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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 1,027 records · Page 57

Up up down down left right left right B A Start for the catalytic hackers of programmable materials

Catalysts have advanced over the last century to accelerate and control reactions based on static active sites. More effective catalysis can be achieved using catalysts that change with time over the course of a reaction, providing a dynamic free energy landscape that is tailored to each step in the reaction sequence. Here, the catalyst is modulated via an input program that directs the surface to change physically or electronically with time, providing information regarding the extent and duration of change optimized for specific combinations of chemistry and programmable catalyst surfaces. While in its infancy, programmable catalysis is advancing with parallel efforts to establish fundamental principles of dynamic catalysts, design of programmable materials, and strategies to design input programs that will control catalysis for faster and more selective reactions.

catalyst↗

Fingerprinting Brownian Motions of Polymers under Flow

Here, we present a quantitative approach to the self-dynamics of polymers under steady flow by employing a set of complementary reference frames and extending the spherical harmonic expansion technique to dynamic density correlations. Application of this method to nonequilibrium molecular dynamics simulations of polymer melts reveals a number of universal features. For both unentangled and entangled melts, the center-of-mass motions in the flow frame are described by superdiffusive, anisotropic Gaussian distributions, whereas the isotropic component of monomer self-dynamics in the center-of-mass frame is strongly suppressed. Spatial correlation analysis shows that the heterogeneity of monomer self-dynamics increases significantly under flow.

36 MATERIALS SCIENCE↗

Chemical Heterogeneity in PAN/LLZTO Composite Electrolytes by Synchrotron Imaging

Solid polymer/ceramic composite electrolytes are promising for batteries due to their attractive thermal stability and mechanical properties. Chemical heterogeneity in solid composite electrolytes, such as the inhomogeneity in the ceramic phase and salt distribution at the polymer/ceramic interface, is critical to the performance of solid composite electrolytes. However, such heterogeneity has not been well understood yet. In this work, we use Synchrotron-based X-ray fluorescence imaging (XRF) and Transmission X-ray Microscope (TXM) to image nanoscale chemical heterogeneity in polyacrylamide/Li 7+x La 3 Zr 2–x Ta x O 12 (LLZTO) composite electrolytes and investigate the effects of lithium salt, salt concentration, and plasticizer. We find that LLZTO particles show strong inter- and intra-particles chemical heterogeneities, and the off-stoichiometry of Zr in an LLZTO particle is unlikely to be only balanced by Ta substitution. Moreover, statistical analysis suggests that LiI tends to accumulate at the ceramic/polymer interface at a low concentration of 5 wt%, but no such tendency was observed in samples with 10 wt% LiI. However, composite electrolytes with LiTFSI show interfacial accumulation at both 5 wt% and 10 wt%. Furthermore, this report provides insight into element distributions in solid composite electrolytes, and we hope further researches can shed light on the connections between chemical heterogeneity and ionic transport pathway inside.

36 MATERIALS SCIENCE↗

Heterogeneity in MacMullin Number of Li-Ion Battery Electrodes Studied by Means of an Aperture Probe

Heterogeneity of MacMullin number within battery electrodes is a key metric affecting cell performance. To characterize this heterogeneity, an aperture probe was developed. This probe, coupled with a newly developed transmission-line model, allows for measurements of tortuosity, represented by the MacMullin number, on millimeter length scales. Local MacMullin number values of seven electrodes were measured, and the ionic resistance profiles of these electrodes are given through contour maps of the MacMullin number. The method is validated by comparing the average MacMullin number to the value obtained through other measurement methods. The results show significant local MacMullin number variation in such electrodes on a millimeter length scale. Furthermore, this method will allow battery manufacturers and researchers to better quantify sources of heterogeneity and improve electrode quality.

