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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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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Unveiling the lithium-ion transport mechanism in Li{sub 2}ZrCl{sub 6} Solid-State Electrolyte {ital via} deep learning-accelerated molecular dynamics simulations.

Lithium zirconium chlorides (LZCs) present a promising class of cost-effective solid electrolytes for next-generation all-solid-state batteries. The unique crystal structure of LZCs plays a crucial role in facilitating lithium-ion mobility, which further affects the electrochemical performance. To understand the underlying mechanism governing ion transport, we employed deep learning-accelerated molecular dynamics simulation on Li2ZrCl6 (trigonal alpha- and monoclinic beta-LZC), focusing specifically on the zirconium coordination environment. Our results reveal that disordered alpha-LZC exhibits the highest ionic conductivity, while beta-LZC demonstrates significantly lower conductivity, closely aligning with experimental findings. The study confirms that across all phases, lithium migration proceeds via the site-to-site hopping mechanism, where variations in site residence times critically impact the overall ionic conductivity. In alpha-LZCs, lithium ions prefer to anisotropically diffuse across interlayers as the result of a lower energy barrier, driven primarily by collective diffusion. In contrast, lithium ions in beta-LZC primarily isotropically diffuse within the intralayer, hindered by higher energy barriers and determined by individual diffusion. The variation in ZrCl6 2- octahedral unit softening, induced by the specific layered arrangement of zirconium atoms, emerges as a critical determinant of the energy barriers across the LZC phases. These atomic-scale insights into the transport processes provide valuable guidance for the rational design and optimization of LZCs-based electrolytes, accelerating their practical application in advanced energy storage technologies.

Guo, Hanzeng↗
DOE OSTI2026

Mechanistic Insights for Plasma-Catalytic CO 2 Reduction over TiO 2 in a Dielectric Barrier Discharge Reactor

Reaction kinetics experiments coupled with phenomenological kinetic modeling and parameter estimation are used to elicit insights into the mechanism and active sites for the plasma-catalytic dissociation of CO 2 on TiO 2 . Experimental and model insights showed that gas-phase reactions contribute at least two-thirds of the overall product formation at explored conditions; weak temperature dependence, strong sensitivity to specific energy input (SEI), apparent first order in CO 2 , and positive influence of cofed argon (Ar) and oxygen (O 2 ) for the gas-phase contributions all suggest that expected plasma reaction steps such as electron-impact and high-energy collisions are the dominant modes for CO 2 dissociation. The Arrhenius-like expression for gas contributions resulted in a preexponential of 4.40 × 10 –3 s –1 , an E SEI,g of 7.90 × 10 –4 mol/kJ, and an E a,g of 1.00 × 10 –3 J/mol. For surface contributions, the small apparent barrier of 16.3 kJ/mol, relatively weaker dependence on SEI, first-order dependence on CO 2 , and insensitivity to cofed Ar and O 2 all point to CO 2 dissociation on TiO 2 surface facets without vacancies and aided by plasma (leading to vibrationally excited CO 2 and/or a reactive surface with significant surface charge accumulation). The Arrhenius-like expression resulted in a preexponential of 7.81 × 10 –2 s –1 , an E SEI,s of 1.90 × 10 –3 mol/kJ, and an E a,s of 1.63 × 10 4 J/mol. The derived kinetic model further enabled a systematic evaluation of the effect of inputs (plasma power, flow rate, CO 2 inlet concentration, and temperature) to identify process trends and optimal operating conditions.

catalyst↗
DOE OSTI2026

Iron isotope fractionation between solid and liquid metal in the Fe-P±Ni system: Experimental constraints and implications for meteorites

Iron meteorites record a range of Fe isotope compositions that hold valuable information regarding the evolution of their parent bodies. Interpreting this isotopic variability, however, requires experimental constraints on the equilibrium isotope fractionation between phases. It is thought that the cores of many iron meteorite parent bodies experienced fractional crystallization, during which crystallization of solid iron-nickel occurs from an increasingly non-metal-rich liquid alloy. Phosphorus is one component of this alloy, and this study provides the first constraints on Fe-isotope fractionation between solid and liquid alloys in the Fe-Ni-P system. Experiments comprising Fe and P show a clear enrichment in the light isotopes of Fe in the liquid phase, which increases with the amount of phosphorus. Nickel-bearing samples are offset from the trend defined by Ni-free experiments, which is accounted for by the change in the solid alloy phase from a body-centered cubic to face-centered cubic structure upon the addition of Ni. The increasing light isotope enrichment of the liquid with increasing P content suggests interstitial solution of P, which is known to lengthen Fe-Fe bonds in Fe-P liquids (Waseda and Shiraishi 1977). Results suggest a negligible effect of P on Fe isotope fractionation during planetesimal core crystallization. Iron isotopes may, however, prove useful for identifying the petrogenesis of schreibersite in pallasites and iron meteorites.

