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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

SISGR: The regulation of carbon fixation in plant and green algae: Rubisco activase and the origin of heat inactivation of CO 2 assimilation

Rubisco activase (Rca) is a critical AAA+ ATPase protein complex that remodels and promotes the Rubisco enzyme, a key player in photosynthetic performance and carbon fixation. The assembly and function of the Rca protein complex are regulated by a range of factors, including subunit concentration, nucleotide-binding states, thermal conditions, metal-ion coordination, and post-translational modifications, such as phosphorylation. Despite its importance in photosynthesis, the detailed molecular mechanisms underlying the regulation of plant Rca and how it activates Rubisco remain elusive. This project aims to bridge this knowledge gap by integrating sophisticated enzymology tools with single-molecule methods and high-resolution electron microscopy to elucidate the structure and function of plant Rca. Through these multiple approaches, we have systematically investigated how the activity of plant Rca is impacted by various factors, such as phosphorylation and metal-ion coordination. The Rca complex assembly/disassembly dynamics were captured using anti-Brownian electrokinetic (ABEL) trap-based measurements, providing unprecedented insight into its structural flexibility and diverse assembly states. Furthermore, the structural analysis of Rca through electron crystallography and single-particle cryogenic electron microscopy (cryo-EM) reveals novel assembly states of the spinach Rca, providing insight into the mechanistic action for Rubisco remodeling. By combining cutting-edge tools and approaches, this work uncovers critical aspects of Rca’s regulation and assembly, paving the way for a deeper understanding of its role in photosynthetic efficiency and the potential for enhancing carbon fixation in crops.

59 BASIC BIOLOGICAL SCIENCES↗

A Markov chain Monte Carlo (MCMC) Bayesian inference approach to analyze apparent activation barriers and reaction orders from microreactor data

Statistical analysis of steady-state catalytic kinetic data is often limited by data sparsity due to the slow pace at which the data is collected. Data sparsity and limitations in statistical analysis make it difficult to differentiate between mechanistic models and catalytic sites. A Bayesian inference tool is reported for catalysis researchers to estimate error in the determination of reaction orders from steady state microreactor data. The benefits of a Bayesian inference approach are discussed, as an alternative to the more common frequentist approach. The approach incorporates prior knowledge of the system and the data collected to form an error estimate on reaction orders. We investigated the effects of three distinct data treatments—individual fitting of trials, pooled analysis, and constrained regression methods—on the precision and uncertainty of reaction order determinations. To assess the robustness of our findings, we conducted sensitivity analyses to evaluate the influence of Bayesian parameters on uncertainty estimation. Additionally, we utilized synthetic data to illustrate how data quality impacts the precision of uncertainty assessments. We show Bayesian analysis can obtain a more precise estimation of error with a sparse data set than a frequentist analysis. Finally, this work provides strong evidence that the adoption of Bayesian analysis of kinetic data may help researchers make more precise arguments as to the strength of their evidence for a particular mechanistic hypothesis, or in comparing across different catalysts.

42 ENGINEERING↗

Life Cycle Analysis of Natural Gas Supply Chain and End Use Applications in the United States

Natural gas (NG) plays a crucial role in current and future energy systems in the United States due to its abundance and affordability. In this study a life cycle analysis of the NG supply chain in the United States was conducted using Argonne's R&D GREET model, examining stages from recovery to distribution using reported field data processed and documented by National Energy Technology Laboratory. Supply chain emissions were evaluated across multiple spatial scales, including national average, overall regional production, region-to-region, and basin-to-region scenarios. The GHG intensity of the U.S. average NG supply chain was estimated at 10.3 kg CO 2 e/MMBtu (lower heating value), with a range across regions from 7.8 kg CO 2 e/MMBtu (Northeast) to 15.1 kg CO 2 e/MMBtu (Pacific). The analysis further assessed how upstream NG emissions influence the life cycle GHG emissions of key end-use applications, including electricity generation (0.044–0.086 kg CO 2 e/kWh from upstream NG in combined cycle facilities), hydrogen production (1.04–2.20 kg CO 2 e/kg H 2 for steam methane reforming [SMR] and 1.06–2.23 kg CO 2 e/kg for autothermal reforming [ATR]), and transit bus operation utilizing compressed natural gas fuel (0.19–0.37 kg CO 2 e/mile) and hydrogen fuel (0.12–0.25 kg CO 2 e/mile for hydrogen produced in SMR and ATR).

