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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Synthesis, Properties, and Electrochemical Proton Reduction of a Homoleptic Tetrathiolato Ni-Site Model of [NiFe]-Hydrogenase

[NiFe]-hydrogenase enzymes process H 2 at a nonplanar tetracysteinato-Ni site, the sole participator in proton binding/redox chemistry during turnover. With the objective of assessing whether a simple tetrahedral/ tetrathiolato-Ni 2+ core could promote H 2 evolution reaction (HER), we synthesized (Et 4 N) 2 [Ni(S-p-CF 3 −Ph) 4 ] (1) employing para-trifluoromethylbenzenethiolate ( − S-p-CF 3 −Ph) as a Ni-site analog of [NiFe]-hydrogenase. Spectroscopic measurements and X-ray crystallography confirm the distorted tetrahedral geometry of 1. Dissolution of 1 results in partial thiolate dissociation and formation of S,S-bridged complexes such as (Et 4 N) 2 [Ni 2 (S-p-CF 3 −Ph) 6 ] (3) among other ill-defined species. Dissociation is further accelerated in the presence of Brønsted acids, complicating the assessment of 1 for proton reduction. However, this dissociation/proton instability is suppressed in the presence of additional thiolate ligand to ensure tetrahedral/tetrathiolato 1 persists in solution. Electrochemical HER activity was evaluated by monitoring the current response of an MeCN solution of 1/ excess thiolate after sequential titration with a weak Brønsted acid (acetic acid). The results suggest that 1 is a modest electrocatalyst for the HER with a turnover frequency of 14.5 ± 3.6 s −1 and an overpotential of 0.72 ± 0.02 V. Control experiments and supplementary DFT computations indicate that 1, or a species derived from 1, is responsible for the HER and suggest an ECCE-type mechanism.

Evolution reactions↗
DOE OSTI2025

Preventing Loss of Selectivity during the Oxidative Dehydrogenation of Propane over Supported Vanadium Catalysts

Supported vanadium materials are promising catalysts for the oxidative dehydrogenation of propane to propylene (ODHP), but a lack of mechanistic understanding limits the rational design of catalysts with improved propylene selectivity. Adding Ta to V/SiO 2 increases the propylene selectivity, as well as the activity, leading to superior performance compared to state-of-the-art boron-based systems. In this contribution, we utilize this surprising promotional effect of Ta to elucidate key elements of the mechanistic cycle. Through a combination of characterization techniques, computational modeling, and kinetic experiments, we show that the catalytic cycle over V/SiO 2 likely involves the formation of an isopropyl alcohol intermediate, the fate of which is in kinetic competition between subsequent dehydration to propylene or further oxidation. Furthermore, we show that the relatively facile propylene overoxidation observed for these materials occurs via the epoxidation of propylene by a proposed peroxovanadium intermediate, rather than the abstraction of propylene’s allylic C–H bond as previously assumed. Using these key mechanistic features, we rationalize the enhanced selectivity and activity of Ta promotion. In conclusion, our mechanistic framework offers avenues for future catalyst development to improve supported vanadium materials for ODHP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Chemically Separable Ruthenium Hydride Isomers with Distinct Hydride Transfer Properties

Transition metal hydrides are key intermediates in biological and industrial catalysis, where control over hydride donor ability (hydricity) is essential for optimizing reactivity. Herein, we report a series of isomeric ruthenium hydrides in which the ligand trans to the ruthenium hydride bond–either an N-heterocyclic carbene or pyridine–modulates the thermodynamic hydricity by up to 8 kcal mol –1 . These hydrides exhibited distinct reactivity toward CO 2 and various organic hydride acceptors, enabling detailed kinetic and mechanistic analysis. Stopped-flow experiments, isotopic labeling, and computational studies supported an outer-sphere hydride transfer mechanism. Linear free energy relationships (LFERs) and Marcus relationships were utilized to correlate the changes in thermodynamics and kinetics, revealing that ligands with strong trans effects and trans influence can disrupt conventional scaling relationships, which can be a powerful strategy for promoting new reactivity paradigms in hydride transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Photoenzymatic Csp 3 –Csp 3 bond formation via enzyme-templated radical–radical coupling

