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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 1,621 records · Page 90

Finite temperature effects on the X-ray absorption spectra of lithium compounds: First-principles interpretation of X-ray Raman measurements

We elucidate the role of room-temperature-induced instantaneous structural distortions in the Li K-edge X-ray absorption spectra (XAS) of crystalline LiF, Li{sub 2}SO{sub 4}, Li{sub 2}O, Li{sub 3}N, and Li{sub 2}CO{sub 3} using high resolution X-ray Raman spectroscopy (XRS) measurements and first-principles density functional theory calculations within the eXcited electron and Core Hole approach. Based on thermodynamic sampling via ab initio molecular dynamics simulations, we find calculated XAS in much better agreement with experiment than those computed using the rigid crystal structure alone. We show that local instantaneous distortion of the atomic lattice perturbs the symmetry of the Li 1s core-excited-state electronic structure, broadening spectral line-shapes and, in some cases, producing additional spectral features. The excellent agreement with high-resolution XRS measurements validates the accuracy of our first-principles approach to simulating XAS, and provides both accurate benchmarks for model compounds and a predictive theoretical capability for identification and characterization of multi-component systems, such as lithium-ion batteries, under working conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Artifact reduction in industrial computed tomography via data fusion

As the most stressed part of a gas turbine the first row of turbine blades is not only a challenge for the materials used. Also the testing of these parts have to meet the highest standards. Computed tomography (CT) as the technique which could reveal the most details also provides the biggest challenges [1]: A full penetration of large sized turbine blades is often only possible at high X-ray voltages causing disproportional high costs. A reduction of the X-ray voltage is able to reduce these arising costs but yields non penetration artifacts in the reconstructed CT image. In most instances, these artifacts manifests itself as blurred and smeared regions at concave edges due to a reduced signal to noise ratio. In order to complement the missing information and to increase the overall image quality of our reconstruction, we use further imaging modalities such as a 3-D Scanner and ultrasonic imaging. A 3-D scanner is easy and cost effective to implement and is able to acquire all relevant data simultaneously with the CT projections. If, however, the interior structure is of supplemental interest, an ultrasonic imaging method is additionally used. We consider this data as a priori knowledge to employ them in an iterative reconstruction. To do so, standard iterative reconstruction methods are modified to incorporate the a priori data in a regularization approach in combination with minimizing the total variation of our image. Applying this procedure on turbine blades, we are able to reduce the apparent artifacts almost completely.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Neuromorphic Graph Algorithms: Extracting Longest Shortest Paths and Minimum Spanning Trees

Neuromorphic computing is poised to become a promising computing paradigm in the post Moore's law era due to its extremely low power usage and inherent parallelism. Traditionally speaking, a majority of the use cases for neuromorphic systems have been in the field of machine learning. In order to expand their usability, it is imperative that neuromorphic systems be used for non-machine learning tasks as well. The structural aspects of neuromorphic systems (i.e., neurons and synapses) are similar to those of graphs (i.e., nodes and edges), However, it is not obvious how graph algorithms would translate to their neuromorphic counterparts. In this work, we propose a preprocessing technique that introduces fractional offsets on the synaptic delays of neuromorphic graphs in order to break ties. This technique, in turn, enables two graph algorithms: longest shortest path extraction and minimum spanning trees.

Kay, Bill↗

Efficient QAOA Optimization using Directed Restarts and Graph Lookup

Variational Quantum Algorithms (VQA) aim to enhance the capabilities of Noisy Intermediate-Scale Quantum (NISQ) devices. These algorithms utilize parameterized circuits and classical optimizers to iteratively execute circuits with varying parameters. However, VQA faces computational overheads due to repeated iterations and random restarts. Prior work suggests using basic sub-graphs to transfer parameters for the input graph, reducing optimizer overheads but limiting applicability to structured regular graphs. In real-world applications, random irregular graphs are common, and existing methods are not scalable or practical for such graphs. This paper presents a framework that aims to improve random irregular graphs in VQA. The framework uses graph similarity and important features like total edge counts, average edge counts, and variance. It follows an iterative process to choose basis sub-graphs from a small database and adjust parameters accordingly. Classical optimizers then utilize these parameters to determine when to restart and perform gradient descent. This approach increases the chances of reaching global maximum points.