compression↗

Nuclear Data Management and Analysis System Plan

The United States Department of Energy Advanced Reactor Technologies Program was formed in Fiscal Year 2015 and encompasses the Next Generation Nuclear Plant Project and Very High Temperature Reactor (VHTR) Program as they were known previously. The VHTR Program was created to support design and licensing of the first VHTR nuclear plant. Data created for and used by the program must be qualified for use, stored in a readily accessible electronic form, categorized to assure the correct data are used, and controlled to prevent data corruption or inadvertent changes. The Nuclear Data Management and Analysis System was designed to support the data needs of the VHTR Program, at the time and now the Advanced Reactor Technologies Program. Since its inception, use of the Nuclear Data Management and Analysis System has expanded to support additional projects and programs with similar requirements for control, analysis, and availability of large data sets.

99 GENERAL AND MISCELLANEOUS↗

Dynamic mode decomposition of nonequilibrium electron-phonon dynamics: accelerating the first-principles real-time Boltzmann equation

Abstract Nonequilibrium dynamics governed by electron–phonon ( e -ph) interactions plays a key role in electronic devices and spectroscopies and is central to understanding electronic excitations in materials. The real-time Boltzmann transport equation (rt-BTE) with collision processes computed from first principles can describe the coupled dynamics of electrons and atomic vibrations (phonons). Yet, a bottleneck of these simulations is the calculation of e –ph scattering integrals on dense momentum grids at each time step. Here we show a data-driven approach based on dynamic mode decomposition (DMD) that can accelerate the time propagation of the rt-BTE and identify dominant electronic processes. We apply this approach to two case studies, high-field charge transport and ultrafast excited electron relaxation. In both cases, simulating only a short time window of ~10% of the dynamics suffices to predict the dynamics from initial excitation to steady state using DMD extrapolation. Analysis of the momentum-space modes extracted from DMD sheds light on the microscopic mechanisms governing electron relaxation to a steady state or equilibrium. The combination of accuracy and efficiency makes our DMD-based method a valuable tool for investigating ultrafast dynamics in a wide range of materials.

36 MATERIALS SCIENCE↗

Genomic Surveillance Detection of SARS-CoV-1–Like Viruses in Rhinolophidae Bats, Bandarban Region, Bangladesh

We sequenced sarbecovirus from Rhinolophus spp. bats in Bandarban District, Bangladesh, in a genomic surveillance campaign during 2022–2023. Sequences shared identity with SARS-CoV-1 Tor2, which caused an outbreak of human illnesses in 2003. Describing the genetic diversity and zoonotic potential of reservoir pathogens can aid in identifying sources of future spillovers.

Angiotensin Converting Enzyme 2↗

Spin-State and Reorganization Energy Considerations for Metal-Centered Photoredox Catalysis

Transition-metal complexes featuring metal-centered excited states have recently emerged as mechanistically distinct platforms for selective photochemistry, including photoredox catalysis. Among these, Co(III) complexes have demonstrated productive photoinduced electron transfer via the 3 T 1 metal-centered state. In contrast, photoreactivity from the 5 T 2 metal-centered state in Fe(II) polypyridyl complexes remains limited. Building on our prior report concerning reactivity associated with the 5 T 2 state in [Fe(tren(py) 3 )] 2+ (tren(py) 3 = tris(2-pyridylmethyliminoethyl)-amine), we introduced stronger-field ligands in an effort to increase excited-state energies of Fe(II) polypyridyl complexes and enhance reactivity. Despite achieving nanosecond-scale excited-state lifetimes and favorable thermodynamic driving forces, no photoreactivity was observed. Reinvestigation of the observations previously reported for [Fe(tren(py) 3 )] 2+ revealed interactions between the metal complex and the substrate in their respective ground states that mimicked dynamic quenching of the chromophore, prompting a reassessment of mechanistic considerations inherent in leveraging reductive chemistry from the 5 T 2 excited state of Fe(II). Our analysis indicates that electron transfer from the 5 T 2 excited state of a low-spin d6 metal is subject to significant barriers both in terms of reorganization energies and spin conservation that undermines its ability to act as an electron donor for photoredox catalysis. In contrast, ligand fields that are sufficient to stabilize the 3 T 1 excited state have available to them numerous spin-allowed and, in certain cases, near-barrierless pathways to engage in excited-state electron transfer (both oxidative and reductive depending on the identity of the metal). These results highlight the critical role of spin-state changes and their associated reorganization energy requirements in metal-centered photoredox catalysis.

