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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 55 records · Page 3

G4CMP: Condensed matter physics simulation using the G$\scriptsize{\mathrm{EANT}}$4 toolkit

G4CMP simulates phonon and charge transport in cryogenic semiconductor crystals using the Geant4 toolkit. The transport code is capable of simulating the propagation of acoustic phonons as well as electron and hole charge carriers. Herein processes for anisotropic phonon propagation, oblique charge-carrier propagation, and phonon emission by accelerated charge carriers are included. The simulation reproduces theoretical predictions and experimental observations such as phonon caustics, heat-pulse propagation times, and mean charge-carrier drift velocities. In addition to presenting the physics and features supported by G4CMP, this report outlines example applications from the dark matter and quantum information science communities. These communities are applying G4CMP to model and design devices for which the energy transported by phonons and charge carriers is germane to the performance of superconducting instruments and circuits placed on silicon and germanium substrates. The G4CMP package is available to download from GitHub: github.com/kelseymh/G4CMP.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Metallaphotoredox: The Merger of Photoredox and Transition Metal Catalysis

The merger of photoredox catalysis with transition metal catalysis, termed metallaphotoredox catalysis, has become a mainstay in synthetic methodology over the past decade. Metallaphotoredox catalysis has combined the unparalleled capacity of transition metal catalysis for bond formation with the broad utility of photoinduced electron- and energy-transfer processes. Photocatalytic substrate activation has allowed the engagement of simple starting materials in metal-mediated bond-forming processes. Moreover, electron or energy transfer directly with key organometallic intermediates has provided novel activation modes entirely complementary to traditional catalytic platforms. Finally, this Review details and contextualizes the advancements in molecule construction brought forth by metallaphotocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Growth rate as a link between microbial diversity and soil biogeochemistry

The growth rate of a microorganism is a simple yet profound way to quantify its impact on the world. The absolute growth rate of a microbial population reflects rates of resource assimilation, biomass production, and element transformation, some of the many ways that organisms affect Earth’s ecosystems and climate. Microbial fitness in the environment depends on the ability to reproduce quickly when conditions are favorable and adopt a survival physiology when conditions worsen, which cells coordinate by adjusting their relative growth rate. At the population level, relative growth rate is a sensitive metric of fitness, linking survival and reproduction to the ecology and evolution of populations. Techniques combining ‘omics and stable isotope probing enable sensitive measurements of growth rates of microbial assemblages and individual taxa in soil. Microbial ecologists can explore how the growth rates of taxa with known traits and evolutionary histories respond to changes in resource availability, environmental conditions, and interactions with other organisms. We anticipate that quantitative and scalable data on the growth rates of soil microorganisms, coupled with measurements of biogeochemical fluxes, will allow scientists to test and refine ecological theory and advance process-based models of carbon flux, nutrient uptake, and ecosystem productivity. Finally, measurements of in situ microbial growth rates provide insights into the ecology of populations and can be used to quantitatively link microbial diversity to soil biogeochemistry.

54 ENVIRONMENTAL SCIENCES↗

Limited cross-variant immunity from SARS-CoV-2 Omicron without vaccination

SARS-CoV-2 Delta and Omicron are globally relevant variants of concern. Although individuals infected with Delta are at risk of developing severe lung disease, infection with Omicron often causes milder symptoms, especially in vaccinated individuals. The question arises of whether widespread Omicron infections could lead to future cross-variant protection, accelerating the end of the pandemic. Here we show that without vaccination, infection with Omicron induces a limited humoral immune response in mice and humans. Sera from mice overexpressing the human ACE2 receptor and infected with Omicron neutralize only Omicron, but not other variants of concern, whereas broader cross-variant neutralization was observed after WA1 and Delta infections. Unlike WA1 and Delta, Omicron replicates to low levels in the lungs and brains of infected animals, leading to mild disease with reduced expression of pro-inflammatory cytokines and diminished activation of lung-resident T cells. Sera from individuals who were unvaccinated and infected with Omicron show the same limited neutralization of only Omicron itself. By contrast, Omicron breakthrough infections induce overall higher neutralization titres against all variants of concern. Our results demonstrate that Omicron infection enhances pre-existing immunity elicited by vaccines but, on its own, may not confer broad protection against non-Omicron variants in unvaccinated individuals.

