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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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1,713 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Carbon in GaN as a nonradiative recombination center

Trap-assisted nonradiative recombination has been shown to limit the efficiency of optoelectronic devices. While substitutional carbon (⁠C N ) has been suggested to be a nonradiative recombination center in GaN devices, a complete recombination cycle including the two charge-state transition levels has not been previously described. In this work, we investigate the trap-assisted recombination process due to C N in GaN, including multiphonon emission, radiative recombination, trap-assisted Auger–Meitner (TAAM) recombination as well as thermal emission of holes. Our study shows the key role of TAAM processes at the high carrier densities relevant for devices. We also reveal the carrier-density regimes where thermal emission and radiative recombination are expected to play an observable role. Our results highlight that carbon concentrations exceeding ~10 17 cm −3 can have a noticeable impact on device efficiency, not just in GaN active layers but also in InGaN and AlGaN. Furthermore, our comprehensive formalism not only offers detailed results for carbon but also provides a general framework for assessing the multiple processes that participate in trap-assisted recombination in semiconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Design Trade-Offs in Composite Fuel Cell Membranes: Effects of Reinforcement and Chemical Additives

Perfluorosulfonic acid (PFSA) membranes are critical components in proton exchange membrane fuel cells, where performance depends on balancing ionic conductivity, mechanical durability, and chemical stability. This study characterizes a composite membrane (NC700) featuring PFSA-impregnated expanded polytetrafluoroethylene (ePTFE) reinforcement and cerium-based radical scavengers, benchmarked against unreinforced NR211. Complementary techniques, including electron microscopy, X-ray scattering, infrared spectroscopy, thermogravimetric analysis, and dynamic mechanical analysis, identify the structural and compositional strategies employed in NC700. Water sorption isotherms reveal lower water uptake for NC700 across all conditions, attributed to reinforcement and cerium incorporation. Reinforcement reduces in-plane swelling from 11% to 2.1% at 90% RH, confirming strong swelling anisotropy, while maintaining mechanical properties at elevated temperatures. While the ionic conductivity of NC700 is approximately 10% lower than that of NR211, the reduced thickness yields a 40% decrease in calculated area-specific resistance, suggesting the composite architecture can favorably shift the conductivity-stability trade-off. The composite structure also reduces gas permeability, indicating potential for improved separator function alongside favorable transport properties. Systematic deconvolution of reinforcement and additive contributions shows that conductivity losses from cerium incorporation are largely offset by gains from the lower equivalent-weight polymer, providing quantitative relationships that may guide composite membrane design for fuel cells and other electrochemical applications.

25 ENERGY STORAGE↗
DOE OSTI2024

Collective excitations and low-energy ionization signatures of relativistic particles in silicon detectors

Abstract Solid-state detectors with a low energy threshold have several applications, including searches of non-relativistic halo dark-matter particles with sub-GeV masses. When searching for relativistic, beyond-the-Standard-Model particles with enhanced cross sections for small energy transfers, a small detector with a low energy threshold may have better sensitivity than a larger detector with a higher energy threshold. In this paper, we calculate the low-energy ionization spectrum from high-velocity particles scattering in a dielectric material. We consider the full material response including the excitation of bulk plasmons. We generalize the energy-loss function to relativistic kinematics, and benchmark existing tools used for halo dark-matter scattering against electron energy-loss spectroscopy data. Compared to calculations commonly used in the literature, such as the Photo-Absorption-Ionization model or the free-electron model, including collective effects shifts the recoil ionization spectrum towards higher energies, typically peaking around 4–6 electron-hole pairs. We apply our results to the three benchmark examples: millicharged particles produced in a beam, neutrinos with a magnetic dipole moment produced in a reactor, and upscattered dark-matter particles. Our results show that the proper inclusion of collective effects typically enhances a detector’s sensitivity to these particles, since detector backgrounds, such as dark counts, peak at lower energies.