25 ENERGY STORAGE↗

DONUT: Physics-aware Machine Learning for Real-time X-ray Nanodiffraction Analysis

SF-25-088 Coherent X-ray scattering techniques are critical for investigating the fundamental structural properties of materials at the nanoscale. While advancements have made these experiments more accessible, real-time analysis remains a significant bottleneck, often hindered by artifacts and computational demands. In scanning X-ray nanodiffraction microscopy, which is widely used to spatially resolve structural heterogeneities, this challenge is compounded by the convolution of the divergent beam with the sample’s local structure. To address this, we introduce DONUT (Diffraction with Optics for Nanobeam by Unsupervised Training), a physics-aware neural network designed for the rapid and automated analysis of nanobeam diffraction data. By incorporating a differentiable geometric diffraction model directly into its architecture, DONUT learns to predict crystal lattice strain and orientation in real-time. Crucially, this is achieved without reliance on labeled datasets or pre-training, overcoming a fundamental limitation for supervised machine learning in X-ray science. We demonstrate experimentally that DONUT accurately extracts all features within the data over 200 times more efficiently than conventional fitting methods.

Zhou, Tao [Argonne National Laboratory (ANL), Argo↗

Prediction and Experimental Verification of Electrolyte Solvation Structure from an OMol25-Trained Interatomic Potential

A molecular-level understanding of electrolyte solvation structure and ion–ion correlations is critical to developing next-generation battery chemistries. Atomistic simulation capabilities with sufficient accuracy, speed, and transferability to deliver reliable structural insights while avoiding arduous system-specific reparameterization are thus highly desirable. Machine learning interatomic potentials (MLIPs) trained on large, chemically diverse data sets are revolutionizing computational chemistry, enabling molecular dynamics simulations of battery electrolytes with near-DFT accuracy over 10,000× faster than DFT. While previous MLIP training data sets with suitable elemental coverage for electrolytes have been based on inorganic materials, the Open Molecules 2025 (OMol25) data set provides large-scale molecular DFT MLIP training data with broad elemental coverage and specifically samples tens of millions of electrolyte configurations. Here, we integrate computational modeling with experimental validation to systematically assess the ability of large-scale MLIPs pretrained on materials data or on OMol25 to accurately resolve nanoscale structural organization and ion-solvation characteristics in Na-ion battery electrolytes across diverse physicochemical conditions and compositional regimes. We find that the OMol25-trained Universal Model of Atoms (UMA-OMol) predicts experimentally measured densities and X-ray structure factors in substantially better agreement compared to state-of-the-art models trained only on inorganic materials data. Using UMA-OMol, we further analyze systematic trends in solvation structure as a function of cation identity, anion chemistry, salt concentration, and solvent topology. We observe that increasing system temperature amplifies the heterogeneity within the solvation environment, perturbing cation–solvent interactions and promoting the formation of contact ion pairs (CIPs). Moreover, subtle variations in the solvent topology of glyme-based electrolytes cause pronounced changes in ion correlations and solvation structure. The experimental agreement and microscopic insights shown here position OMol25-trained MLIPs as a practical route to predictive, high-throughput electrolyte simulations beyond the limits of classical force fields and direct DFT molecular dynamics, serving as a powerful tool for accelerating the design of next-generation Na-ion battery electrolytes and beyond.

MLIPs↗

A novel, mesoporous molybdenum doped titanium dioxide/reduced graphene oxide composite as a green, highly efficient solid acid catalyst for acetalization

A novel, mesoporous composite of Mo doped TiO 2 /reduced graphene oxide is synthesized to be used as a highly efficient heterogeneous acid catalyst. The composite has a high surface area (263 m 2 g -1 ) and a monomodal pore size distribution with an average pore diameter of 3.4 nm. A comprehensive characterization of the synthesized material was done using PXRD, Raman, BET, SEM, EDX, TEM, TGA, and XPS. The composite exhibited excellent catalytic activity (1.6 h -1 TOF, >99% GC yield, and >99% selectivity) towards acetalization of cyclohexanone at room tempertaure within 30 minutes. The catalyst was reusable up to 4 reaction cycles without any significant loss in the activity and the acidic site calculations showed that the reaction is mostly driven by the weak acidic sites on the composite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mapping nanocrystal orientations via scanning Laue diffraction microscopy for multi-peak Bragg coherent diffraction imaging

