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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Partitioning Quantum Chemistry Simulations with Clifford Circuits

Current quantum computing hardware is restricted by the availability of only few, noisy qubits which limits the investigation of larger, more complex molecules in quantum chemistry calculations on quantum computers in the near term. Here, in this work, we investigate the limits of their classical and near-classical treatment while staying within the framework of quantum circuits and the variational quantum eigensolver. To this end, we consider naive and physically motivated, classically efficient product ansatz for the parametrized wavefunction adapting the separable-pair ansatz form. We combine it with post-treatment to account for interactions between subsystems originating from this ansatz. The classical treatment is given by another quantum circuit that has support between the enforced subsystems and is folded into the Hamiltonian. To avoid an exponential increase in the number of Hamiltonian terms, the entangling operations are constructed from purely Clifford or near-Clifford circuits. While Clifford circuits can be simulated efficiently classically, they are not universal. In order to account for missing expressibility, near-Clifford circuits with only few, selected non-Clifford gates are employed. The exact circuit structure to achieve this objective is molecule-dependent and is constructed using simulated annealing and genetic algorithms. We demonstrate our approach on a set of molecules of interest and investigate the extent of our methodology’s reach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Dependence of Aerosol-Droplet Partitioning on Turbulence in a Laboratory Cloud

Activation is the first step in aerosol-cloud interactions, which have been identified as one of the principal uncertainties in Earth's climate system. Aerosol particles become cloud droplets, or activate, when the ambient saturation ratio exceeds a threshold, which depends on the particle's size and hygroscopicity. In the traditional formulation of the process, only average, uniform saturation ratios are considered. Furthermore, turbulent environments like clouds intrinsically have fluctuations around mean values in the scalar fields of temperature and water vapor concentration, which determine the saturation ratio. Through laboratory measurements, we show that these fluctuations are an important parameter that needs to be addressed to fully describe activation. Our results show, even for single-sized, chemically homogeneous aerosols, that fluctuations blur the correspondence between activation and a particle's size and chemical composition, that turbulence can increase the fraction of aerosol particles which activate, and that the activated fraction decreases monotonically as the concentration of aerosol increases. Taken together, our data demonstrate that fluctuations can have effects equivalent to the aerosol limited and updraft limited regimes, known from adiabatic parcel theory.

58 GEOSCIENCES↗
DOE OSTI2022

Effects of Improved Simulation of Precipitation on Evapotranspiration and Its Partitioning Over Land

Evapotranspiration (ET) is a key component of the global hydrological cycle, which is strongly modulated by the occurrence of different rainfall intensities. Global climate models (GCMs) commonly suffer from “too much light rain” and a negative bias in the ratio of transpiration (T) to ET (T/ET). It is unclear whether these biases are related. Here, in this work, we show that with the improved simulation of probability density functions of rainfall intensity by suppressing light-rain occurrence using a stochastic convection parameterization in the NCAR CESM1.2, the canopy T increases in tropical forests while evaporation from canopy interception and bare soil decreases. The simulated T/ET is increased by 2.5% globally and up to 8% regionally, primarily attributable to reduced fraction of wet leaves due to less frequent light rain despite its weak intensity. These results imply that excessive light rain is an important cause of the negative T/ET bias in GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Model‐Based Interpretation of Solute Exports and Carbon Partitioning During Shale Weathering in a Mountainous Hillslope

The weathering of sedimentary rocks in high-elevation catchments influences freshwater quality and the global carbon cycle. While individual biogeochemical mechanisms involved in this process are relatively well understood, quantifying their contributions to solute export and carbon fluxes under natural, transient conditions remains challenging. Here, we implement a numerical multidimensional and multiphase model to simulate coupled hydrological and biogeochemical processes in a shale-underlain, snow-dominated hillslope in the Rocky Mountains, Colorado. The model captures the dynamic interplay between soil respiration, mineral weathering, and climate-driven hydrological forcing, reproducing observed soil CO 2 dynamics, groundwater chemistry, and subsurface flow. Our results reveal that seasonal snowmelt enhances carbonate weathering by promoting the infiltration of CO 2 -rich water to depth, while pyrite oxidation is primarily sensitive to low water saturation that facilitates O 2 diffusion through the regolith. Topography modulates the spatial distribution of shale weathering, as steeper slopes enhance lateral drainage, favoring the delivery of reactants to greater depths. While shale weathering at our site acts as a transient carbon sink, with silicates and carbonates buffering acidity and promoting atmospheric CO 2 consumption (1% of soil-derived CO 2 ), the exported dissolved inorganic carbon is predominantly geogenic (∼73%). Consequently, when accounting for long-term marine carbonate precipitation. The current weathering regime represents a net source of carbon to the atmosphere. The oxidation of pyrite and petrogenic organic carbon together release approximately 0.9 mol·m −2 ·yr −1 of CO 2 . Our findings highlight the role of topography, hydroclimate, and the coupling between acid-base reactions in shaping the carbon balance and the solute exports in mountainous critical zones.