Physics↗
DOE OSTI2026

Ferroelectric Fractals: Switching Mechanism of Wurtzite AlN

The advent of wurtzite ferroelectrics is enabling new ferroelectric devices for computer memory that have the potential to bypass the von Neumann bottleneck due to their robust polarization and silicon compatibility. However, the atomistic switching mechanism of wurtzites is still undetermined due to the limitations of density functional theory simulation size and experimental temporal and spatial resolution. Thus, physics-informed materials engineering to reduce coercive field and breakdown in these devices has been limited. In this work, the atomistic mechanism of domain wall migration and domain growth in aluminum nitride-based wurtzites is uncovered using molecular dynamics and Monte Carlo simulations. We reveal the anomalous switching mechanism of fast 1D single columns of atoms propagating from a slow-moving 2D fractallike domain wall. We find that the critical nucleus is a single aluminum ion that breaks its bond with one nitrogen and bonds to another nitrogen; this creates a cascade that flips atoms directly only in the same column, due to the extreme locality (sharpness) of the domain walls in wurtzites. We further show how the fractallike shape of the domain wall in the 2D plane breaks assumptions in the Kolmogorov, Avrami, and Ishibashi (KAI) model and leads to the anomalously fast switching in wurtzite structured ferroelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

POWER ELECTRONICS GRID TIED SYSTEM FINAL REPORT

Across the country, electric utilities are grappling with the persistent hurdles of integrating Distributed Energy Resources (DERs). Managing these assets safely and effectively is a complex endeavor, complicated by varying ownership structures, management philosophies, and the diversity of the technologies themselves. Consequently, the industry has seen a proliferation of bespoke system designs, control strategies, and communication frameworks—forcing utilities to spend significant time and resources developing one-off integration solutions. This project addressed these integration hurdles through a scalable demonstration of intelligent devices designed to coordinate and control diverse resources in low-voltage applications. This concept minimized the need for complex integration by transforming the separate DERs into a dispatchable virtual power plant (VPP) with integrated resiliency functions (called a Node). By collaborating with a utility partner, the project focused on developing rapidly implementable use cases that bridged the gap between theoretical control and real-world deployment

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Nuclear–Electronic Orbital General Rate Theory: Predicting Hydrogen Kinetic Isotope Effects in the Deep Tunneling Regime

Hydrogen transfer is a critical component of many chemical and biological processes. The ratio of rate constants for hydrogen and deuterium transfer defines the H/D kinetic isotope effect (KIE), which is a powerful tool for elucidating hydrogen transfer mechanisms. Interpretation of experimental H/D KIEs relies on accurate and affordable computational methods. However, due to their light mass, hydrogen and deuterium can undergo tunneling, which is challenging to describe in multidimensional molecular systems. Herein, we introduce the nuclear–electronic orbital general rate theory (NEO-GRT), which enables the efficient prediction of H/D KIEs based on full-dimensional molecular quantum chemistry calculations. The NEO-GRT approach describes the hydrogen transfer rate constant with a general expression that spans the vibrationally adiabatic and nonadiabatic hydrogen tunneling regimes. The input quantities are computed using NEO density functional theory, which treats the transferring hydrogen or deuterium nucleus quantum mechanically on the same level as the electrons. We investigate two intramolecular proton transfer reactions in organic molecules at temperatures down to 50 K to evaluate the performance of NEO-GRT by comparison to transition state theory and ring-polymer instanton theory. The KIEs computed with NEO-GRT agree with those calculated using ring-polymer instanton theory for the full-dimensional molecular systems at the same level of electronic structure theory. This agreement indicates that NEO-GRT captures the deep hydrogen tunneling effects, in contrast to transition state theory, which neglects such effects. Given its relatively low computational cost, NEO-GRT is a promising approach for predicting H/D KIEs in large organic and organometallic systems.

Hydrogen↗
DOE OSTI2026

Quantifying the dislocation content of atomically resolved grain boundary line defects using the Nye tensor

The Nye tensor, which quantifies the density of Burgers vector for a given dislocation line direction, can be effectively used to characterize dislocation content in bulk crystals from atomic-resolution transmission electron microscopy images. The Nye tensor can be calculated from these images, in part because the reference state is simply defined by the lattice of the perfect crystal. The application of the Nye tensor to interfacial line defects, for which the natural reference state is the dichromatic pattern of the two grains in their reference orientation, poses additional challenges. In this work, we present a method that employs the Nye tensor to characterize the edge dislocation content of line defects at grain boundaries from atomic-resolution images. This approach enables us to rapidly characterize all edge dislocation content along a grain boundary. Additionally, the Nye tensor provides information about line defect core structure. Finally, we demonstrate this method on two exemplar defects: a twin boundary disconnection and a facet junction in face-centered cubic Au.