60 APPLIED LIFE SCIENCES↗

A robust benchmark for detection of germline large deletions and insertions

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution and comprehensiveness. To help translate these methods to routine research and clinical practice, we developed a sequence-resolved benchmark set for identification of both false-negative and false-positive germline large insertions and deletions. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle Consortium integrated 19 sequence-resolved variant calling methods from diverse technologies. The final benchmark set contains 12,745 isolated, sequence-resolved insertion (7,281) and deletion (5,464) calls ≥50 base pairs (bp). The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.51 Gbp and 5,262 insertions and 4,095 deletions supported by ≥1 diploid assembly. We demonstrate that the benchmark set reliably identifies false negatives and false positives in high-quality SV callsets from short-, linked- and long-read sequencing and optical mapping.

59 BASIC BIOLOGICAL SCIENCES↗

Automated Resonance Fitting for Nuclear Data Evaluation

Global and national efforts to deliver high-quality nuclear data to users have a wide-ranging impact, affecting applications in national security, reactor operations, basic science, medicine, and more. Cross section evaluation is a major part of this effort, combining theory and experimentation to produce recommended values and uncertainties for reaction probabilities. Resonance region evaluation is a specialized type of nuclear data evaluation that can require significant manual effort and months of time from expert scientists. In this article, non-convex non-linear optimization methods are combined with concepts of inferential statistics to infer a resonance model from experimental data in an automated manner that is not dependent on prior evaluation(s). This methodology aims to enhance the workflow of a resonance evaluator by minimizing time, effort, and the potential for bias from prior assumptions, while enhancing reproducibility and documentation, thereby addressing well-known challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quantum optimal control of superconducting qubits based on machine-learning characterization

Implementing fast and high-fidelity quantum operations using open-loop quantum optimal control relies on having an accurate model of the quantum dynamics. Any deviations between this model and the complete dynamics of the device, such as the presence of spurious modes or pulse distortions, can degrade the performance of optimal controls in practice. Here, we propose an experimentally simple approach to realize optimal quantum controls tailored to the device parameters and environment while specifically characterizing this quantum system. Concretely, we use physics-inspired machine learning to infer an accurate model of the dynamics from experimentally available data and then optimize our experimental controls on this trained model. We show the power and feasibility of this approach by optimizing arbitrary single-qubit operations in detailed numerical simulations of a superconducting transmon qubit. Furthermore, we demonstrate that this framework produces an accurate description of the device dynamics under arbitrary controls, together with the precise pulses achieving arbitrary single-qubit gates with a high fidelity of ∼99.99%.

Artificial neural networks↗

Broadband Solenoidal Haloscope for Terahertz Axion Detection

We introduce the Broadband Reflector Experiment for Axion Detection (BREAD) conceptual design and science program. This haloscope plans to search for bosonic dark matter across the [ 10 - 3 , 1 ] eV ([0.24, 240] THz) mass range. BREAD proposes a cylindrical metal barrel to convert dark matter into photons, which a novel parabolic reflector design focuses onto a photosensor. This unique geometry enables enclosure in standard cryostats and high-field solenoids, overcoming limitations of current dish antennas. A pilot 0.7 m 2 barrel experiment planned at Fermilab is projected to surpass existing dark photon coupling constraints by over a decade with one-day runtime. Axion sensitivity requires < 10 - 20 W / Hz sensor noise equivalent power with a 10 T solenoid and 10 m 2 barrel. We project BREAD sensitivity for various sensor technologies and discuss future prospects.