58 GEOSCIENCES↗
DOE OSTI2025

Probabilistic Predictions for Fastener Failure in the Sandia Mechanics Challenge Using the Discrete-Direct Uncertainty Quantification Approach

This paper documents the blind and post-blind analysis predictions for the 2023 Sandia Mechanics Challenge (SMC), which involved predicting the behavior of a threaded fastener joint structure subjected to shock loading. Utilizing repeat sets of fastener calibration data from various experimental configurations including tension, double shear, and joint tension, we developed a library of calibrated models which were propagated through the application model using the Discrete-Direct (DD) uncertainty quantification (UQ) approach. Although the initial blind predictions did not incorporate spare-sample processing to quantify fastener failure probabilities, the analyses yielded reasonable conclusions aligned with experimental results. In the post-blind analysis phase, we focused on enhancing the fidelity of the aluminum constitutive model and innovating the DD approach to obtain probabilistic predictions for fastener failure, particularly when quantities of interest (QoIs) approach their bounds. The improved aluminum model captures the behavior of the cantilever under shock loading more accurately, predicting both partial and complete cracks, although it tends to underpredict failure propagation. The enhanced DD approach facilitates probabilistic predictions that reflect the interdependent failure mechanisms of the fasteners and the cantilever, revealing that while certain fasteners are more likely to fail, the failure does not necessarily follow a progressive pattern. Overall, the post-blind analyses significantly improved the predictive capabilities of the model, providing valuable insights into the SMC application and establishing a robust foundation for informed engineering decisions. The methodology demonstrates a cost-effective and extensible approach suitable for a wide range of applications, highlighting the importance of uncertainty quantification to provide context for engineering decision making.

42 ENGINEERING↗
DOE OSTI2026

Time at Temperature Experiments on Neutron Irradiated Zircaloy-2 using Conventional & Flash DSC

Dryout events in Boiling Water Reactors (BWRs) are currently treated by NRC regulations as automatic disqualification for continued fuel rod operation, even though this criterion does not account for the rate or duration of power increases, associated changes in material behavior, or the possibility of rewetting. Operational history from Anticipated Operational Occurrences (AOOs) shows that short, transient power excursions often demand only modest heat removal, and industry experience suggests that fuel can briefly enter dryout yet return to safe, stable operation. The lack of detailed understanding of the material response during such events motivates the present series of experiments. This study uses unique and innovative methods to investigate microstructural evolution in irradiated Zircaloy-2 exposed to high temperatures in inert environments. Differential Scanning Calorimetry (DSC) and FlashDSC are combined to build a comprehensive experimental framework capable of identifying the a–ß phase transformation in zirconium and examining defect annealing under steep thermal gradients. FlashDSC enables rapid heating and cooling of Focused Ion Beam (FIB)–prepared large-area lift-outs (LALOs) of irradiated Zircaloy-2 at rates of 1,000 K/s to peak temperatures of 600°C, 750°C, and 900°C. The goal is to determine whether these conditions produce measurable microstructural changes that could influence cladding performance in typical BWR environments. Microstructural characterization includes quantifying dislocation density and assessing secondary phase particle (SPP) size and distribution using Transmission Electron Microscopy (TEM). Ongoing analysis, such as diffraction pattern indexing and 4D STEM processing, will further refine these observations.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Exploring 2D X-ray diffraction phase fraction analysis with convolutional neural networks: Insights from kinematic-diffraction simulations

Abstract Deep-learning models are effective for analyzing the complex information in 2D X-ray diffraction (XRD) patterns. Accurately collecting parameters of the material sample is crucial during model training, significantly impacting model performance. In this study, we employ a kinematic-diffraction simulator to generate simulated 2D XRD patterns for Ti–6Al–4V alloy, allowing precise control of sample parameters. These simulated patterns are used to train convolutional neural networks, predicting $$\upbeta$$ β -phase volume fractions. The training data set consists exclusively of 2D XRD patterns with pure $$\upalpha$$ α - or pure $$\upbeta$$ β -phase, while the testing set incorporates patterns with intermediate phase volume fraction. In particular, we investigate how the architectures of the model influence prediction reliability and computational performance. Experimental results reveal that, with appropriate training, the convolutional neural network accurately detects intermediate phase volume fractions even trained with only pure-phase patterns, achieving a mean square error accuracy of $$9.4 \times 10^{-4}$$ 9.4 × 10 - 4 . Graphical abstract