Wang, Meng↗

Simulations of Radiation Hydrodynamics in Strongly Coupled Plasmas (Final Report)

Radiation propagates throughout the Universe and is often the only information we have from distant astronomical objects. Additionally, radiation plays a key role in systems ranging from the interior of stars to the establishment of shocks at the edges of forming galaxies to neutron star mergers. Here radiative processes, absorption, emission, and scattering, are fundamental to transport of momentum and energy, as well as, the overall evolution of these and other astrophysical systems. In some cases, radiation-dominant systems are also sufficiently dense and ionized, such that, the ions are strongly coupled (ie electrostatic energy >> thermal energy or Γ >> 1), which will affect radiative processes and the transport of radiation. During this project, we developed a computational ray-tracing algorithm to study radiation transport through a simulated neutron star capsule implosion under conditions relevant to Omega-60 laser experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

The Other Artificial Intelligence Hardware Problem

The consolidation of leading-edge semiconductor manufacturing in one company in one country poses two problems: a short-term strategic risk and a long-term innovation risk. Furthermore, both problems remain underexplored because advances in artificial intelligence (AI) algorithms have compensated for a relative lack of advances in AI hardware.

97 MATHEMATICS AND COMPUTING↗

Trajectory Optimization via Unsupervised Probabilistic Learning On Manifolds

This report investigates the use of unsupervised probabilistic learning techniques for the analysis of hypersonic trajectories. The algorithm first extracts the intrinsic structure in the data via a diffusion map approach. Using the diffusion coordinates on the graph of training samples, the probabilistic framework augments the original data with samples that are statistically consistent with the original set. The augmented samples are then used to construct conditional statistics that are ultimately assembled in a path-planing algorithm. In this framework the controls are determined stage by stage during the flight to adapt to changing mission objectives in real-time. A 3DOF model was employed to generate optimal hypersonic trajectories that comprise the training datasets. The diffusion map algorithm identfied that data resides on manifolds of much lower dimensionality compared to the high-dimensional state space that describes each trajectory. In addition to the path-planing worflow we also propose an algorithm that utilizes the diffusion map coordinates along the manifold to label and possibly remove outlier samples from the training data. This algorithm can be used to both identify edge cases for further analysis as well as to remove them from the training set to create a more robust set of samples to be used for the path-planing process.

42 ENGINEERING↗

QPatLib v1.0 — Measurement-based quantum simulation Pauli string unitary pattern collections

This Zenodo record accompanies the paper “Scalable Measurement-Based Quantum Simulation Patterns for Benchmarking” arXiv.2605.12502 and provides QPatLib v1.0 measurement-pattern datasets in human-readable JSONL together with a ZIP archive of OpenQASM 3.0 circuits used for validation and reproducibility. The patterns and circuits implement Pauli string unitaries for benchmark cases. Cases include all possible string combinations for less than 6 qubits and strings used in Hamiltonians for certain diatomic molecules for 6 or more qubits. Format: Each pattern_*.jsonl file is containins measurement patterns for all subsets for a given model/instance and subset strategy: it begins with a preamble containing model metadata, subset definitions, provenance, and (when feasible) full-pattern test results, followed by one pattern entry per subset. Each subset entry includes a required pattern_ascii field storing the measurement pattern in the measurement-calculus/Graphix standard with signal shifting, written left-to-right in the canonical order nodes → edges → measurements (with signal dependencies) → byproduct corrections (X/Z). The circuits are included as circuit_files.zip. Patterns in this record were validated against the corresponding circuits and checked for causal flow. Codes for generating these patterns can be found at QPatLib repository on Github

Graphix↗

Quantitative relationships between film morphology, charge carrier dynamics, and photovoltaic performance in bulk-heterojunction binary vs. ternary acceptor blends

