinct neural network-based ODE models. The first model, known as the black-box model, comprehensively describes the strain–stress relationship using a Neural ODE equation. To interpret this black-box model, we apply the Sparse Identification of Nonlinear Dynamical Systems (SINDy) technique, transforming the black-box model into an equation-based model using symbolic regression. The second model, the Neural flow rule model, incorporates Hooke’s Law for the linear elastic component, with the nonlinear part characterized by a Neural ODE. Both models are trained with experimental data to accurately reflect the observed stress–strain behavior. We conduct a detailed comparison with the standard Chaboche model, which includes three back stresses. Our results demonstrate that the neural network-based ODE models precisely capture the experimental creep–fatigue mechanical behavior, exceeding the standard Chaboche model’s accuracy. Furthermore, an interpretable model derived from the black-box neural ODE model through symbolic regression achieves accuracy comparable to the Chaboche model, enhancing its interpretability. The results highlight the potential of neural network-based ODE models to depict complex creep–fatigue behavior, eliminating the necessity for experts to define a specific, material-focused model form.

creep-fatigue↗
NASA NTRS2026

Thermal Considerations for 2039 Opposition Class Nuclear Electric Propulsion/Chemical Propulsion Crewed Mars Mission

The high specific impulse (Isp) of Nuclear Electric Propulsion (NEP) technology offers the potential for advanced space mission capabilities. However, the five critical technology elements of NEP vehicles have yet to prove technical maturity levels for consideration into mission design. In response to the critical reviews by the NASA Engineering and Safety Center (NESC) and the National Academies of Sciences, Engineering, and Medicine (NASEM), NASA’s Space Nuclear Propulsion (SNP) project created an NEP Technology Maturation Plan (TMP) for focused development of NEP technology. The TMP called for a coordinated set of technology development efforts to meet this objective. The Modular Assembled Radiators for NEP VehicLes (MARVL) Early Career Initiative (ECI) project was initiated to develop a portion of the fifth Critical Technology Element (CTE) of the NEP vehicle: the Primary Heat Rejection Subsystem (PHRS). A target application of a 2039 human-rated Mars mission was outlined in the TMP. For the outlined mission, a NEP vehicle will experience several thermal environments which will impact the design and operation of the PHRS. To maintain radiator temperatures within the required effective temperature range, the effect of natural, induced, and NEP internally generated heat loads on the radiator panel must be well understood. Furthermore, this analysis is critical for analyzing the influence of various orientations and positions of the NEP vehicle relative to nearby celestial bodies throughout the mission. This study conducted a complete enveloping analysis of the thermal environments influencing the NEP vehicle throughout the mission. Thermal analysis was conducted for the radiator panels based on the defined mission environments. This thermal analysis concludes with the selection of ideal radiator orientations for the NEP vehicle, and the identification of worst case hot and cold environmental sink temperatures throughout the mission. For the target application, the environmental sink temperature while the reactor is powered OFF or powered ON ranges from 30 K to 353 K and 2.7 K to 243 K respectively. When considering interplanetary space, the minimum environmental sink temperature when the reactor is powered OFF and the radiators are oriented “edge to Sun” is 2.7 K. The environmental thermal models generated in this study will be used for future studies with the full vehicle system model. The environmental sink temperature curves generated will be used for future radiator and component analysis to predict transient performance in the space environment. The environmental sink temperature and heat rejection capability curves will inform the trade between commissioning orbits that are in consideration. The model may also serve as a useful tool as reference for future crewed space missions, missions involving radiators or temperature sensitive equipment, or other missions requiring analysis of natural orbital thermal environments.

Nuclear Electric Propulsion↗
NASA NTRSDate not supplied

First-Principles Investigation of Phase Transitions in RuNb, RuTa, and Ru-Nb-Ta Ultrahigh Temperature Shape Memory Alloys