Liu, Jesse↗

Compatibility of Medium Density Polyethylene (MDPE) for Distribution of Gaseous Hydrogen

Hydrogen has emerged as a convenient energy storage medium and is being considered as an alternative for reducing the use of carbon-based fuels. Numerous projects are looking into distributing blends of natural gas and different amounts of gaseous hydrogen through the existing natural gas distribution system, which is widely composed of medium density polyethylene (MDPE) line pipes. The mechanical behavior of MDPE with hydrogen is not well understood; therefore, the effect of gaseous hydrogen on the mechanical properties of MDPE needs to be examined. In the current study, we investigate the effects of gaseous hydrogen on fatigue crack growth rate, fracture resistance, and fatigue life of MDPE in the presence of 3.4 MPa gaseous hydrogen. Fatigue crack growth behavior and fracture resistance are measured using compact tension specimens, while the fatigue life tests are carried out using circumferential notched tensile specimens. In addition, fatigue and fracture tests were conducted in air to determine the baseline properties of MDPE, which was then compared with the ones observed in gaseous hydrogen environment. After the completion of mechanical testing, fracture surfaces are also analyzed using optical and scanning electron microscopes to understand salient fracture features of MDPE with and without the presence of gaseous hydrogen.

Shrestha, Rakish↗

A Grassroots Network and Community Roadmap for Interconnected Autonomous Science Laboratories for Accelerated Discovery

Scientific discovery is being revolutionized by AI and autonomous systems, yet current autonomous laboratories remain isolated islands unable to collaborate across institutions. We present the Autonomous Interconnected Science Lab Ecosystem (AISLE), a grassroots network transforming fragmented capabilities into a unified system that shorten the path from ideation to innovation to impact and accelerates discovery from decades to months. AISLE addresses five critical dimensions: (1) cross-institutional equipment orchestration, (2) intelligent data management with FAIR compliance, (3) AI-agent driven orchestration grounded in scientific principles, (4) interoperable agent communication interfaces, and (5) AI/ML-integrated scientific education. By connecting autonomous agents across institutional boundaries, autonomous science can unlock research spaces inaccessible to traditional approaches while democratizing cutting-edge technologies. This paradigm shift toward collaborative autonomous science promises breakthroughs in sustainable energy, materials development, and public health.

Ferreira da Silva, Rafael [Oak Ridge National Labo↗

Distributed heterogeneous compute infrastructure for the study of additive manufacturing systems

We present the current status of a large-scale computing framework to address the need of the multidisciplinary effort to study chemical dynamics. Specifically, we are enabling scientists to process and store experimental data, run large-scale computationally expensive high-fidelity physical simulation, and analyze these results using the state-of-the-art data analytics tools, machine learning, and uncertainty quantification methods using heterogeneous computing resources, such as CPU and GPU cluster. The framework can integrate or abstract out multiple domains based on roles. In order to develop this framework, we have leveraged an existing framework coupled with in-house heterogeneous computing resources. We present the results of using this framework on a single metadata triggered workflow to accelerate an additive manufacturing use case.

heterogeneous computing, hpc, workflows, reproduci↗

Evidence for carbon dioxide removal via enhanced rock weathering with steel slag, though not basalt, in a midwestern U.S. field trial

Enhanced weathering is an emergent pathway for permanent atmospheric carbon dioxide removal (CDR). However, despite a dramatic increase in academic and commercial research, there remain relatively few published examples of field evidence demonstrating the effectiveness of enhanced weathering. Here, we present results from a three-year field trial that evaluated steel slag and crushed basalt applied as amendments in a conventional agricultural system in the Midwestern United States. Steel slag applied to initially acidic soil increased porewater pH and alkalinity and increased soil pH and Ca-saturation. Together, changes in porewater chemistry and soil properties provide strong evidence for steel slag weathering and CDR. However, steel slag applied to soils with a neutral initial pH did not generate significant changes in soil or porewater chemistry. In addition, coarse-grained crushed basalt did not generate significant change in any of the soils. Strong acid effects were apparent in all 3 years of monitoring soil porewater chemistry. Overall, our results demonstrate clear evidence of CDR from applying steel slag amendments to acidic cropland soils while also highlighting the difficulty of greenhouse gas reduction accounting from enhanced weathering and the variable outcomes that can occur depending on feedstock and soil type.

Geosciences↗