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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Enhancement of STAYSL_PNNL with IRDFF/V1.05 to 60 MeV

The STAYSL PNNL program performs a least-squares adjustment of the neutron spectrum based on the IRDFF cross section library and user-defined activation data and a starting neutron spectrum. All known covariances are included. Required corrections are included for the irradiation history, gamma absorption, neutron burn-up, and neutron self-shielding using separate utility programs prior to the execution of STAYSL PNNL. Several new neutron cross section libraries based on IRDFF V1.05 to 60 MeV are provided with the program including energy group structures of 69 (WIMS), 129 (14 MeV), 140 (prior 100 groups extended to 60 MeV), 175 (Vitamin J), 640 (old SANDII to 20 MeV), and 725 (old Sand II extended to 60 MeV) energy groups. Twelve new reactions were included in IRDFF V1.05. At higher neutron energies, calculations demonstrate the need for activation cross sections from natural targets such as Ti(n,x)46Sc rather than only isotopic targets such as 46Ti(n,p)46Sc and 47Ti(n,x)46Sc. The effects of such reactions increase dramatically with increasing neutron energies and cannot be neglected. Some critical reactions such as 56Fe(n,x)54Mn are not currently included in IRDFF and prevent the use of the 54Fe(n,p)54Mn reaction at higher neutron energies. It is recommended that natural element cross sections be included in future releases of IRDFF for a list of reactions that suffer from reactions on multiple isotopes that lead to the same activation product. Spectral adjustments are illustrated in Be(d,n) thick target neutron fields at deuteron energies of 30 and 40 MeV.

reactor dosimetry, neutron spectral adjustment↗
DOE OSTI2016

Association Between Anticholinergic Medication Use and Cognition, Brain Metabolism, and Brain Atrophy in Cognitively Normal Older Adults

Importance of this Paper: The use of anticholinergic (AC) medication is linked to cognitive impairment and an increased risk of dementia. To our knowledge, this is the first study to investigate the association between AC medication use and neuroimaging biomarkers of brain metabolism and atrophy as a proxy for understanding the underlying biology of the clinical effects of AC medications. Objective: To assess the association between AC medication use and cognition, glucose metabolism, and brain atrophy in cognitively normal older adults from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Indiana Memory and Aging Study (IMAS). Design, Setting, and Participants: The ADNI and IMAS are longitudinal studies with cognitive, neuroimaging, and other data collected at regular intervals in clinical and academic research settings. For the participants in the ADNI, visits are repeated 3, 6, and 12 months after the baseline visit and then annually. For the participants in the IMAS, visits are repeated every 18 months after the baseline visit (402 cognitively normal older adults in the ADNI and 49 cognitively normal older adults in the IMAS were included in the present analysis). Participants were either taking (hereafter referred to as the AC + participants [52 from the ADNI and 8 from the IMAS]) or not taking (hereafter referred to as the AC - participants [350 from the ADNI and 41 from the IMAS]) at least 1 medication with medium or high AC activity. Data analysis for this study was performed in November 2015. Main Outcomes and Measures: Cognitive scores, mean fludeoxyglucose F 18 standardized uptake value ratio (participants from the ADNI only), and brain atrophy measures from structural magnetic resonance imaging were compared between AC + participants and AC - participants after adjusting for potential confounders. The total AC burden score was calculated and was related to target measures. The association of AC use and longitudinal clinical decline (mean [SD] follow-up period, 32.1 [24.7] months [range, 6-108 months]) was examined using Cox regression. Results: The 52 AC + participants (mean [SD] age, 73.3 [6.6] years) from the ADNI showed lower mean scores on Weschler Memory Scale–Revised Logical Memory Immediate Recall (raw mean scores: 13.27 for AC + participants and 14.16 for AC - participants; P = .04) and the Trail Making Test Part B (raw mean scores: 97.85 seconds for AC + participants and 82.61 seconds for AC - participants; P = .04) and a lower executive function composite score (raw mean scores: 0.58 for AC + participants and 0.78 for AC - participants; P = .04) than the 350 AC - participants (mean [SD] age, 73.3 [5.8] years) from the ADNI. Reduced total cortical volume and temporal lobe cortical thickness and greater lateral ventricle and inferior lateral ventricle volumes were seen in the AC + participants relative to the AC - participants. Conclusions and Relevance of this Paper: The use of AC medication was associated with increased brain atrophy and dysfunction and clinical decline. Thus and finally, use of AC medication among older adults should likely be discouraged if alternative therapies are available.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Computational approaches to detect allosteric pathways in transmembrane molecular machines