Yue, Weiqi↗
DOE OSTI2025

An electronic microemulsion phase emerging from a quantum crystal-to-liquid transition

Strongly interacting electronic systems often exhibit a complicated phase diagram that results from the competition between different quantum ground states. One feature of these phase diagrams is the emergence of microemulsion phases, where regions of different phases self-organize across multiple length scales. The experimental characterization of these microemulsions can pose considerable challenges, as the long-range Coulomb interaction microscopically mingles with the competing states. Here we observe the signatures of the microemulsion between an electronic Wigner crystal and an electron liquid in a MoSe 2 monolayer using cryogenic reflectance and magneto-optical spectroscopy. We find that the transition into this microemulsion state is marked by anomalies in exciton reflectance, spin susceptibility and umklapp scattering, establishing it as a distinct phase of electronic matter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Autonomous phase mapping of gold nanoparticles synthesis with differentiable models of spectral shape

Autonomous experimentation–or self-driving labs–offers a systematic approach to accelerate materials discovery by integrating automated synthesis, characterization, and data-driven decision-making. We present a closed-loop workflow for the on-demand synthesis and structural characterization of colloidal gold nanoparticles, enabling direct mapping from composition to nanoscale structure. Our framework leverages differentiable models of spectral shape to address two central tasks in self-driving labs: (a) phase mapping, or identifying compositional regions with distinct structural behavior; and (b) material retrosynthesis, or optimizing compositions for target structure. Using functional data analysis, we develop a data-driven model with generative pre-training, active learning, and high-throughput experiments to predict spectral responses across composition space. We demonstrate the approach on seed-mediated growth of gold nanoparticles, showcasing its ability to extract design rules, reveal secondary interactions, and efficiently navigate morphology space. Gradient-based optimization of the models enables inverse design, making this a unified platform.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Interaction Effects on the Dynamical Anderson Metal-Insulator Transition Using Kicked Quantum Gases

Understanding the interplay of interaction and disorder in quantum transport poses long-standing scientific challenges for theory and experiment. While highly controlled ultracold atomic platforms combining atomic interactions with spatially disordered lattices have led to remarkable advances, the extension of such controlled studies to phenomena in high-dimensional disordered systems, such as the three-dimensional Anderson metal-insulator transition has been limited. Kicked quantum gases provide an alternate experimental platform that captures the Anderson model in momentum space and features dynamical localization as the analog of Anderson localization. Here, we utilize a momentum space lattice platform using quasiperiodically kicked ultracold atomic gases to experimentally investigate interaction effects on the three-dimensional dynamical Anderson metal-insulator transition. Here, we observe interaction-driven subdiffusion and a divergence of delocalization onset time on approaching the phase boundary. Mean-field numerical simulations show qualitative agreement with experimental observations, but with significant quantitative deviations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Controlling structural phases of Sn through lattice engineering

Topology and superconductivity, two distinct phenomena, offer unique insight into quantum properties and their applications in quantum technologies, spintronics, and sustainable energy technologies. Tin (Sn) plays a pivotal role here as an element because of its two structural phases, α-Sn exhibiting topological characteristics and β-Sn showing superconductivity. Here, we demonstrate precise control of these phases in Sn thin films using molecular beam epitaxy with systematically varied lattice parameters of the buffer layer. The Sn films exhibit either β-Sn or α-Sn phases as the buffer layer's lattice constant varies from 6.10 Å to 6.48 Å, spanning the range from GaSb (like InAs) to InSb. Further, the crystal structures of α- and β-Sn films are characterized by x-ray diffraction and confirmed by Raman spectroscopy and scanning transmission electron microscopy. Atomic force microscopy validates the smooth, continuous surface morphology. Electrical transport measurements further verify the phases: resistance drop near 3.7 K for β-Sn superconductivity and Shubnikov-de Haas oscillations for α-Sn topological characteristics. Density functional theory shows that α-Sn is stable under tensile strain and β-Sn under compressive strain, aligning well with experimental findings. Hence, this study introduces a platform controlling Sn phases through lattice engineering, enabling innovative applications in quantum technologies and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nonmonotonic Band Flattening near the Magic Angle of Twisted Bilayer MoTe 2

Twisted bilayer MoTe 2 (tMoTe 2 ) is an emergent platform for exploring exotic quantum phases driven by the interplay between nontrivial band topology and strong electron correlations. Direct experimental access to its momentum-resolved electronic structure is essential for uncovering the microscopic origins of the correlated topological phases therein. Here, we report angle-resolved photoemission spectroscopy measurements of tMoTe 2 , revealing pronounced twist-angle-dependent band reconstruction shaped by orbital character, interlayer coupling, and moiré potential modulation. Density functional theory captures the qualitative evolution, yet underestimates key energy scales across twist angles, highlighting the importance of electronic correlations. Notably, the hole effective mass at the 𝐾 point exhibits a nonmonotonic dependence on twist angle, peaking near 2°, consistent with band flattening at the magic angle predicted by continuum models. Via electrostatic gating and surface dosing, we further visualize the evolution of electronic structure versus doping, enabling direct observation of the conduction band minimum and confirm tMoTe 2 as a direct band gap semiconductor. These results establish a spectroscopic foundation for modeling and engineering emergent quantum phases in this moiré platform.