Cross-couplings are essential reactions in modern chemical synthesis, enabling the rapid construction of complex molecules from simple precursors. Transition metal catalysts are prized for these transformations because their reactivity and selectivity can be tuned via judicious selection of the metal and ligand. Although enzymes offer analogous opportunities for tuning via protein engineering, their application to cross-coupling remains limited, as nature relies on alternative paradigms for building molecular complexity. Here, we report the cross-coupling of alkyl halides and benzylic carboxylic acids using an engineered flavin-dependent lactate monooxygenase—a photoenzyme. The enzyme achieves this feat by exploiting the redox versatility of the flavin cofactor. Stoichiometric experiments, ultrafast spectroscopy, and computational studies support a mechanism in which photoexcited flavin quinone initiates the reaction via oxidative decarboxylation to generate a benzylic radical. The resulting flavin semiquinone can reduce the alkyl halide to form a second organic radical within the protein active site, which rapidly engages in C(sp 3 )–C(sp 3 ) bond formation. A variant was engineered to control the stereochemical outcome of this radical–radical coupling event, highlighting the ability of the protein to alter the energetic barrier for a mechanistic step that is traditionally understood to be near barrierless. This work demonstrates that the scope for nonnative reaction mechanisms in biocatalysis far exceeds previously established bounds and has potential to solve a variety of reactivity challenges in cross-coupling chemistry.

biocatalysis↗
DOE OSTI2026

Efficient CP Rounding Using Alternating Least Squares with QR Decomposition

The CANDECOMP/PARAFAC (CP) decomposition is widely used for analyzing multidimensional data, and the alternating least squares (CP-ALS) algorithm is a common method for its computation. CP rounding is the problem of computing a lower-rank CP decomposition of an input already in a higher-rank CP format. While the normal equations (NE) approach in CP-ALS is efficient for the CP rounding problem and frequently used, it becomes unstable in the presence of ill-conditioned subproblems. This paper presents a new QR-based CP-ALS method for CP rounding that preserves both numerical stability and computational efficiency. Here, our experiments show that the proposed method offers significant speedup over a previous QR-based approach and the Tensor Toolbox's NE-based implementation, particularly for higher-order tensors. Furthermore, our approach demonstrates a marked reduction in error for ill-conditioned problems, with error reductions several orders of magnitude smaller compared to the NE-based method, while achieving faster convergence and more accurate solutions. By using a more numerically stable approach, we can solve more problems in reduced working precision, which enables further reduction in time to solution.

CANDECOMP/PARAFAC↗
DOE OSTI2026

Data for "Photoinduced Chemomimetic Biocatalysis for Enantioselective Intermolecular Radical Conjugate Addition"

Exploiting nature’s catalysts for non-natural transformations that are inaccessible to chemocatalysis is highly desirable but challenging. On the one hand, the widespread nicotinamide-dependent oxidoreductases have not been utilized for single-electron-transfer-induced bimolecular cross-couplings; on the other, the addition of catalytic asymmetric radical conjugate to terminal alkenes remains a challenge owing to strong racemic background reaction and unselective termination of prochiral radical species. Here we report a chemomimetic biocatalysitic approach for construction of alpha-carbonyl stereocentres via an unnatural intermolecular conjugate addition of N-(acyloxy)phthalimides-derived radicals with acceptor-substituted terminal alkenes, by combination of visible-light excitation and nicotinamide-dependent ketoreductases (KREDs). Based on protein crystal structure, we engineered KREDs via a semi-rational mutagenesis strategy to improve reaction outcomes with a small and high-quality variants library. Mechanistic investigations combining wet experiments, crystallographic studies and computational simulations demonstrate that the repurposed biocatalyst can suppress racemic background reaction and unselected side reactions, yielding enantioselectivity that is challenging to achieve by chemocatalysis.