Ultrahigh temperature shape memory alloys (UHT-SMAs) have transition temperatures above 600 C, and they have found applications for sensing and actuating devices in aerospace industry. Among very few such UHT-SMAs currently known are Ru-based alloys such as RuNb and RuTa, whose martensite structures and phase transitions are totally different from those of NiTi-based SMAs and were poorly understood. In this work, we carried out a systematical study of RuNb using first-principles total energy calculations and molecular dynamics (MD) simulations. The transition paths and mechanisms in cubic → tetragonal →monoclinic transitions are revealed. and the transition sequence and martensitic transition temperatures are determined (MTTs) by evaluating the Gibbs free energies using thermodynamic integration. The calculated MTTs are in very good agreement with the experimental data. We found that the monoclinic phase at the second transition has the 𝑃21/m symmetry instead of experimentally identified 𝑃2/m. Our calculations demonstrate that RuTa has very similar phase transitions to those of RuTa. Furthermore, we studied the Ru0.5Nb0.25Ta0.25 ternary. Our results can explain the measured significant drop of MTT (~ 200 C) in the second transition for Ru0.5Nb0.25Ta0.25 compared with those of RuNb and RuTa, while in the first transition its MTT is between MTTs of RuNb and RuTa. The insights gained by this study and the verified ab initio methods for accurate MTT calculations can be applied to fast screen and quantitatively design novel UHT-SMAs having similar properties with desirable MTTs and much reduced cost.

Zhigang Wu↗
DOE OSTI2025

From PINNs to PIKANs: recent advances in physics-informed machine learning

Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offering a promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Lastly, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.

Kolmogorov-Arnold networks↗
DOE OSTI2025

Boron Nitride-Driven Strengthening of Aluminum Composites via Friction Stir Processing

Friction stir welding and processing (FSW/P) has emerged as an effective solid-state joining technique for fabricating metal matrix composites (MMCs), offering improved mechanical properties through refined microstructural evolution. In this study, an aluminum-boron nitride nanoparticle (Al-BNNP) composite was synthesized via FSW, and its indentation-based mechanical properties were systematically evaluated. Microhardness mapping across the weld cross-section revealed a progressive increase in hardness toward the stir zone (SZ), attributed to severe plastic deformation, dynamic recrystallization (DRX), and the reinforcing effect of BNNPs. Profilometry-based indentation plastometry (PIP) inferred yield strength (YS) demonstrates a 47.8% increase compared to the base metal (BM) and a 75% improvement compared to FSP pure aluminum reported in literature. This enhancement is attributed to strengthening mechanisms, including grain boundary pinning, load transfer, and increased dislocation density. The strain rate sensitivity (SRS) measurements at the nanoscale demonstrated a substantial decrease in the SZ, correlated with ultrafine grain structures and strong BNNP-matrix interactions. Activation volume analysis revealed a significant reduction in the SZ, suggesting that dislocation motion is increasingly restricted by dislocation-dislocation and dislocation-particle interactions. These findings suggest that incorporating BNNPs in FSW/P enables tailoring the microstructure without thermal degradation of the secondary particles, thereby significantly enhancing the mechanical performance of aluminum composites, particularly for structural applications in aerospace and automotive industries.

Aluminum↗
DOE OSTI2024

An Accreting Supermassive Black Hole Buried in a Faint Dwarf Galaxy

Abstract In the last decade, there have been several discoveries of active galactic nuclei (AGN) in dwarf galaxies including an AGN in an ultracompact dwarf galaxy with a black hole mass >10 6 M ⊙ . However, finding a supermassive black hole (SMBH) in a dwarf low surface brightness (LSB) galaxy is rare. We report the discovery of a Seyfert type 2 class AGN that is associated with a nuclear SMBH of mass ∼6.5 × 10 6 M ⊙ in a dwarf LSB galaxy (μ 0,r > 23.8 mag arcsec −2 ) that we denote by MJ0818+2257. The galaxy was previously thought to be an outlying emission blob around the large spiral galaxy LEDA 1678924. In our current analysis, which includes the detection of the optical counterpart of MJ0818+2257, we study its ionized gas kinematics and find that the dynamical mass within the ionized gas disk is ∼5.3 × 10 9 M ⊙ . This is comparable to its stellar mass, which is ∼3 × 10 9 M ⊙ , and suggests that MJ0818+2257 is moderately dark matter dominated within the stellar disk. The SMBH-mass-to-galaxy-stellar-mass ratio isM BH /M(*) > 0.022, which is high compared to disk galaxies. Our detection of an SMBH in a bulgeless LSB dwarf galaxy raises questions about the growth of SMBHs in low-luminosity galaxies and suggests the possibility of detecting heavy seed black holes from early epochs in LSB dwarf galaxies in the low-redshift Universe.

Astronomy & Astrophysics↗