charge transfer↗

Life-cycle analysis of offshore macroalgae production systems in the United States

Offshore macroalgae production offers the potential to provide valuable biomass for food, energy, and higher value products without the use of land or freshwater while using excess nutrients and carbon dioxide. To realize this potential, the Macroalgae Research Inspiring Novel Energy Resources program of the Advanced Research Projects Agency-Energy has initiated projects to develop advanced cultivation technologies that enable the cost- and energy-efficient production of macroalgal biomass. Here, this study addresses the life-cycle greenhouse gas emissions and energy return on investment for five U.S. offshore macroalgae production systems designed for deployment at the thousand-hectare scale using a detailed module developed within the GREET life-cycle analysis model for this study. The carbon intensity of macroalgae production system designs, expressed as kg of carbon dioxide equivalent per dry metric ton of algae harvested, vary widely from 49 to 220 and confirm that biomass productivity has the highest degree of sensitivity across the model parameters tested. Regardless of the system designs, the upstream and combustion emissions from fuel use are the key contributor (over 45 %) to carbon intensity, indicating that the use of low-carbon fuels (e.g., renewable diesel) could further reduce greenhouse gas emissions. Further studies need to specify the market opportunity and specific product slates for macroalgae to provide a complete picture of the environmental impacts of macroalgal feedstock.

59 BASIC BIOLOGICAL SCIENCES↗

Powered by dGen Webinar [Slides]

NLR's Powered By Webinar Series featuring NLR's dGen Modeling Tool. The Distributed Generation Market Demand (dGenTM) model simulates customer adoption of distributed energy resources for residential, commercial, and industrial entities in the United States or other countries through 2050. The model enables analysis at multiple geographic levels (national, state, and utility, or below) and offers sophistication in representation of decision-making regarding economic and behavioral considerations. Analysts have used dGen to answer questions about load forecasting and integrated resource planning, policy analysis, locational value of distributed energy resources, and more. dGen is open source, and various energy organizations - including independent system operators, regional transmission organizations, and the California Energy Commission - use the model internally.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A molecular ground electronic state with an occupied 5g spinor—The superheavy (E125)F molecule

Fully relativistic calculations, primarily at the 4-component coupled-cluster singles and doubles with perturbative triples [CCSD(T)] level of theory with the Dirac–Coulomb (DC) Hamiltonian, have been carried out for the superheavy (E125)F molecule using large Gaussian basis sets. The electronic ground state is determined to have an [Og]8s 2 5g 1 6f 3 configuration on E125 with an Ω = 6 ground state and an 8p electron largely donated to F. A Mulliken population analysis indicates that the ground state is mainly ionic with a partial charge of +0.79 on E125 and a single sigma bond involving the F 2p and E125 8p spinors. The occupied g spinor is not involved in the bonding. With the largest basis set used in this work, the (0 K) dissociation energy was calculated at the DC-CCSD(T) level of theory to be 7.02 eV. Analogous calculations were also carried out for the E125 atom, both the neutral and its cation. The lowest energy electron configuration of E125 + , [Og]$8s$$^{2}_{1/2}$$5g$$^{1}_{7/2}$$6f$$^{3}_{5/2}$ with a J = 6 ground state, was found to be similar to that in (E125)F, while the neutral E125 atom has an [Og]$8s$$^{2}_{1/2}$$5g$$^{1}_{7/2}$$6f$$^{2}_{5/2}$$7d$$^{1}_{3/2}$$8p$$^{1}_{1/2}$ ground state electron configuration with a J = 17/2 ground state. The ionization energy (IE) of E125 is reported for the first time and is calculated to be 4.70 eV at the DC-CCSD(T) level of theory. Non-relativistic calculations were also carried out on the E125 atom and the (E125)F molecule. Here, the non-relativistic ground state of the E125 atom was calculated to have a 5g 5 ground state with an IE of just 3.4 eV. The net effect of relativity on (E125)F is to stabilize its bonding.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Theorems in Service of Sound Composition, Rapid Modeling and Scalable Analysis

This project extends the state of the art in formal verification modeling with modules and automatically checkable data-sharing patterns such that component modules can retain their assurance case when composed within a larger system. For users, smaller models make reasoning easier and help to ensure they accurately reflect text specifications. For automated methods, smaller models give exponential benefits for verification algorithm execution time.