2D materials↗
DOE OSTI2026

Mott vs Kondo: Influence of various density functional based methods on the Ce isostructural phase transition mechanism

The cerium iso-structural phase transition (γ–α) is dominated by f-electron localization changes that results in a magnetic ordering change and a volume collapse. Generally, these physics are difficult to capture with ab initio and first principles methods. However, previous works have shown various methods to be successful in predicting at least some of the physics of the γ to α phase transition. Therefore, here, we perform a broad survey of density functional based methods across three levels of theory and types of functions [GGA (generalized gradient approximation), MetaGGA, and hybrid functionals] and compare the results, focusing on hydrostatic compression across the phase boundary at zero kelvin. For the methods that best reproduce experimental results, we directly probe the predicted mechanisms and frame the results in the Mott/Kondo debate, assessing how the underlying methods and assumptions of different functionals can assess the physical drivers in the phase transition, providing insight into the governing processes of this unique phase transition.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Coupled Theoretical and Experimental Approach to Elucidating the Mechanisms of Methyl Esters

The goal of this project was to probe fundamental kinetics questions regarding the gas phase reactive behavior of oxygenates. In order to succeed, our program necessitated both the development of new experimental tools and the development of theory based kinetic models to explain the chemistry of oxygenate fuels. By using advanced hybrid additive manufacturing/ traditional manufacturing techniques to create specialized ceramic micro-reactors, the team was able to simulate extreme high-temperature environments with much greater precision and durability than was previously possible. These tiny, high-tech tubes allow researchers to capture and identify "fleeting" chemical species—molecules that exist for only a fraction of a millisecond—using sophisticated light sources and mass spectrometry. Additionally, the team supported the development of a tabletop VUV laser system for isomer detection without a synchrotron. Through this work, we have successfully mapped out the specific chemical pathways of various oxygen-rich fuels, solving long-standing mysteries about how these substances break down kinetically. Ultimately, this research provides the fundamental knowledge needed to design next-generation engines and fuels that are better for the environment.

09 BIOMASS FUELS↗
DOE OSTI2025

Multi-modality deep learning for pulse prediction in homogeneous nonlinear systems via parametric conversion

In this Letter, we introduce FusionNet, a multi-modality deep learning framework designed to predict and analyze output pulses in high-power rare-earth-doped laser systems driving parametric conversion in homogeneous guided nonlinear media. FusionNet integrates temporal, spectral, and physical experimental conditions to model ultrafast nonlinear phenomena, including parametric nonlinear frequency conversion, self-phase modulation, and cross-phase modulation in homogeneous guided systems such as gas-filled hollow-core fibers. These systems bridge physical models with experimental data, advancing our understanding of light-guiding principles and nonlinear interactions while expediting the design and optimization of on-demand high-power, high-brightness systems. Our results demonstrate a 73% reduction in prediction error and an 83% improvement in computational efficiency compared to conventional neural networks. This work establishes a new paradigm for accelerating parametric simulations and optimizing experimental designs in high-power laser systems, with further implications for high-precision spectroscopy, quantum information science, and distributed entangled interconnects.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Phase Transformation Driven by Oxygen Vacancy Redistribution as the Mechanism of Ferroelectric Hf 0.5 Zr 0.5 O 2 Fatigue

As a promising candidate for nonvolatile memory devices, the hafnia-based ferroelectric system has recently been a hot research topic. Although significant progress has been made over the past decade, the endurance problem is still an obstacle to its final application. In perovskite-based ferroelectrics, such as the well-studied Pb[Zr x Ti 1-x ]O 3 (PZT) family, polarization fatigue has been discussed within the framework of the interaction of charged defects (such as oxygen vacancies) with the moving domains during the switching process, particularly at the electrode-ferroelectric interface. Armed with this background, a hypothesis is set out to test that a similar mechanism can be in play with the hafnia-based ferroelectrics. The conducting perovskite La-Sr-Mn-O is used as the contact electrode to create La 0.67 Sr 0.33 MnO 3 / Hf 0.5 Zr 0.5 O 2 (HZO)/ La 0.67 Sr 0.33 MnO 3 capacitor structures deposited on SrTiO 3 -Si substrates. Nanoscale X-ray diffraction is performed on single capacitors, and a structural phase transition from polar o-phase toward non-polar m-phase is demonstrated during the bipolar switching process. The energy landscape of multiphase HZO has been calculated at varying oxygen vacancy concentrations. Based on both theoretical and experimental results, it is found that a polar to non-polar phase transformation caused by oxygen vacancy redistribution during electric cycling is a likely explanation for fatigue in HZO.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Verification and validation of detonation-shock-dynamics relations for explosives described by general equation of state and chemical reaction models