Many of the functions of transmembrane proteins involved in signal processing and transduction across the cell membrane are determined by allosteric couplings that propagate the functional effects well beyond the original site of activation. Data gathered from breakthroughs in biochemistry, crystallography, and single molecule fluorescence have established a rich basis of information for the study of molecular mechanisms in the allosteric couplings of such transmembrane proteins. The mechanistic details of these couplings, many of which have therapeutic implications, however, have only become accessible in synergy with molecular modeling and simulations. Here, we review some recent computational approaches that analyze allosteric coupling networks (ACNs) in transmembrane proteins, and in particular the recently developed Protein Interaction Analyzer (PIA) designed to study ACNs in the structural ensembles sampled by molecular dynamics simulations. The power of these computational approaches in interrogating the functional mechanisms of transmembrane proteins is illustrated with selected examples of recent experimental and computational studies pursued synergistically in the investigation of secondary active transporters and GPCRs. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Biochemistry & Molecular Biology↗
DOE OSTI2020

A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): an application of the Community Emissions Data System (CEDS)

Global anthropogenic emission inventories remain vital for understanding the sources of atmospheric pollution and the associated impacts on the environment, human health, and society. Rapid changes in today's society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx; CO; SO2; NH3; non-methane volatile organic compounds, NMVOCs; black carbon, BC; organic carbon, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture; energy generation; industrial processes; on-road and non-road transportation; separate residential, commercial, and other sectors (RCO); waste; solvent use; and international shipping) and four fuel categories (total coal, solid biofuel, the sum of liquid-fuel and natural-gas combustion, and remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes monthly global gridded (0.5°?×?0.5°) emission fluxes for each compound, sector, and fuel type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default scaling procedure, and modifications to the final procedures for emissions gridding and aggregation. Relative to the previous CEDS inventory (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel types and source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), and emissions from the waste sector. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS (last access: 1 December 2020). The CEDSGBD-MAPS emission inventory dataset (both annual country-total and monthly global gridded files) is publicly available under https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020c).

Mcduffie, Erin↗
DOE OSTI2021

A measure of active interfaces in supported catalysts for high-temperature reactions

Formulating knowledge of structure-function relationships in heterogeneous catalysis is central to the design of efficient catalysts; yet, the elucidation of dominant reaction sites has remained as a challenge. Here, in this paper, we present a methodology that can be used to visualize metal-gas and metal-oxide-gas interfaces in three dimensions and to quantify their catalytic activity levels. As a case study, CH 4 oxidation occurring in a Pt/CeO 2 system is chosen. By employing thermally robust Pt@CeO 2 model catalysts with size-tunable and monodisperse cores, and gas-permeable shells, we reconstruct a series of structures in 3D via electron tomography and match the information to activity data and theoretical calculations. This strategy reveals that two different interfaces catalyze the CH 4 oxidation and that their contribution to the overall rate changes with the Pt size, temperature, and gas atmosphere. Our results provide an analytic platform on which to explore reaction pathways and mechanisms applicable to multiple reactions and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Russian anthropogenic black carbon: Emission reconstruction and Arctic black carbon simulation