Crystallographic defects↗
DOE OSTI2024

A novel digital lifecycle for Material‐Process‐Microstructure‐Performance relationships of thermoplastic olefins foams manufactured via supercritical fluid assisted foam injection molding

Abstract This research significantly enhances the applicability of thermoplastic olefins (TPOs) in the automotive industry using supercritical N 2 as a physical foaming agent, effectively addressing the limitations of traditional chemical agents. It merges experimental results with simulations to establish detailed material‐process‐microstructure‐performance (MP2) relationships, targeting 5–20% weight reductions. This innovative approach labeled digital lifecycle (DLC) helps accurately predict tensile, flexural, and impact properties based on the foam microstructure, along with experimentally demonstrating improved paintability. The study combines process simulations with finite element models to develop a comprehensive digital model for accurately predicting mechanical properties. Our findings demonstrate a strong correlation between simulated and experimental data, with about a 5% error across various weight reduction targets, marking significant improvements over existing analytical models. This research highlights the efficacy of physical foaming agents in TPO enhancement and emphasizes the importance of integrating experimental and simulation methods to capture the underlying foaming mechanism to establish material‐process‐microstructure‐performance (MP2) relationships. Highlights Establishes a material‐process‐microstructure‐performance (MP2) for TPO foams Sustainably produces TPO foams using supercritical (ScF) N 2 with 20% lightweighting Shows enhanced paintability for TPO foam improved surface aesthetics Digital lifecycle (DLC) that predicts both foam microstructure and properties DLC maps process effects & microstructure onto FEA mesh for precise prediction

Engineering↗
DOE OSTI2026

Concerted Electron-Ion Transport by Polyacrylonitrile Elucidated with Reactive Deep Learning Potentials

Charge transport in polymers, such as polyacrylonitrile (PAN), is crucial for electronics and energy storage. For instance, PAN can transport cations e.g., Li + , by facilitating dynamic cation-nitrile coordination in batteries. However, little is known regarding the underlying role of complex reactive polymer configurations. Herein, we develop a deep-learning potential, trained on ab initio energies and forces of nonequilibrium reactive PAN configurations, to unravel the kinetics of PAN cyclization initiated by a nucleophile (OH – dissociated from LiOH) attacking the terminal nitrile carbon. We find, based on the reaction free-energetics, rates, and charge analysis, that the nucleophile attack producing the first ring is the rate-limiting step, which subsequently triggers Li + -coupled electron transfer along the PAN backbone, causing ∼10 4 times faster sequential ring-formation of the remaining nitriles. PAN’s extended configurations, where dipolar and H-bonding interactions are minimal, enable such rapid kinetics. By validating our computational findings with IR and NMR experiments, we establish a pathway for designing reactive polymers with enhanced charge transport for energy applications.

Chahal-Crockett, Rajni [Oak Ridge National Laborat↗
DOE OSTI2025

Detecting thermodynamic phase transition via explainable machine learning of photoemission spectroscopy

Identifying thermodynamic signatures of electronic phases, such as superconductivity, is challenging in low-dimensional materials due to strong fluctuations and low probing volume. Spectroscopic methods are often used to identify new bulk phases, but their main measurable quantity—electronic energy gaps—is no longer an effective order parameter in low-dimensional and fluctuating systems. Combining angle-resolved photoemission with a domain-adversarial neural network, we report a data-driven method to identify thermodynamic phase transitions solely based on single-particle spectra. We demonstrate 97.6% accuracy in cuprate superconductor Bi 2 Sr 2 CaCu 2 O 8+δ with strong superconducting fluctuations. This model notably compensates for the scarcity of experimental data by leveraging virtually inexhaustible simulated data. Further, its explainability reveals the crucial role of in-gap spectral weight in detecting phase fluctuations and thermodynamic transitions. Our work pinpoints the spectroscopic signatures of fluctuating orders and enables using spectroscopy for machine-learning-assisted material discovery for low-dimensional and strong coupling systems.

2D materials↗
DOE OSTI2024

Selective solid-state isolation of NMR circuit elements using back-to-back field effect transistors

Nuclear Magnetic Resonance (NMR) electronics that employ selective solid-state isolation of circuit elements can include solid-state switches, such as back-to-back Field Effect Transistor (FET) pairs, and isolated gate drive electronics adapted to operate the solid-state switches in order to selectively decouple induction coils from receive electronics. The solid-state switches can be placed in series to achieve higher standoff voltages, and can be configured for low on resistance and short switching times. The gate drive electronics can include electrical isolation components adapted to enhance standoff voltages and reduce electrical noise at the selectively isolated receive electronics.