The recent commissioning of a movable monochromator at the 34-ID-C endstation of the Advanced Photon Source has vastly simplified the collection of Bragg coherent diffraction imaging (BCDI) data from multiple Bragg peaks of sub-micrometre scale samples. Laue patterns arising from the scattering of a polychromatic beam by arbitrarily oriented nanocrystals permit their crystal orientations to be computed, which are then used for locating and collecting several non-co-linear Bragg reflections. The volumetric six-component strain tensor is then constructed by combining the projected displacement fields that are imaged using each of the measured reflections via iterative phase retrieval algorithms. Complications arise when the sample is heterogeneous in composition and/or when multiple grains of a given lattice structure are simultaneously illuminated by the polychromatic beam. Here, a workflow is established for orienting and mapping nanocrystals on a substrate of a different material using scanning Laue diffraction microscopy. The capabilities of the developed algorithms and procedures with both synthetic and experimental data are demonstrated. The robustness is verified by comparing experimental texture maps obtained with Laue diffraction microscopy at the beamline with maps obtained from electron back-scattering diffraction measurements on the same patch of gold nanocrystals. Such tools provide reliable indexing for both isolated and densely distributed nanocrystals, which are challenging to image in three dimensions with other techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A crystal plasticity finite element method modeling of Zircaloy with hydride phases based on scanning electron micrographs

This work developed a microstructure-based finite element model to predict the stress state of alloys with second phase inclusions. Quantitative microstructural details extracted from scanning electron microscopy (SEM) images were used to generate heterogeneous microstructures including the morphology and spatial distribution of hydrides. Generation of digital microstructure was achieved through two steps of tessellations using software Neper and Matlab. The process is demonstrated using an example of Zircaloy material with secondary phases of hydrides dispersed within and stress-strain response of Zircaloy containing hydrides was predicted. The constitutive material model for Zircaloy in this study was based on crystal plasticity theory which considers the hexagonal close-packed (HCP) atomic structure of Zircaloy material. The hydrides were modeled as isotropic elasto-plastic material. A parametric study had been conducted to understand the effect of volume fraction, and lamellae thickness of the hydride phase on the mechanical properties of the overall material. Results can help designers to alter the manufacturing process to obtain the enhanced mechanical properties for components used in nuclear applications made by Zircaloy material.

Kulkarni, Shank S.↗

Design principles for heterointerfacial alloying kinetics at metallic anodes in rechargeable batteries

How surface chemistry influences reactions occurring thereupon has been a long-standing question of broad scientific and technological interest. Here, we consider the relation between the surface chemistry at interfaces and the reversibility of electrochemical transformations at rechargeable battery electrodes. Using Zn as a model system, we report that a moderate strength of chemical interaction between the deposit and the substrate—neither too weak nor too strong—enables highest reversibility and stability of the plating/stripping redox processes. Focused ion beam and electron microscopy were used to directly probe the morphology, chemistry, and crystallography of heterointerfaces of distinct natures. Analogous to the empirical Sabatier principle for chemical heterogeneous catalysis, our findings arise from competing interfacial processes. Using full batteries with stringent negative electrode–to–positive electrode capacity (N:P) ratios, we show that such knowledge provides a powerful tool for designing key materials in highly reversible battery systems based on Earth-abundant, low-cost metals such as Zn and Na.