Development of reliable source emission inventories is needed to advance the understanding of the origin of Arctic haze using chemical transport modeling. This paper develops a regional anthropogenic black carbon (BC) emission inventory for the Russian Federation, the largest country by land area in the Arctic Council. Activity data from combination of local Russia information and international resources, emission factors based on either Russian documents or adjusted values for local conditions, and other emission source data are used to approximate the BC emissions. Emissions are gridded at a resolution of 0.1° × 0.1° and developed into a monthly temporal profile. Total anthropogenic BC emission of Russia in 2010 is estimated to be around 224 Gg. Gas flaring, a commonly ignored black carbon source, contributes a significant fraction of 36.2% to Russia's total anthropogenic BC emissions. Other sectors, i.e., residential, transportation, industry, and power plants, contribute 25.0%, 20.3%, 13.1%, and 5.4%, respectively. Three major BC hot spot regions are identified: the European part of Russia, the southern central part of Russia where human population densities are relatively high, and the Urals Federal District where Russia's major oil and gas fields are located but with sparse human population. BC simulations are conducted using the hemispheric version of Community Multi-scale Air Quality Model with emission inputs from a global emission database EDGAR (Emissions Database for Global Atmospheric Research)-HTAPv2 (Hemispheric Transport of Air Pollution) and EDGAR-HTAPv2 with its Russian part replaced by the newly developed Russian BC emissions, respectively. The simulation using the new Russian BC emission inventory could improve 30–65% of absorption aerosol optical depth measured at the AERONET sites in Russia throughout the whole year as compared to that using the default HTAPv2 emissions. At the four ground monitoring sites (Zeppelin, Barrow, Alert, and Tiksi) in the Arctic Circle, surface BC simulations are improved the most during the Arctic haze periods (October–March). The poor performance of Arctic BC simulations in previous studies may be partly ascribed to the Russian BC emissions built on out-of-date and/or missing information, which could result in biases to both emission rates and the spatial distribution of emissions. Finally, this study highlights that the impact of Russian emissions on the Arctic haze has likely been underestimated, and its role in the Arctic climate system needs to be reassessed. The Russian black carbon emission source data generated in this study can be obtained via http://abci.ornl.gov/download.shtml or http://acs.engr.utk.edu/Data.php.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

ADP‐Induced Ca 2+ Signaling and Proliferation of Rat Ventricular Myofibroblasts Depend on Phospholipase C‐Linked TRP Channels Activation Within Lipid Rafts

Nucleotides released during heart injury affect myocardium electrophysiology and remodeling through P2 purinoceptors activation in cardiac myofibroblasts. ATP and UTP endorse [Ca 2+ ] i accumulation and growth of DDR‐2/α‐SMA‐expressing myofibroblasts from adult rat ventricles via P2Y 4 and P2Y 2 receptors activation, respectively. Ventricular myofibroblasts also express ADP‐sensitive P2Y 1 , P2Y 12 , and P2Y 13 receptors as demonstrated by immunofluorescence confocal microscopy and western blot analysis, but little information exists on ADP effects in these cells. ADP (0.003–3 mM) and its stable analogue, ADPßS (100 μM), caused fast [Ca 2+ ] i transients originated from thapsigargin‐sensitive internal stores, which partially declined to a plateau sustained by capacitative Ca 2+ entry through transient receptor potential (TRP) channels inhibited by 2‐APB (50 μM) and flufenamic acid (100 μM). Hydrophobic interactions between G q/11 ‐coupled P2Y purinoceptors and TRP channels were suggested by prevention of the ADP‐induced [Ca 2+ ] i plateau following PIP 2 depletion with LiCl (10 mM) and cholesterol removal from lipid rafts with methyl‐ß‐cyclodextrin (2 mM). ADP [Ca 2+ ] i transients were insensitive to P2Y 1 , P2Y 12 , and P2Y 13 receptor antagonists, MRS2179 (10μM), AR‐C66096 (0.1 μM), and MRS2211 (10μM), respectively, but were attenuated by suramin and reactive blue‐2 (100 μM) which also blocked P2Y 4 receptors activation by UTP. Cardiac myofibroblasts growth and type I collagen production were favored upon activation of MRS2179‐sensitive P2Y 1 receptors with ADP or ADPßS (30 μM). In conclusion, ADP exerts a dual role on ventricular myofibroblasts: [Ca 2+ ] i transients are mediated by fast‐desensitizing P2Y 4 receptors, whereas the pro‐fibrotic effect of ADP involves the P2Y 1 receptor activation. Data also show that ADP‐induced capacitative Ca 2+ influx depends on phospholipase C‐linked TRP channels opening in lipid raft microdomains. J. Cell. Physiol. 232: 1511–1526, 2017. © 2016 Wiley Periodicals, Inc.