Addressing pertinent and perplexing questions regarding why nonfullerene acceptors (NFAs) promote higher power conversion efficiencies (PCEs) than traditional fullerenes and how photoactive bulk heterojunction (BHJ) film morphology, charge photogeneration, and recombination dynamics dictate solar cell performance have stimulated many studies of polymer solar cells (PSCs), yet quantitative relationships remain limited. Better understanding in these areas offers the potential to advance materials design and device engineering, afford higher PCEs, and ultimate commercialization. Here we probe quantitative relationships between BHJ film morphology, charge carrier dynamics, and photovoltaic performance in model binary and ternary blend systems having a wide bandgap donor polymer, a fullerene, and a promising NFA. We show that optimal PC 71 BM incorporation in a PBDB-TF:ITIC-Th binary system matrix retains the original π-face-on orientation, ITIC-Th crystallinity and BHJ film crystallite dimensions, and reduces film upper surface ITIC-Th segregation. Such morphology changes together simultaneously increase hole (μ h ) and electron (μ e ) mobilities, facilitate light-activated ITIC-Th to PC 71 BM domain electron delocalization, reduce free charge carrier (FC) bimolecular recombination (BR) within PBDB-TF:ITIC-Th mixed regions, and increase FC extraction pathways viaPBDB-TF:PC 71 BM pairs. The interplay of these effects yields significantly enhanced inverted cell short-circuit current density (J SC ), fill factor (FF), and PCE. Unexpectedly, we also find that excessive PC 71 BM in the PBDB-TF:ITIC-Th binary system alters the PBDB-TF orientation to π-edge-on, increases large scale PC 71 BM-rich aggregations and BHJ upper surface PC 71 BM composition. Further, these morphology changes increase parasitic decay processes such as intersystem crossing from photoexcited PC 71 BM, compromising the J SC , FF, and PCE metrics. ITIC-Th X-ray diffraction reveals a unique sidechain-dominated molecular network with previously unknown sidechain-end group stacking, rationalizing the STEM and GIWAXS results, photophysics, and the high μ e . DFT computation reveals charge transfer networks within ITIC-Th crystallites, supporting excited-state electron delocalization from ITIC-Th to PC 71 BM. This structure–property understanding leads to a newly reported NFA blend with PCE near 17%.

14 SOLAR ENERGY↗

Normal and resonant Auger spectroscopy of isocyanic acid, HNCO

In this study, we investigate HNCO by resonant and nonresonant Auger electron spectroscopy at the K-edges of carbon, nitrogen, and oxygen, employing soft X-ray synchrotron radiation. In comparison with the isosteric but linear CO 2 molecule, spectra of the bent HNCO molecule are similar but more complex due to its reduced symmetry, wherein the degeneracy of the π-orbitals is lifted. Resonant Auger electron spectra are presented at different photon energies over the first core-excited 1s → 10a' resonance. All Auger electron spectra are assigned based on ab initio configuration interaction computations combined with the one-center approximation for Auger intensities and moment theory to consider vibrational motion. The calculated spectra were scaled by a newly introduced energy scaling factor, and generally, good agreement is found between experiment and theory for normal as well as resonant Auger electron spectra. A comparison of resonant Auger spectra with nonresonant Auger structures shows a slight broadening as well as a shift of the former spectra between –8 and –9 eV due to the spectating electron. Since HNCO is a small molecule and contains the four most abundant atoms of organic molecules, the reported Auger electron decay spectra will provide a benchmark for further theoretical approaches in the computation of core electron spectra.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

STRUCTURE OF NON-FORCE-FREE MAGNETIC FLUX ROPES IN AN AMBIENT MEDIUM

The structure of non-force-free equilibrium magnetic flux ropes in an ambient medium of specified pressure p{sub a} is studied. A flux rope is a self-organized magnetized plasma structure consisting of a localized channel of electric current and the magnetic field arising from this current. An analytic method is developed to obtain one-dimensional equilibrium solutions satisfying c {sup -1} J Multiplication-Sign B - {nabla}p = 0 subject to the requirements that (1) all physical quantities be nonsingular and continuous, (2) pressure p(r) be physically admissible-real and non-negative, and (3) the magnetic field profile have ''minimum complexity''. The solutions are shown to be characterized by two parameters, B{sup *}{sub t}{identical_to} B-bar{sub t}/(8{pi}p{sub a}){sup 1/2} and B*{sub p} {identical_to} B{sub pa} /(8{pi}p{sub a} ){sup 1/2}, where B-bar{sub t} is the toroidal (axial) field averaged over the cross-sectional radius a and B{sub pa} is the poloidal (azimuthal) field at the edge of the current channel (r = a). The physical constraint on pressure defines equilibrium boundaries in the B*{sub t}-B*{sub p} space beyond which no physical solutions exist. The method is illustrated with a number of families of solutions governed by distinct physical constraints. The force-free limit with p{sub a} {ne} 0 is investigated and is found to be characterized by plasma {beta} = {infinity}. The local Alfven speed V{sub A} and plasma {beta} are computed. The results are scale-invariant.