25 ENERGY STORAGE↗

Towards Realistic Models of Heterogeneous Catalysis: Simulations of Oxidation Catalysis from First Principles

Among the most significant developments in heterogeneous catalysis in the last 20 years is the emergence of microkinetic models, often parameterized from density functional theory (DFT) calculations, used to quantify observed catalyst performance and to guide the discovery of new catalytic materials. While DFT directly reports binding energies and elementary step activation energies, the free energies that enter into microkinetic models must be computed from additional approximations. Frequently these free energy approximations assume ideal behavior—that adsorbates do not interact with one another, or that adsorbates are immobile or vibrate harmonically about a binding site. These assumptions can and do have an impact on predicted catalyst performance and potentially even on predicted trends. Our work relates to three categories of non-idealities, explored in the context of nitrogen oxidation and reduction catalysis on metal surfaces. One component relates to adsorbate translational free energy, the contribution least well described by conventional models, in which we develop modeling approaches that improve accuracy with limited increase in computational expense. A second component relates adsorbate-adsorbate interactions, in which we develop benchmark on-lattice interaction models and compare kinetic predictions with conventional mean-field models, in an effort to develop more robust coverage-dependent mean field modeling approaches. The last relates the most fundamental assumption of all—that of energy equipartition—in an effort to rationalize and guide plasma-enhanced catalysis.

99 GENERAL AND MISCELLANEOUS↗

Development of process parameters and post-build conditions for qualification of LPBF 316 SS

To harness the potential of laser powder bed fusion (LPBF) 316H stainless steel (SS) for use in advanced nuclear reactors, extensive research efforts are needed to develop optimal laser processing parameters and appropriate heat treatments, taking into account various manufacturing platforms and locations. Furthermore, it is crucial to assess the material properties in environments relevant to reactor operating conditions. In collaboration with Oak Ridge National Laboratory (ORNL) and Los Alamos National Laboratory (LANL), Argonne National Laboratory (ANL) is dedicated to gaining insights into how the manufacturing process and post-build treatments impact the performance of LPBF 316H SS. This report provides an overview of ANL's research findings for FY23, focusing on LPBF 316H SS produced using a Renishaw AM400 laser system. Specifically, our research has concentrated on three key areas: 1) Optimum laser processing parameters: Leveraging the high-throughput printing technology, we systematically varied the laser power, exposure time and point distance within the same build. By measuring the as-printed porosity, we identified an optimum printing parameter window that produced materials with near-complete density; 2) Post-built treatment development: Materials printed with the optimum laser parameters underwent treatments including stress relief, solution annealing, and hot isostatic pressing. Subsequently, we fabricated tension, creep, and fatigue specimens from materials subjected to these different conditions. Over the next year, a series of scoping tests will be conducted to facilitate the selection of the most suitable post-build treatment condition; 3) Thermal aging effects on microstructure and properties: thermal aging at 550°C, 650°C and 750°C was conducted on LPBF 316H SS specimens up to 2500 h. Microstructural characterization was performed with electron microscopy, and the evolution of the dislocation cell structures and secondary phases was studied. Microhardness tests and tension tests were conducted to quantify changes in mechanical properties. The results revealed that the aged LPBF 316H SS exhibited a high density of Cr-rich and Mo-rich fine precipitates within grains due to the presence of a high density of dislocations and the globally distributed dislocation cell structures, which served as heterogeneous nucleation sites for secondary phases. Along grain boundaries, a Mo-Cr-rich phase, observed in 750°C-aged conditions, displayed significant thermal coarsening. Throughout the aging process, various mechanisms, including stress relaxation, dislocation cell structure recovery, solution hardening, and precipitation hardening, competed to influence materials strength. These results contribute towards establishing the technical basis for qualifying LPBF 316H SS for advanced nuclear reactor applications.

36 MATERIALS SCIENCE↗

Three-dimensional thermo-mechanical simulations of heterogeneous solid propellants

Here in this work, we present a numerical framework that describes thermo-mechanical deformations in a burning heterogeneous solid propellant. These deformations are quasi-static at time scales associated with combustion, and the resulting thermo-mechanical formulation is discretized on a Cartesian grid using a hypoelastic law. We use a weak form of Chorin-type projection method to deal with large difference in shear modulus of the constituent materials. Extending our previous two-dimensional work, grid convergence studies for a three-dimensional propellant configuration are presented for the stress, velocity, and reference map components. Finally, simulations are carried out for a random propellant pack that is coupled to a gas phase, and we present results for the pack undergoing combustion, with and without deformations.