carbon cycling↗
DOE OSTI2020

Polysaccharide niche partitioning of distinct Polaribacter clades during North Sea spring algal blooms

Massive releases of organic substrates during marine algal blooms trigger growth of many clades of heterotrophic bacteria. Algal polysaccharides represent the most diverse and structurally complex class of these substrates, yet their role in shaping the microbial community composition is poorly understood. We investigated, whether polysaccharide utilization capabilities contribute to niche differentiation of Polaribacter spp. (class Flavobacteriia; known to include relevant polysaccharidedegraders) that were abundant during 2009–2012 spring algal blooms in the southern North Sea. We identified six distinct Polaribacter clades using phylogenetic and phylogenomic analyses, quantified their abundances via fluorescence in situ hybridization, compared metagenome-assembled genomes, and assessed in situ gene expression using metaproteomics. Four clades with distinct polysaccharide niches were dominating. Polaribacter 2-a comprised typical first responders featuring small genomes with limited polysaccharide utilization capacities. Polaribacter 3-a were abundant only in 2010 and possessed a distinct sulfated α-glucoronomannan degradation potential. Polaribacter 3-b responded late in blooms and had the capacity to utilize sulfated xylan. Polaribacter 1-a featured high numbers of glycan degradation genes and were particularly abundant following Chattonella algae blooms. These results support the hypothesis that sympatric Polaribacter clades occupy distinct glycan niches during North Sea spring algal blooms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Astatine partitioning between nitric acid and conventional solvents: indication of covalency in ketone complexation of AtO +

Astatine-211 has been produced at Texas A&M University on the K150 cyclotron, with a yield of 890 ± 80 MBq through the 209 Bi(α,2n) 211 At reaction via an 8 h bombardment with a beam current of 4–8 μA and an α-particle beam energy of 28.8 MeV. The target was then dissolved in HNO 3 and the extraction of 211 At was investigated into a variety of organic solvents in 1–3 M HNO 3 . Extraction of 211 At with distribution ratios as high as 11.3 ± 0.6, 12.3 ± 0.8, 42.2 ± 2.2, 69 ± 4, and 95 ± 6 were observed for diisopropyl ether, 1-decanol, 1-octanol, 3-octanone, and methyl isobutyl ketone, respectively, while the distribution ratios for 207 Bi were ≤0.05 in all cases. The extraction of 211 At into both methyl isobutyl ketone and 3-octanone showed a strong, linear dependence on the HNO 3 initial aqueous concentration and better extraction than other solvents. DFT calculations show stronger binding between the carbonyl oxygen of the ketone and the At metal center.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Partitioning uncertainty in projections of Arctic sea ice

Abstract Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic environment. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice area (SIA) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model Intercomparison Project. For projections of September Arctic SIA change, internal variability accounts for as much as 40%–60% of the total uncertainty in the next decade, while emissions scenario dominates uncertainty toward the end of the century. Model structure accounts for 60%–70% of the total uncertainty by mid-century and declines to 30% at the end of the 21st century in the summer months. For projections of wintertime Arctic SIA change, internal variability contributes as much as 50%–60% of the total uncertainty in the next decade and impacts total uncertainty at longer lead times when compared to the summertime. In winter, there exists a considerable scenario dependence of model uncertainty with relatively larger model uncertainty under strong forcing compared to weak forcing. At regional scales, the contribution of internal variability can vary widely and strongly depends on the calendar month and region. For wintertime SIA change in the Greenland-Iceland-Norwegian and Barents Seas, internal variability contributes 60%–70% to the total uncertainty over the coming decades and remains important much longer than in other regions. We further find that the relative contribution of internal variability to total uncertainty is state-dependent and increases as sea ice volume declines. These results demonstrate that internal variability is a significant source of uncertainty in projections of Arctic sea ice.

Bonan, David B. (ORCID:0000000338676009)↗
DOE OSTI2022

A simple framework to characterize land aridity based on surface energy partitioning regimes

Land aridity is often characterized by the aridity index (AI), which does not account for land surface water-energy interactions that are crucially important in determining regional climate. Such interactions can be captured by the evaporative fraction (EF, ratio of evapotranspiration to available energy) regimes. As EF is subject to energy and water limitations in humid and dry areas, respectively, EF regimes may be used to characterize land aridity to account for the influence of complex land characteristics and their impact on water availability. Here, we propose a simple framework to characterize land aridity by statistically ranking the coupling strength between EF and surface energy and water terms. The framework is demonstrated using gridded data and compared with AI over the U.S. and China. Results show that regionalization of aridity zones based on EF regimes and a two-tiered classification scheme may provide information such as surface energy and water variability complementary to the background aridity depicted by AI, with implications for extreme events.

54 ENVIRONMENTAL SCIENCES↗