Detonation shock dynamics is a powerful method to model the behaviour of High Explosives (HE). However in order to use this method, the underlying relationship between the local radius of curvature and the detonation speed must be known. Previous work has developed methods to calculate this effect using simple, single-step Arrhenius and polytropic gas, models for the chemical reaction and the equation of state, respectively. In recent years, more complex models for both reaction rates and equations of state have been developed which show better agreement with experimental data than these simple models, especially when considering condensed phase explosives.. This work presents the governing equations for solving these problems in a way that is generalised to use arbitrary equations of state as well as reaction models which may have more than a single step and multiple product species. This implementation is verified against exact solutions, demonstrating that the equations were implemented properly. The verified algorithm is then validated against experimental data and high fidelity simulations, showing that it is able to make accurate predictions in a regime where the underlying assumptions of the governing equations are valid. Importantly, this approach has many applications: from creating equivalent detonation shock dynamics models for existing reactive burn calibrations for HE; to developing new functional forms and calibrations of reactive burn models for condensed phase high explosives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Hydrogen density mapping in biomolecular crystals through dynamic nuclear polarization

Many fundamental biological processes, including those in photosynthetic reaction centers and enzyme active sites, involve charge and energy transfer, bond cleavage, protonation and hydrogen bonding. Because H atoms play such central roles in these reactions, accurately determining their positions is essential. Yet, conventional X-ray crystallography primarily resolves the heavy atoms in biological structures and provides limited insight into hydrogen, even at atomic resolution. Neutron macromolecular crystallography (NMC) overcomes this limitation by offering exceptional sensitivity to hydrogen and deuterium. Here, we present a theoretical framework for the development of dynamic nuclear polarization NMC (DNP-NMC) techniques, which exploit the alignment of neutron and proton nuclear spins to enhance and tune the hydrogen signal contribution. The DNP-NMC approach advances the resolution of H atoms within biomolecular crystals, whether bound to protein residues or present in solvent. The method establishes key relationships for the coherent structure factor of polarized neutron scattering from hydrogenous matter. It theoretically achieves full accuracy in phase reconstruction and offers a path to improve neutron structure determination, achieving accuracies exceeding ≳80% by incorporating titration states. Using a variant of the hybrid input/output phase-retrieval algorithm, it allows recovery of the hydrogen density with ≳90% phase accuracy. In conclusion, we further discuss sources of experimental uncertainty for the upcoming DNP-enabled, quasi-Laue IMAGINE-X experiment at Oak Ridge National Laboratory's High Flux Isotope Reactor.

dynamic nuclear polarization↗
DOE OSTI2025

Non-equilibrium states and interactions in the topological insulator and topological crystalline insulator phases of NaCd4As3

Topological materials are of great interest because they can support metallic edge or surface states that are robust against perturbations, with the potential for technological applications. Here, we experimentally explore the light-induced non-equilibrium properties of two distinct topological phases in NaCd4As3: a topological crystalline insulator (TCI) phase and a topological insulator (TI) phase. This material has surface states that are protected by mirror symmetry in the TCI phase at room temperature, while it undergoes a structural phase transition to a TI phase below 200 K. After exciting the TI phase by an ultrafast laser pulse, we observe a leading band edge shift of >150 meV that slowly builds up and reaches a maximum after ∼0.6 ps and that persists for ∼8 ps. The slow rise time of the excited electron population and electron temperature suggests that the electronic and structural orders are strongly coupled in this TI phase. It also suggests that the directly excited electronic states and the probed electronic states are weakly coupled. Both couplings are likely due to a partial relaxation of the lattice distortion, which is known to be associated with the TI phase. In contrast, no distinct excited state is observed in the TCI phase immediately or after photoexcitation, which we attribute to the low density of states and phase space available near the Fermi level. Our results show how ultrafast laser excitation can reveal the distinct excited states and interactions in phase-rich topological materials.

Angle-resolved photoemission spectroscopy↗