97 MATHEMATICS AND COMPUTING↗

Cataloging US state policy patterns towards microgrid deployment

Frequent extreme weather events have called for rigorous and timely efforts for alternative non-wire solutions. These efforts are getting more widespread to offer a perfect alternative as the conventional grid becomes progressively less resilient. One of these solutions is microgrids that can disconnect from the grid and offer grid resilience during an outage. While this technology is still finding its footing in the industry, states across the US are employing policy patterns and forms of instruments to support its deployment. This study includes a systemic review of the US by conducting a binary analysis of all 50 states (including Washington D.C, excluding other US territories) using seven variables. The results show four major policy approaches to microgrids: i) supporting microgrids through a definitive legislative activity leading to further policy action; ii) direct efforts from the public utilities commissions without a concrete legislative push; iii) initiatives from institutions other than the commissions; and lastly, iv) self-initiated community and private consumer efforts. The results help understand what policy instruments are being used in each of these patterns to support this niche technology that still faces regulatory challenges.

Furqan, Maham↗

Hydride Migration within RhH 2 Ag 19 Superatom: A Combined Neutron Diffraction and DFT Analysis

Abstract An investigation combining neutron diffraction and DFT allows determining the most likely hydride migration pathway within the icosahedral metal framework of [RhH 2 Ag 19 {S 2 P(O n Pr) 2 } 12 ] (RhH 2 Ag 19 ). Starting from the experimentally derived solid‐state structures, a computational analysis is able to reveal an energetically favorable migration pathway with a maximum energy barrier of 4.2 kcal mol −1 . The two hydrides migrate simultaneously within the Rh@Ag 12 icosahedral core, traversing several positional isomers. This study expands the understanding of hydride dynamics in nanoclusters and provides critical insights into the structural flexibility of the superatom framework. These findings have significant implications for hydrogen storage, catalysis, and the design of advanced hydride‐containing materials.

Chemistry↗

Operational Analytics Studies for ATLAS Distributed Computing: Data Popularity Forecast and Utilization of the WLCG Centers

Operational analytics is the direction of research related to the analysis of the current state of computing processes and the prediction of future states in order to anticipate imbalances and take timely measures to stabilize a complex system. There are two relevant areas in ATLAS Distributed Computing that are currently the focus of studies: user physics analysis including the forecast of popularity of data samples among users, and evaluating WLCG centers for their readiness to process user analysis payloads. Studying these areas is challenging due to the complexity involved, as it requires a comprehensive understanding of numerous boundary conditions typically found in large-scale distributed computing infrastructures. Forecasts of data popularity are problematic without the categorization of user tasks by their types (data transformation or physics analysis), which do not always appear on the surface but may induce noise, which introduces significant distortions for predictive analysis. Evaluating the WLCG resources by their analysis workloads is also a challenging task as it is necessary to find a balance between the workload of the resource, its performance, the waiting time for jobs on it, as well as the volume of jobs that it processes. This is especially difficult in a heterogeneous computing environment, where legacy resources are used along with modern high-performance machines. We will look at these areas of research in detail and discuss what tools and methods are used in our work, demonstrating results already obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of the Higgs boson production in association with top quarks in multilepton final states in pp collisions at s=13 TeV with the ATLAS detector

A measurement of the associated production of a top-quark pair with the Higgs boson (tt¯H$$ t\overline{t}H $$) in multilepton final states is presented. The analysis is based on a data sample of proton-proton collisions at s=13$$ \sqrt{s}=13 $$ TeV recorded with the ATLAS detector at the CERN Large Hadron Collider and corresponding to an integrated luminosity of 140 fb−1. Six final states defined by the number and flavour of reconstructed charged leptons are combined in a simultaneous likelihood fit to extract the tt¯H$$ t\overline{t}H $$ signal and constrain the most relevant backgrounds. The measured tt¯H$$ t\overline{t}H $$ cross-section normalised to Standard Model (SM) prediction is σtt¯H/σSM=0.63−0.19+0.20$$ {\sigma}_{t\overline{t}H}/{\sigma}^{\mathrm{SM}}=0.{63}_{-0.19}^{+0.20} $$. This result corresponds to an observed (expected) significance of 3.3σ (5.3σ). Additionally, two other fits are used to measure the tt¯H$$ t\overline{t}H $$ cross-section differentially in bins of the Higgs boson transverse momentum in the simplified template cross-section framework, and to extract the associated production cross-section of a single top-quark with the Higgs boson (tH) together with the tt¯H$$ t\overline{t}H $$ one. The CP structure of the top quark-Higgs boson Yukawa coupling is probed through an analysis of tt¯H$$ t\overline{t}H $$ and tH events. The results are compatible with the SM hypothesis, and values of the mixing angle between CP-even and CP-odd top-Higgs Yukawa couplings of |α| > 62° are excluded at 68% confidence level.