79 ASTRONOMY AND ASTROPHYSICS↗

Detailed Simulations of a Three-Stage Supercritical Carbon Dioxide Axial Compressor with a Focus on the Shrouded Stator Cavities Flow

This paper describes the findings of detailed simulations performed to investigate the impact of seal teeth cavity leakage flow on the aerodynamic and thermal performance of a three-stage supercritical CO 2 axial compressor. The study compares a shrouded stator configuration (with cavities) to a cantilevered stator configuration (without cavities) to highlight their differences. High-fidelity computational fluid dynamics simulations were performed using non-linear harmonic (NLH) and mixing plane assumptions, considering various possible rotor/stator interface configurations for mixing plane calculations. The key performance parameters for each case were compared, and the best-performing configuration selected for further analysis. The individual stage performance parameters are also examined and compared between the cantilevered and shrouded configurations. It was observed that in the shrouded case, the leakage flow enters the cavity downstream of the stator trailing edge and gets entrained into the primary flow upstream of the stator, leading to boundary layer changes at the hub and degradation of stator and downstream rotor performance. Vortical flow structures were also observed in the stator wells, which tended to change the flow angles around the region, thereby affecting mixing and velocity distribution, resulting in a slight deterioration of compressor performance. Additionally, the study examines windage heating due to shear work from rotating walls, including the seal teeth surface. The amount of shear work done on the leakage flow and the corresponding rise in fluid temperature were quantified, tabulated, and further compared with a simple analytical model, showing good agreement between them and, hence, validating the numerical approach used.

42 ENGINEERING↗

Fast Machine Learning for Quantum Control of Microwave Qudits on Edge Hardware

Quantum optimal control is a promising approach to improve the accuracy of quantum gates, but it relies on complex algorithms to determine the best control settings. CPU or GPU-based approaches often have delays that are too long to be applied in practice. It is paramount to have systems with extremely low delays to quickly and with high fidelity adjust quantum hardware settings, where fidelity is defined as overlap with a target quantum state. Here, we utilize machine learning (ML) models to determine control-pulse parameters for preparing Selective Number-dependent Arbitrary Phase (SNAP) gates in microwave cavity qudits, which are multi-level quantum systems that serve as elementary computation units for quantum computing. The methodology involves data generation using classical optimization techniques, ML model development, design space exploration, and quantization for hardware implementation. Our results demonstrate the efficacy of the proposed approach, with optimized models achieving low gate trace infidelity near $10^{-3}$ and efficient utilization of programmable logic resources.

Sanders, Flor [Columbia U.]↗

Identifying factors controlling the selective ethane dehydrogenation on Pt-based catalysts from DFT based micro-kinetic modeling

Herein, a detailed EDH reaction mechanism on Pt(111), Pt(211), Pt 3 Sn(111) and Pt 3 Sn(211) surfaces has been systematically computed with DFT. A mean-field micro-kinetic model has been established to simulate the product distribution and selectivity on each surface at experimentally relevant conditions. We have uncovered a number of different factors controlling the catalytic performance of Pt-based EDH catalysts, thus leading to a better understanding of experimentally detected phenomenon. In this study, the (111) and (211) model surfaces of Pt and Pt 3 Sn catalysts were chosen to represent the terrace and step-edge sites when simulating the EDH reaction mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polarized XANES Monitors Femtosecond Structural Evolution of Photoexcited Vitamin B 12