Catalysis↗
DOE OSTI2025

Integrated photonic Galton board and its application for photon counting

The Galton board is a desktop probability machine traditionally used to visualize the principles of statistical physics from classical particles. Here, we demonstrate a photonic Galton board that enables on-chip observation of statistics from single-photon interference. The photonic Galton board consists of a directional coupler matrix terminated by an array of superconducting nanowire detectors to provide spatiotemporal resolution. This design also allows for photon-number-resolving capability, making it suitable for high-speed photon counting. Our results demonstrate the compatibility between single-photon detector array and photonic integrated circuits, paving the way for implementing on-chip large-scale quantum optics experiments and photonic quantum computing.

Qin, Hezheng (ORCID:0009000139348800)↗
DOE OSTI2025

An Efficient Storage-Driven Machine Learning Model for Performance in the Era of Multimodal Scientific Data

Scientific workflows are increasingly relying on machine learning (ML), simulation, and hybrid techniques to predict, understand, and optimize the behavior of complex experiments. High-performance computing has greatly improved researchers’ ability to acquire diverse data modalities in these workflows. Recent studies suggest that the performance of machine learning models can be improved by integrating data from various sources. Unfortunately, these workloads pose unprecedent pressure on the network storage to meet the demands associated with accessing these multimodal data. To mitigate the impact of intensive IO, we propose a solution that utilizes a multi-tier High-Performance Computing (HPC) distributed storage and data processing framework, placing computation where the data resides for better performance. By adopting this project, the scientific community will gain new opportunities to explore multimodal storage-driven possibilities, integrating multiple scientific data sources with advanced streaming frameworks. Additionally, our framework effectively utilizes computing resources and bridges the gaps identified by HPC experts. Our proposed approach tackles scalability and persistence challenges by leveraging native persistency, which has posed difficulties in traditional approaches. Furthermore, we seek to enhance fault-tolerance and load-balance of computations by leveraging real-time streaming in diverse scientific computing environments, thereby propelling advanced scientific computing research into the next generation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Optical Particle Measurements during EPCAPE Field Campaign Report

This campaign requested the deployment of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility optical particle counter (OPC) at the first ARM Mobile Facility (AMF1) located at the Scripps Pier in La Jolla, California during the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE). The addition of the OPC was requested for two reasons. (1) Close the gap between the scanning mobility particle sizer (SMPS) and aerodynamic particle sizer (APS) size distribution from the Aerosol Observing System (AOS) measurements. (2) Principal investigator Petters has been working with Tracking Aerosol Convection Interaction Experiment (TRACER) data to compute particle fluxes from Doppler lidar (Petters et al. 2024). Briefly, backscatter flux is obtained using the eddy covariance technique using the Doppler vertical velocity and attenuated backscatter. Building upon prior studies, we were able to relate backscatter to particle number concentration by calibrating the lidar retrievals against optical particle counter-measured ground-based aerosol size distribution and radiosonde-interpolated relative humidity at lidar sample height. Performing similar analysis was of interest to EPCAPE to better understand the emissions and vertical transport of large particles into the overlying stratus clouds. However, as stated above, this analysis requires an optical size distribution that covers the 0.3-30-μm-diameter size range. The OPC was deployed between 2023-04-14 and 2024-02-14. The deployment, data quality analysis, and data archiving was handled by the DOE ARM instrument mentor team without additional involvement by the principal investigator. Data quality was marked as “routine” for the majority of the campaign.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Reconstruction of 6D Phase Space

A ‘Phase Space’ is a mathematical representation of all possible physical states of matter of a physical volume or system. Particle beams at Fermilab exist in a six-dimensional phase space: three position dimensions, and three momentum dimensions. To ‘reconstruct’ that space means to take measurement data from virtual detectors along those beams and map out where particles are and how they’re moving, using computational methods. In this experiment, we simulated a particle beam (Fig 1) and used the position distribution of each particle at each detector to map out the magnitude of the beam’s initial momentum.