Certal, Mariana↗
DOE OSTI2020

Machine learning-based prediction of enzyme substrate scope: Application to bacterial nitrilases

Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequenc- and structure-based annotation approaches are often accurate for predicting broad categories of substrate specificity, they generally cannot predict which specific molecules will be accepted as substrates for a given enzyme, particularly within a class of closely related molecules. Combining targeted experimental activity data with structural modeling, ligand docking, and physicochemical properties of proteins and ligands with various machine learning models provides complementary information that can lead to accurate predictions of substrate scope for related enzymes. Here we describe such an approach that can predict the substrate scope of bacterial nitrilases, which catalyze the hydrolysis of nitrile compounds to the corresponding carboxylic acids and ammonia. Each of the four machine learning models (logistic regression, random forest, gradient-boosted decision trees, and support vector machines) performed similarly (average ROC = 0.9, average accuracy = ~82%) for predicting substrate scope for this dataset, although random forest offers some advantages. Finally, this approach is intended to be highly modular with respect to physicochemical property calculations and software used for structural modeling and docking.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Assessment of Myocarditis: Cardiac MR, PET/CT, or PET/MR?

Purpose of Review: Diagnosis of myocarditis is challenging given its variable clinical manifestations and non-specific laboratory findings. Cardiac magnetic resonance (MR) is currently the preferred imaging modality for the diagnosis of myocarditis. {sup 18}F-fluoro-deoxy-glucose (FDG) positron emission tomography/computed tomography (PET/CT), as a functional imaging tool, has a potential role in the assessment of myocarditis by detecting the underlying myocardial inflammatory activity. Data are accumulating that simultaneous cardiac PET/MR may have complementary and incremental values for the evaluation of myocarditis compared to PET/CT or cardiac MR alone. The article aims to summarize the findings in the literature and discuss future directions of cardiac PET/MR for myocarditis. Recent Findings: The Lake Louis Criteria (CLL) of cardiac MR is widely used for the diagnosis of myocarditis. It has an overall acceptable sensitivity of 67% and specificity of 91% for acute myocarditis but does not have the same accuracy for chronic myocarditis. FDG PET/CT is capable of assessing myocarditis by providing metabolic information of inflammation as increased myocardial FDG uptake. In addition to reduced radiation exposure, FDG PET performed on a hybrid PET/MR may detect more myocarditis than FDG PET/CT, because of the delayed PET acquisition time on PET/MR. Case-based observations and small clinical studies of FDG PET/MR have shown that FDG PET findings as abnormally increased myocardial uptake correlate well with the cardiac MR biomarkers. FDG PET findings may add complementary and incremental values to cardiac MR by improving the sensitivity of cardiac MR for mild or borderline myocarditis, and increasing specificity for chronic myocarditis. Summary: Preliminary data from retrospective and case-based observational studies have suggested the complementary and incremental values of simultaneous cardiac FDG PET/MR for evaluation of myocarditis, compared to PET/CT or MR alone. Well-designed studies are needed to confirm the findings and to assess the value of cardiac PET/MR for clinical management and more importantly patient’s outcome in both acute and chronic myocarditis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Effect of sodium loading on Pt/ZrO 2 during ethanol steam reforming

Ethanol steam reforming (ESR) was investigated on unpromoted and several sodium promoted Pt/ZrO 2 catalysts. From DRIFTS experiments, the following steps during ESR were inferred: dissociation of ethanol to produce ethoxy species; oxidative dehydrogenation of ethoxy species to acetate; and acetate decomposition. Acetate decomposition depends on the catalyst formulation. Decarboxylation is the most favored route at high sodium loading (2.5 and 5 wt.%); acetate decomposes in the forward direction to CH 4 and a carbonate, which further decomposes to CO 2 . In contrast, decarbonylation is prevalent for the unpromoted catalyst or catalysts having low sodium loading. Furthermore, acetate likely decomposes to CH 3 OH and CO. Adsorbed methanol may undergo further steam reforming by oxidative dehydrogenation to formate species, which decarbonylates via reverse decomposition to CO and H 2 O. Temperature programmed desorption/reaction and activity data confirmed that alkali promotion, especially at 1.8 %Na and higher loading, facilitates the forward acetate decomposition step, favoring decarboxylation over decarbonylation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Discovery and crystallography of bicyclic arylaminoazines as potent inhibitors of HIV-1 reverse transcriptase

Non-nucleoside inhibitors of HIV-1 reverse transcriptase (HIV-RT) are reported that incorporate a 7-indolizinylamino or 2-naphthylamino substituent on a pyrimidine or 1,3,5-triazine core. The most potent compounds show below 10 nanomolar activity towards wild-type HIV-1 and variants bearing Tyr181Cys and Lys103Asn/Tyr181Cys resistance mutations. As a result, the compounds also feature good aqueous solubility. Crystal structures for two complexes enhance the analysis of the structure–activity data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Exploring Subsite Selectivity within Plasmodium vivax N -Myristoyltransferase Using Pyrazole-Derived Inhibitors