simulations↗

Advancing material modeling in hydrocodes using a concurrent finite-element and molecular dynamics multiscale framework

We present a multiscale simulation framework that couples the finite-element method with molecular dynamics. Bypassing traditional equations of state (EOS) by using in-line atomistic simulations, the method offers the advantage of incorporating detailed microscale physics not easily represented with coarse-grained models. Coupling consistency with the continuum code is ensured through the use of lifting and restriction operators, in line with heterogeneous multiscale methods. The concurrent continuum-atomistic framework is validated through comparison with experimental results and conventional EOS models, and demonstrated in a shock-driven hydrodynamic flow simulation under extreme conditions. We further evaluate the framework's usability by comparing it to state-of-the-art EOS models of deuterium. A computational performance study reveals that the atomistic EOS evaluation is a feasible alternative to conventional approaches, and demonstrates a weak scaling of 99% efficiency. These results highlight the framework's potential for large-scale multiscale modeling across a broad range of materials and conditions.

Computer science↗

Nonlinear Nano‐Imaging of Interlayer Coupling in 2D Graphene‐Semiconductor Heterostructures

The emergent electronic, spin, and other quantum properties of 2D heterostructures of graphene and transition metal dichalcogenides are controlled by the underlying interlayer coupling and associated charge and energy transfer dynamics. However, these processes are sensitive to interlayer distance and crystallographic orientation, which are in turn affected by defects, grain boundaries, or other nanoscale heterogeneities. This obfuscates the distinction between interlayer charge and energy transfer. Here, nanoscale imaging in coherent four‐wave mixing (FWM) and incoherent two‐photon photoluminescence (2PPL) is combined with a tip distance‐dependent coupled rate equation model to resolve the underlying intra‐ and inter‐layer dynamics while avoiding the influence of structural heterogeneities in mono‐ to multi‐layer graphene/WSe 2 heterostructures. With selective insertion of hBN spacer layers, it is shown that energy, as opposed to charge transfer, dominates the interlayer‐coupled optical response. From the distinct nano‐FWM and ‐2PPL tip‐sample distance‐dependent modification of interlayer and intralayer relaxation by tip‐induced enhancement and quenching, an interlayer energy transfer time of τ ET ≈ ( 0 . 35 − 0.15 + 0.65 ) $\tau _{\rm ET} \approx (0.35^{+0.65}_{-0.15})$ ps consistent with recent reports is derived. As a local probe technique, this approach highlights the ability to determine intrinsic sample properties even in the presence of large sample heterogeneity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Multi-scale structural analysis of swift heavy ion-irradiated ZrO 2 and HfO 2

The radiation-induced monoclinic-to-tetragonal phase transition in ZrO 2 and HfO 2 has been the subject of many investigations, but the transformation pathways and underlying structural mechanisms are still not well understood. In this study, microcrystalline powder samples of ZrO 2 and HfO 2 were irradiated with 946 MeV and 1470 MeV Au ions to a wide fluence range up to 3 × 10 13 ions/cm 2 . To characterize beam-induced structural modifications across all spatial length scales, complementary experimental techniques such as synchrotron X-ray diffraction and spallation neutron total scattering were used. The phase evolution of the tetragonal polymorph with increasing ion fluence is accurately described by a heterogeneous track-overlap model that incorporates both direct- and double-impact processes. These damage accumulation processes are an expression of a core-shell ion track morphology that depends on irradiation conditions and target material. Neutron pair distribution function analysis revealed that ion-beam-induced tetragonal ZrO 2 is merely a configurational average of short-range orthorhombic (Pbcn) domains stabilized by a dense network of domain walls. Furthermore, this knowledge is critical for a better understanding of how crystalline-to-crystalline phase transformations proceed at the atomic scale under extreme conditions.

Monoclinic-to-tetragonal phase transformation↗