Shirlee, Jermaine [DuPage Coll.]↗
DOE OSTI2025

A Demonstration of ARCANE Reweighting: Reducing the Sign Problem in the MC@NLO Generation of $e^+ e^- \rightarrow q \bar{q} + 1\, jet$ Events

Negatively weighted events, which appear in the simulation of particle collisions, significantly increase the computational requirements of collider experiments. A new technique called ARCANE reweighting has been introduced in a companion paper to tackle this problem. This paper demonstrates the technique for the next-to-leading-order generation of $e^+ e^- \rightarrow q \bar{q} + 1\, jet$ events. By redistributing the contributions of "standard" and "hard remainder" pathways in the generator that lead to the same final event, ARCANE reweighting almost completely eliminates the negative weights problem for this process. Some thoughts on implementing the technique in other scenarios are provided.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Simulating Alpha Particles Incident on MKID Chips for Quantum Sensitivity Analysis

Superconducting quantum devices, such as microwave kinetic inductance detectors (MKIDs), are highly sensitive instruments used in quantum computing and advanced sensing technologies. However, their extreme sensitivity also makes them vulnerable to background noise from natural sources like radiation. One significant contributor to this noise is alpha particles emitted by 210Po, a radon decay daughter that accumulates on surfaces near the detector. This project investigates how alpha particles emitted from 210Po interact with MKID chips. These particles can deposit energy on the detector surface, disrupting its operation and generating false signals. Understanding the energy and behavior of these particles is crucial for improving the design and reliability of quantum devices. To explore this, we first modeled the decay chain starting from 210Pb to 210Po using differential equations. This allowed us to predict how the activity of alpha-emitting isotopes changes over time, reaching a steady state after about two years. Next, we simulated alpha particle interactions with the MKID chip using the Geant4 software toolkit. We built a detailed computer model of the detector housing, including the copper lid where alpha particles originate, the silicon chip, and a thin aluminum sensor layer. Alpha particles were emitted isotropically from just beneath the copper lid’s surface, mimicking natural decay conditions. The simulation tracked how these particles deposit energy on the chip, generating electron-hole pairs and phonons. The results provide insight into the behavior of the resultant electron-hole pairs and phonons, giving us a clear understanding of the energy deposition distribution on the chip. This work supports efforts to mitigate background noise in superconducting sensors, advancing their use in quantum computing and sensitive physics experiments.

Hall, Matthew [Fermilab; UCLA]↗
DOE OSTI2024

AI/ML Expo Boosting Job Performance with AI: Innovative Approaches and Success Stories

Our technology leverages artificial intelligence (AI) to enhance the user experience in High Performance Computing (HPC) environments. By analyzing user behavior and providing personalized recommendations, our AI system helps HPC users optimize their workflows and improve productivity. Additionally, we offer an advanced image similarity search feature, which utilizes AI algorithms to identify and retrieve visually similar images, saving users valuable time and effort in their research and analysis.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Comparison of GPU-Accelerated Multiphase CFD Solvers on the Polaris Supercomputer: Part 1

This report is in support of the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program sponsored by the U.S. Department of Energy (USDOE). With INCITE-level resources, one project, titled BubblyFlow, was granted computational resources for the 2025 calendar year on the Polaris supercomputer at the Argonne Leadership Computing Facility (ALCF). The project aims to conduct simulations to understand the fundamental characteristics of turbulent bubbly flow phenomena in nature. Staff at the ALCF and Argonne’s Computational Science division, along with collaborators at the City College of New York and University of Illinois at Chicago, helped a summer student to assess the accuracy and performance of two high performance computing (HPC) codes. Both codes, ImExLBM and FluTAS, are fundamentally different in their mathematical and numerical modeling. However, both may be used to solve the same physical problem. The collaboration sought to better understand the differences between both codes in terms of accuracy and efficiency. This would ultimately help the BubblyFlow project better utilize resources and establish a knowledge-base of code capabilities in future simulation campaigns. We compare ImExLBM and FluTAS, two high-performance multiphase computational fluid dynamics (CFD) solvers, in terms of physical fidelity, time-to-solution, and parallel efficiency. We validate ImExLBM (Implicit-Explicit Lattice Boltzmann Method) against a canonical benchmark and assess it’s performance relative to FluTAS (Fluid Transport Accelerated Solver), a well-established open-source CFD code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Average Rényi entanglement entropy in Gaussian boson sampling