N-myristoyltransferase (NMT) is a promising antimalarial drug target. Despite biochemical similarities between Plasmodium vivax and human NMTs, our recent research demonstrated that high selectivity is achievable. Herein, we report PvNMT-inhibiting compounds aimed at identifying novel mechanisms of selectivity. Various functional groups are appended to a pyrazole moiety in the inhibitor to target a pocket formed beneath the peptide binding cleft. The inhibitor core group polarity, lipophilicity, and size are also varied to probe the water structure near a channel. Selectivity index values range from 0.8 to 125.3. Cocrystal structures of two selective compounds, determined at 1.97 and 2.43 Å, show that extensions bind the targeted pocket but with different stabilities. A bulky naphthalene moiety introduced into the core binds next to instead of displacing protein-bound waters, causing a shift in the inhibitor position and expanding the binding site. Our structure-activity data provide a conceptual foundation for guiding future inhibitor optimizations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Surface Atomic Structure and Functionality of Metallic Nanoparticles: A Case Study of Au–Pd Nanoalloy Catalysts

The surface atomic structure of metallic nanoparticles (NPs) plays a key role in shaping their physicochemical properties and response to external stimuli. Not surprisingly, current research increasingly focuses on exploiting its prime characteristics, including the amount, location, coordination, and electronic configuration of distinct surface atomic species, as tunable parameters for improving the functionality of metallic NPs in practical applications. The effort requires clear understanding of the extent to which changes in each of these characteristics would contribute to achieving the targeted functionality. This, in the first place, requires good knowledge of the actual surface of metallic NPs at atomic level. Through a case study on Au–Pd nanoalloy catalysts of industrial and environmental importance, we demonstrate that the surface atomic structure of metallic NPs can be determined in good detail by resonant high-energy X-ray diffraction (HE-XRD). Furthermore, using our experimental surface structure and CO oxidation activity data, we shed new light on the elusive origin of the remarkable catalytic synergy between surface Au and Pd atoms in the nanoalloys. In particular, we show that it arises from the formation of a specific “skin” on top of the nanoalloys that involves as many unlike, i.e., Au–Pd and Pd–Au, atomic pairs as possible given the overall chemical composition of the NPs. Moreover, unlike atoms from the “skin” interact strongly, including both changing their size and electronic structure in inverse proportions. That is, Au atoms shrink and acquire a partial positive charge of 5d-character whereas Pd atoms expand and become somewhat 4d-electron deficient. Accordingly, the reactivity of Au increases whereas Pd atoms become less reactive, as compared to atoms at the surface of pure Au and Pd NPs, respectively. Ultimately, this renders Au–Pd alloy NPs superb catalysts for CO oxidation reaction over a broad range of alloy compositions. Our findings are corroborated by DFT calculations based on a refined version of d-band center theory on the catalytic properties of late transition metals and alloys. Here, we discuss opportunities for improving the accuracy of current theory on surface-controlled properties of metallic NPs through augmenting the theory with surface structure data obtained by resonant XRD.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Examining Daily Temporal Characteristics of Oil and Gas Methane Emissions in the Delaware Basin Using Continuous Tower Observations

Top-down studies have found consistent underestimations in the United States Environmental Protection Agency (EPA) methane emissions inventory from the oil and gas (O&G) sector. Many of these studies use observations that bias toward hours when worktime activity occurs. In this study, we analyze over 2 years of methane measurements from a tower network in the Delaware basin to analyze hourly temporal emission patterns. Inversion results suggest a range in emissions from 137 Mg/hr at night to 197 Mg/hr during the day, present during both weekdays and weekends. If these results are applicable to other basins, daytime-influenced methodologies may overestimate daily emission rates by up to 27%. This bias does not reconcile the more than 200% difference between the EPA inventory and top-down estimates in the Delaware basin. This study demonstrates how continuous measurement networks can be combined with detailed activity data to improve bottom-up inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Distributed quantum approximate optimization algorithm on a quantum-centric supercomputing architecture

Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dimensional problems due to the large number of qubits required and the complexity of deep circuits, limiting its scalability for real-world applications. In this study, we present a distributed QAOA (DQAOA), which leverages distributed computing strategies to decompose a large computational workload into smaller tasks that require fewer qubits and shallower circuits than are necessary to solve the original problem. These sub-problems are processed using a combination of high-performance and quantum computing resources. The global solution is iteratively updated by aggregating sub-solutions, allowing convergence toward the optimal solution. We demonstrate that DQAOA can handle considerably large-scale optimization problems (e.g., 1000-bit problem), achieving a high solution quality and short time-to-solution, outperforming existing strategies. Furthermore, we realize DQAOA on a quantum-centric supercomputing architecture, paving the way for practical applications of gate-based quantum computers in real-world optimization tasks. To extend DQAOA’s applicability to materials science, we further develop an active learning algorithm integrated with our DQAOA (AL-DQAOA), which involves machine learning, DQAOA, and active data production in an iterative loop. We successfully optimize photonic structures using AL-DQAOA, indicating that solving real-world optimization problems using gate-based quantum computing is feasible. We expect the proposed DQAOA to be applicable to a wide range of optimization problems and AL-DQAOA to find broader applications in material design.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)↗
DOE OSTI2024

Application of research reactor environments for validation of the IRDFF-II dosimetry cross section library

Activation data from seven different reactor-based reference neutron fields are examined to provide enhanced validation evidence for the newly released IRDFF-II library. A least-squares based spectrum adjustment methodology is used and rigorous statistical metrics demonstrate the consistency of the set of IRDFF-II dosimetry cross sections. The use of these reactor-based neutron fields provides validation evidence for nine more reactions than have been addressed in the 252 Cf(sf) and 235 U(th) benchmark validation testing. The use of covers to shift their energy response increases the power of the response validation but makes it challenging to properly capture response correlations.

Griffin, Patrick↗
DOE OSTI2018

Temporal variability largely explains top-down/bottom-up difference in methane emission estimates from a natural gas production region

Here, this study spatially and temporally aligns top-down and bottom-up methane emission estimates for a natural gas production basin, using multiscale emission measurements and detailed activity data reporting. We show that episodic venting from manual liquid unloadings, which occur at a small fraction of natural gas well pads, drives a factor-of-two temporal variation in the basin-scale emission rate of a US dry shale gas play. The midafternoon peak emission rate aligns with the sampling time of all regional aircraft emission studies, which target well-mixed boundary layer conditions present in the afternoon. A mechanistic understanding of emission estimates derived from various methods is critical for unbiased emission verification and effective greenhouse gas emission mitigation. Our results demonstrate that direct comparison of emission estimates from methods covering widely different timescales can be misleading.

03 NATURAL GAS↗
DOE OSTI2023

Mitigation of ventilation air methane (VAM) using novel methanotrophic coating materials: a technical analysis

Abstract Ventilation air methane (VAM) is a potent greenhouse gas source originating from geological wells, current and extinct mineshafts and other terrestrial conduits venting methane to the atmosphere, contributing to global methane emissions and disproportionate warming potential. Herein, we introduce the concept of the methanotrophic material as an engineering solution. Such materials should be capable of converting methane at ambient temperatures and pressures to a binder product, capturing and permanently sequestering the methane while simultaneously restricting its further emission. While such materials are currently under research development, this goal is supported and facilities by the mathematical framework, introduced and used herein, to evaluate the ability to convert methane, using currently published activity data. We include a case study of the conversion of a characteristic stream of VAM (0.6% methane in air, 1.7 × 10 8 l hr −1 equivalent to 100 000 standard cubic feet per minute). We show that when appropriately designed, such systems require a surface coverage of less than 1000 m of mine tunnel length (equivalent to 20 000 m 2 areal coverage) in order to reduce the methane emission from this stream by over 99%. Finally, we highlight formaldehyde as a reactive intermediate of methane oxidation which may itself be incorporated into these coating materials. As a component of binders and polymers already used ubiquitously in commercial products, this intermediate ultimately allows these systems to sequester the carbon from methane in a stable and solid form. The results presented here are easily extended to the treatment of other methane streams—either more concentrated or dilute—and the results herein will guide the design and development of a new class of carbon-negative materials.

Environmental Sciences & Ecology↗