Aad, G↗

Standard Analysis Report INV-SAR-81, Revision 0 Chemical and Cement Components 2023 Inventory Estimates for the Interim State Performance Assessment of the Waste Isolation Pilot Plant

This standard analysis report provides the estimates for the chemical (oxyanions and complexing agents) and cement components with a data collection cut-off date of December 31, 2023. These estimates will be included in a Performance Assessment Inventory Report developed for the U.S. Department of Energy (DOE) interim state repository configuration performance assessment (PA) for the 2026 Compliance Recertification Application (CRA).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Life Cycle Analysis of Growing Canola for Biofuel Production in the United States

This study quantifies and compares the life cycle greenhouse gas (GHG) emissions of renewable diesel (RD), sustainable aviation fuel (SAF), and biodiesel (BD) produced from two U.S. canola production systems: 1) emerging intermediate winter canola, typically grown in double- or relay-cropping systems between the growing seasons of main crops, and 2) main canola, mostly spring canola but also including winter canola, which are grown as primary crops occupying the field for a full growing season. Using the Research and Development version of the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) model and the most up-to-date life cycle inventory data─field trial data for intermediate winter canola (>37,000 acres) and recent national survey data for spring canola─this life cycle analysis (LCA) estimates the direct emissions from canola cultivation and harvest, the conversion of canola into fuels, fuel transportation, and combustion. In addition, we account for market-mediated emissions associated with a scenario of 0.5 billion gallons per year of spring canola-based biofuels, including induced land use change (ILUC), induced other crop (nonfeedstock) production changes, and induced livestock production changes. For intermediate winter canola, these market-mediated effects were not modeled, as ILUC is expected to be negligible due to its integration into existing rotations, and data are currently insufficient to reliably quantify other market-mediated changes. The estimated life cycle direct emissions of RD/SAF derived from intermediate winter canola and main spring canola are about 32 and 33 g of CO2-equivalent per megajoule of fuel (g CO 2 e/MJ), respectively. Corresponding emissions for BD from intermediate winter canola and main spring canola are about 30 and 31 g of CO 2 e/MJ, respectively. Farming is the dominant emissions source for both canola systems, with intermediate winter canola and main spring canola emitting about 19 and 20 g of CO 2 e/MJ, respectively. ILUC and other induced changes increase emissions of main spring canola-derived RD/SAF and BD by about 18 and 17 g of CO 2 e/MJ, respectively. These results indicate that the GHG emissions of biofuels produced from the two canola systems may differ substantially due to the different land use dynamics of the systems.

biodiesel↗

An Analysis of Future Wind Energy Resources and Cost Uncertainties Across the United States

Wind power is a growing source of energy generation that relies on complex global atmospheric and earth system processes. There has been evidence of reductions in average wind speeds over land in North America since the 1980s, and several models project that average wind speeds will continue to decrease. Concurrently, the cost of wind energy systems in the United States has been decreasing since around 2010, a trend also projected to continue. There is considerable uncertainty in these future projections, with quantitative estimates of future wind resource and system costs varying widely. To study this, we run wind energy models with possible future system costs, turbine designs, and meteorological inputs from multiple downscaled earth system models over the contiguous United States. Changes in mean annual energy production from 2000-2019 to 2040-2059 can be as high as +10% in South Texas or as low as -20% in Iowa. Larger turbines and moderate reductions in system costs can offset the largest projected decreases in wind resource, but much uncertainty remains in the extent to which wind resources will change and to what extent system costs can be reduced. An analysis of variance shows, in several states in the Midwest, uncertainty in future wind resources can influence the cost of wind energy nearly as much as uncertainty in future system costs.

17 WIND ENERGY↗