Ultrafast, polarization-selective time-resolved X-ray absorption near-edge structure (XANES) was used to characterize the photochemistry of vitamin B 12 , cyanocobalamin (CNCbl), in solution. Cobalamins are important biological cofactors involved in methyl transfer, radical rearrangement, and light-activated gene regulation, while also holding promise as light-activated agents for spatiotemporal controlled delivery of therapeutics. We introduce polarized femtosecond XANES, combined with UV–visible spectroscopy, to reveal sequential structural evolution of CNCbl in the excited electronic state. Femtosecond polarized XANES provides the crucial structural dynamics link between computed potential energy surfaces and optical transient absorption spectroscopy. Polarization selectivity can be used to uniquely identify electronic contributions and structural changes, even in isotropic samples when well-defined electronic transitions are excited. Our XANES measurements reveal that the structural changes upon photoexcitation occur mainly in the axial direction, where elongation of the axial Co–CN bond and Co–N Im bond on a 110 fs time scale is followed by corrin ring relaxation on a 260 fs time scale. In conclusion, these observations expose features of the potential energy surfaces controlling cobalamin reactivity and deactivation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transport barriers to self-propelled particles in fluid flows

Here, we present theory and experiments demonstrating the existence of invariant manifolds that impede the motion of microswimmers in two-dimensional fluid flows. One-way barriers are apparent in a hyperbolic fluid flow that block the swimming of both smooth-swimming and run-and-tumble Bacillus subtilis bacteria. We identify key phase-space structures, called swimming invariant manifolds (SwIMs), that serve as separatrices between different regions of long-time swimmer behavior. When projected into xy space, the edges of the SwIMs act as one-way barriers, consistent with the experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Local-Ising-type magnetic order and metamagnetism in the rare-earth pyrogermanate Er 2 Ge 2 O 7

The recent discoveries of proximate quantum spin-liquid compounds and their potential application in quantum computing informs the search for new candidate materials for quantum spin-ice and spin-liquid physics. While the majority of such work has centered on members of the pyrochlore family due to their inherently frustrated linked tetrahedral structure, the rare-earth pyrogermanates also show promise for possible frustrated magnetic behavior. With the familiar stoichiometry R 2 Ge 2 O 7 , these compounds generally have tetragonal symmetry with a rare-earth sublattice built of a spiral of alternating edge and corner-sharing rare-earth site triangles. Studies on Dy 2 Ge 2 O 7 and Ho 2 Ge 2 O 7 have shown tunable low temperature antiferromagnetic order, a high frustration index, and spin-ice-like dynamics. Here we use neutron diffraction to study magnetic order in Er 2 Ge 2 O 7 (space group P4 1 2 1 2) and find the lowest yet Neél temperature in the pyrogermanates of 1.15 K. Using neutron powder diffraction, we find the magnetic structure to order with k=(0,0,0) ordering vector, magnetic space group symmetry P4' 1 2 1 2', and a refined Er moment of m=8.1μ B near the expected value for the Er 3+ free ion. Provocatively, the magnetic structure exhibits similar “local Ising” behavior to that seen in the pyrocholres where the Er moment points up or down along the short Er-Er bond. Upon applying a magnetic field, we find a first-order metamagnetic transition at ~0.35T to a lower symmetry P2' 1 2' 1 2 structure. This magnetic transition involves an inversion of Er moments aligned antiparallel to the applied field describing a class I spin-flip-type transition, indicating a strong local anisotropy at the Er site—reminiscent of that seen in the spin-ice pyrochlores.

36 MATERIALS SCIENCE↗

Multimodal Approaches for Leveraging Domain Knowledge with State-of-the-Art Machine Learning to Engineer Biocatalysts

This grant aimed to accelerate the development of specialized enzymes—biological catalysts essential for sustainable manufacturing and medicine—by integrating traditional laboratory evolution with cutting-edge artificial intelligence. To achieve this, we developed a suite of high-throughput sequencing tools and a centralized database to bridge the gap between a protein’s genetic "code" and its physical function. By training machine learning models on large datasets, we also demonstrated the ability to move beyond slow, trial-and-error testing to a "generative" approach, where AI can independently design new, versatile enzymes like tryptophan synthases. Ultimately, these findings demonstrate that combining laboratory data with computer-guided design enables the engineering of highly efficient biological tools with unprecedented speed and precision.

59 BASIC BIOLOGICAL SCIENCES↗