Walsh, David O.↗
DOE OSTI2023

Photoelectrochemical materials for solar energy conversion

Research and development on semiconductors for applications in solar energy conversion has witnessed rapid growth over the past several decades. With the aim of producing chemical fuels from sunlight, intense research efforts have focused on the discovery of semiconductors with crystalline structures and chemical compositions that have the potential to satisfy the complex set of required photoelectrochemical properties. This chapter focuses on the foundational structure-property relationships of selected oxide and nitride semiconductors relevant to their uses as n-/p-type photoelectrodes and as photocatalysts. Their solid-state structures and compositions are described, with a special emphasis on strategies proven effective at targeting suitable band gaps with strong visible-light absorption, efficient charge separation and diffusion of charge carriers, and optimal band edge energies for driving surface redox reactions for water splitting.

O’Donnell, Shaun↗
DOE OSTI2024

3D Printing ofThermally Responsive Shape Memory LiquidCrystalline Epoxy Networks

Abstract A two-component liquid crystalline epoxy network (LCEN) with shape memory behavior was developed and evaluated as a candidate material for 3D printing. The cure kinetics of the uncured material and the shape memory properties of the cured LCEN were investigated by using parallel plate rheology and dynamic mechanical analysis, respectively. A commercially available fumed silica additive was introduced to the neat, uncured material to improve the rheological properties for 3D printing. The addition of fumed silica was found to increase the yield stress, shear-thinning behavior, and toughness of the uncured epoxy ink. Polarized light microscopy, differential scanning calorimetry, and wide-angle X-ray scattering measurements between the neat and additive-modified LCEN suggested a reduction in liquid crystalline alignment in the modified LCEN, owing to interactions between crystalline domains and fumed silica, which in turn influenced the mechanical behavior. Overall, the additive was found to be successful in preserving the shape memory properties of LCEN while improving its printability.

Chemistry↗
DOE OSTI2026

Comparative neutron-irradiation effects on thermal conductivity degradation and dimensional stability of TiC, TiB 2 , and ZrB 2 at 200–1000 °C

Ultra-high-temperature ceramics (UHTCs), including TiC, Ti 11 B₂, and Zr 11 B₂, show great potential for plasma-facing components due to their excellent high-temperature properties prior to irradiation. However, their response to neutron irradiation remains insufficiently understood, limiting robust assessment of their viability for fusion energy applications. Here, this study examines the thermal conductivity, dimensional stability and microstructure of TiC, TiB₂, and ZrB₂ following neutron irradiation at temperatures of 200–1000 °C and fast neutron fluences of 2.0 × 10 25 to 1.1 × 10 26 n/m 2 (E > 0.1 MeV). Lattice swelling measured by synchrotron X-ray diffraction in all three UHTCs was maximized at 200 °C and decreased with increasing irradiation temperature, with no evidence of amorphization observed at 200 °C. Above 600 °C, significant macroscopic volume swelling was observed in irradiated Ti 11 B₂ and Zr 11 B₂, but not in TiC, likely due to cavity formation in the diborides. The post-irradiation thermal conductivity, measured at the irradiation temperature, ranged from 28 to 45 W/m·K, representing a 34–45% reduction relative to the unirradiated material. Notably, neutron-irradiated UHTCs exhibit recoverable thermal conductivity at elevated temperatures, comparable to ferritic–martensitic steels and potentially superior to W when transmutation effects are considered, highlighting promise for shielding or armor plasma-facing components. At 600 °C, both thermal conductivity degradation and lattice swelling saturated at doses exceeding 2–4 dpa.

fusion materials↗
DOE OSTI2026

Associative polymers with controlled sticker placement: How reversible bond distribution and density govern polymer dynamics

Associative polymers with precisely arranged stickers offer opportunities to program material properties with molecular precision. Yet, it remains unclear how the placement and fraction of stickers dictate structure, dynamics, and macroscopic properties. By developing a model unentangled polymer system with hydrogen-bonding stickers, we show that randomly distributed stickers neither form clusters nor change flow properties, whereas stickers placed at chain ends drive nanocluster formation even at low concentrations. Adding more end stickers produces a rubbery plateau spanning eight decades in frequency with two distinct relaxation timescales, in contrast to the single plateau predicted by the classic sticky Rouse model. These results demonstrate that sticker distribution dictates whether associative polymers undergo nanocluster formation or microphase separation, while substantial alterations in dynamics and viscoelasticity require both sticker aggregation and thermomechanical stability of associated domains. Our findings resolve a longstanding debate on associative polymer dynamics and provide molecular design rules for programmable soft materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Advancing technologies for lignin-based jet fuel production in aqueous phase