Recently, many experiments have been conducted with the goal of demonstrating a quantum advantage over classical computation. One popular framework for these experiments is Gaussian boson sampling, where quadratic photonic input states are interfered via a linear optical unitary and subsequently measured in the Fock basis. In this paper, we study the modal entanglement of the output states in this framework just before the measurement stage. Specifically, we compute Page curves as measured by various Rényi- α entropies, where the Page curve describes the entanglement between two partitioned groups of output modes averaged over all linear optical unitaries. We derive these formulas for α = 1 (i.e., the von Neumann entropy) and, more generally, for all positive integer α , in the asymptotic limit of infinite number of modes and for input states that are composed of single-mode-squeezed-vacuum state with equal squeezing strength. We then analyze the limiting behaviors when the squeezing is small and large. Having determined the averages, we then explicitly calculate the Rényi- α variance for integers α > 1 and are able to show that these entropies are weakly typical. Published by the American Physical Society 2025

Youm, Jason (ORCID:0009000057597782)↗
DOE OSTI2025

Survey-wide asteroid discovery with a high-performance computing enabled non-linear digital tracking framework

Modern astronomical surveys detect asteroids by linking together their appearances across multiple images taken over time. This approach faces limitations in detecting faint asteroids and handling the computational complexity of trajectory linking. Here, we present a novel method that adapts “digital tracking” – traditionally used for short-term linear asteroid motion across images – to work with large-scale synoptic surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time (Rubin/LSST). Our approach combines hundreds of sparse observations of individual asteroids across their non-linear orbital paths to enhance detection sensitivity by several magnitudes. To address the computational challenges of processing massive data sets and dense orbital phase spaces, we developed a specialized high-performance computing architecture. We demonstrate the effectiveness of our method through experiments that take advantage of the extensive computational resources at Lawrence Livermore National Laboratory. This work enables the detection of significantly fainter asteroids in existing and future survey data, potentially increasing the observable asteroid population by orders of magnitude across different orbital families, from near-Earth objects (NEOs) to Kuiper belt objects (KBOs).

Asteroid discovery↗
DOE OSTI2025

Efficient Streaming Dynamic Mode Decomposition

We propose a reformulation of the streaming dynamic mode decomposition method that requires maintaining a single orthonormal basis, thereby reducing computational redundancy. The proposed efficient streaming dynamic mode decomposition method results in a constant-factor reduction in computational complexity and memory storage requirements. Numerical experiments on representative canonical dynamical systems show that the enhanced computational efficiency does not compromise the accuracy of the proposed method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Antiviral discovery using sparse datasets by integrating experiments, molecular simulations, and machine learning

Computational methods have demonstrated success in identifying virucidal agents, effectively contributing to the discovery of novel virucidal molecules. In this study, we developed a machine learning (ML) model, trained on a small dataset, to predict inhibitors of human enterovirus 71 (EV71), a pathological agent that causes severe disease in children and immunocompromised adults. Despite the dataset’s limitation, comprising of only 36 compounds tested, our ML framework demonstrated significant predictive capability. Notably, experimental validation revealed that five out of the eight compounds predicted by our model from the Chinese cosmetic material list exhibited virucidal activity. The inhibitor effects displayed by the main active compounds were further confirmed by molecular dynamics simulation. This underscores the potential of our AI-driven approach to bypass data constraints in identifying active molecules against viral pathogens.

60 APPLIED LIFE SCIENCES↗