Integrating lignin into a cellulosic ethanol plant for the co-production of lignin-based jet fuel (LJF) in aqueous phase offers a significant opportunity to boost operational efficiency, economic viability, carbon conversion, and the overall sustainability of biofuel and chemical production. LJF is lignin-structure-based jet fuel blendstocks primarily composed of alkyl-substituted mono-, bi-, and tri-cyclohexanes. It exhibits high energy density, potential for low emissions, and favourable blend characteristics that comply with drop-in specifications. An overview of lignin feedstock, catalytic processes, LJF chemical compositions, fuel properties tests, and techno-economic analysis (TEA) and life cycle assessment (LCA) indicate that (1) the reactivity of lignin plays a crucial role in its structure transformation to LJF molecules; (2) catalytic processing of lignin to LJF can occur through a simultaneous depolymerization and hydrodeoxygenation process, bypassing the intermediate step of producing and upgrading lignin-derived oil; (3) LJF's uniqueness molecules making it more promising for high energy content and low emission jet fuel properties for next generation sustainable aviation fuel (SAF); and (4) TEA and LCA demonstrate that LJF is not only potentially cost-effective but also offers favourable carbon footprint compared to other SAFs. In conclusion, this review highlights the most recent advancements in LJF technology, along with the challenges and opportunities that lie ahead in fulfilling its potential.

09 BIOMASS FUELS↗
DOE OSTI2026

Battery Material Synthesis and Scalability using a 50L Taylor Vortex Reactor (Final CRADA Report)

Under this agreement, Laminar will loan Argonne a 50L Taylor Vortex Reactor (TVR) and provide mechanical troubleshooting guidance and consulting to ensure the successful setup of the pilot-scale synthesis process. The U.S. Department of Energy (DOE) will allocate funding for the labor and materials required for the study. To evaluate the physical and electrochemical properties of the materials produced by the 50L TVR, Argonne will perform comprehensive characterizations, including XRD, SEM, PSA, ICP, tap density, and coin half-cell testing. Throughout the collaboration, Argonne will provide feedback and recommendations for mechanical improvements to the reactor system. Furthermore, Argonne will credit Laminar as a collaborator in any presentations or publications resulting from data generated by the system. Laminar will retain no rights to experimental results or intellectual property generated through the experiments conducted with the 50L TVR at Argonne.

25 ENERGY STORAGE↗
DOE OSTI2026

Directing Assembly of Mesoscale Multi‐Shell Morphologies of DNA Origami Crystals

Nature builds hierarchically ordered materials, such as seashells, wood, and bones, through spatially and temporally regulated growth. Mimicking such a level of control in synthetic systems remains challenging, particularly in achieving multiscale organizations with prescribed nanoscale arrangements and desired material morphologies. In this study, we introduce a DNA-based self-assembly strategy for constructing diverse multi-shell mesoscale morphologies from nanoscale lattices, enabling prescribed structural, and compositional 3D material patterns. Using DNA origami frames as modular monomers, we direct anisotropic epitaxial growth through addressable DNA frame binding motifs and encapsulate nanoparticles (NPs) in desired 3D patterns. Sequential monomer addition under thermodynamically favorable conditions enables shell growth through heterogeneous nucleation while minimizing unwanted homogeneous nucleation. Here, we demonstrate that DNA-encoded addressability enables epitaxial shell growth along specific lattice directions, yielding crystals with multilayered mesoscale organization, including tube-like (sushi roll) and plate-like (macaron) morphologies. Shell-specific NP configurations and compositions are achieved through addressable and differentiated placement of NPs within each shell, as validated by small-angle x-ray scattering and cross-sectional scanning transmission electron microscopy. We further demonstrate addressable NP release and reveal that shells modulate release kinetics. Together, these findings establish a platform for fabricating DNA origami crystals with programmable mesoscale morphologies, nanoscale structure, composition, and transport properties.

3D patterning↗