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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

North Slope of Alaska Black Carbon Loadings and Mixing State for MOSAiC Field Campaign Report

The Arctic represents a unique region to study global climate change in that it exhibits pronounced sensitivity towards aerosol radiative forcing, referred to as arctic amplification. Of the aerosol species that are expected to contribute to this aerosol forcing, black carbon (BC) is arguably at the top of the list. Black carbon has this distinction because it exerts two radiative forcing influences that can be characterized as atmospheric and non-atmospheric. As an atmospheric forcer, BC behaves much as it does in the mid-latitudes – through the direct effect and semi-direct effects – collectively causing surface dimming with subsequent surface cooling and mid-altitude warming affecting cloud cover. As a terrestrial forcer, which is unique to the cryosphere, the deposition of BC on the surface can readily decrease polar surface albedo that, in turn, can activate a positive feedback wherein the increased surface absorption leads to further snow melt causing still further reduction in surface albedo.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Arctic Aerosol Sources and Mixing States Field Campaign Report

The Arctic is warming at a faster rate than anywhere else on Earth, with rapidly shrinking sea ice extent transforming the region. Depending on chemical and physical properties, atmospheric aerosols directly scatter and/or absorb radiation, serve as cloud droplet and/or ice crystal nuclei, and/or reduce the reflectiveness of the snow surface, thereby altering the atmospheric energy budget. There is a wide spread in the magnitude of simulated arctic aerosol radiative forcing, and significant differences in aerosol concentration levels and seasonal cycles often exist between models and observations. Increasing local natural and anthropogenic emissions are significant, with uncertain climate impacts due to complex feedbacks. Model evaluations, however, are limited by the dearth of arctic aerosol observations available and an inadequate understanding of arctic aerosol processes. The majority of previous arctic aerosol observations have been made through intensive spring/summer field campaigns, with few intensive measurement studies focused on the fall-winter transition, a period when freeze-up is occurring later and thinning sea ice is resulting in wintertime ice fracturing. Aerosol monitoring at arctic coastal stations has provided knowledge of long-term seasonal trends in aerosol concentrations. The completed ARM field campaign addresses observational and knowledge gaps through detailed aerosol size and chemical composition measurements during the fall-winter transition in the coastal Arctic and through the entire annual cycle in the central Arctic. The observations are improving our understanding of the sources and processes controlling the aerosol population in the rapidly changing Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Elucidating Processes Controlling Arctic Atmospheric Aerosol Sources, Aging, and Mixing States (Final Report)

Atmospheric aerosols play critical roles in the Earth’s energy budget, directly by scattering or absorbing solar and terrestrial radiation and indirectly by serving as seeds (nuclei) for cloud droplet and ice crystal formation and by depositing on snow and ice surface, thereby changing the surface albedo. These effects are dependent on aerosol particle size and chemical composition and impact the hydrological cycle as well. This project provided single-particle size and chemical composition measurements across the entire annual cycle in the high Arctic and in the Alaskan Arctic during fall – winter, addressing the most significant gaps in Arctic aerosol observational data. These needs were based on recent rapid sea ice loss across the entire Arctic, as well as the major annual delays in sea ice freeze-up during fall in the Chukchi Sea and increased wintertime sea ice fracturing in the Beaufort Sea, both off the North Slope of Alaska. Two DOE Atmospheric Radiation Measurement (ARM) field campaigns were conducted for atmospheric aerosol sampling. The Aerosols during the Polar Utqiagvik Night (APUN – ‘snow on ground’ in Iñupiaq) ARM field campaign at Utqagivik, Alaska was conducted from Oct. 28 – Dec. 22, 2018. Aerosol sizing instrumentation and a single-particle mass spectrometer were successfully deployed for size-resolved number concentration measurements and measurements of individual particle size and chemical composition, respectively. These results show the influence of locally-produced sea spray aerosol, with high cloud-forming potential, due to delayed sea ice freeze-up in the fall. During the 2019‐2020 international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, daily atmospheric aerosol particles were collected aboard the German icebreaker Polarstern in the Central Arctic from Nov. 2019 – Oct. 2020. Sea salt aerosol and marine organics were observed year-round during MOSAiC with varying morphologies and sources. These findings are important because most Arctic models do not include a sea spray aerosol source, despite this source increasing with declining sea ice extent. In addition to collecting new samples and data, this project also conducted further analysis of previously collected single-particle chemical composition measurements within the North Slope of Alaska oil fields and at Utqiaġvik, AK, during Aug. – Sep. 2015 and 2016 field campaigns. This work resulted in the discovery of chemical reactions of oil field combustion emissions occurring within fog droplets across the North Slope of Alaska and forming secondary aerosol, showing the impact of Arctic oil field emissions beyond black carbon aerosol and greenhouse gases. In addition, the distribution of chemical species across the aerosol population within the oil fields was quantified, using these data and a previously development framework. We also presented the first ambient evidence of the collision of two atmospheric particles resulting in formation of an organic-coated ammonium sulfate particle of marine origin, which has implications for cloud formation with declining sea ice extent. Overall, this project has elucidated connections between seawater biogeochemistry, resource extraction activities, atmospheric composition, clouds, and the energy budget of the Arctic region. The results of this project are expected to improve weather and sea ice forecasting for security and development in the Arctic and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Aerosol Hygroscopic Growth, Mixing State, and Cloud Condensation Nuclei Activity during TRACER (Field Campaign Report)

Convective clouds play a critical role in the Earth’s climate system. Recent research has shown that a realistic representation of convective processes is critical to constraining climate sensitivity in global climate models. Theoretical and modeling studies showed that aerosols could have strong dynamic feedback to convection in warm and humid environments through enhancing ice-related processes and condensational growth. A few observation-based studies also suggested the influence of aerosols on convective cloud and precipitation properties. However, robust observational quantification of an aerosol effect on convective clouds isolated from other factors remains elusive. Understanding the impact of aerosol on convective clouds requires knowledge of the cloud condensation nuclei (CCN) spectrum, which represents the number of particles that uptake water and form cloud droplets as a function of supersaturation. The water uptake by aerosol is also of critical importance for the direct interaction of aerosol with radiation (i.e., aerosol direct effect) due to light scattering and absorption by aerosol. While both droplet activation under supersaturated conditions (i.e., relative humidity RH > 100%) and the hygroscopic growth under sub-saturated conditions (i.e., RH < 100%) are strongly influenced by particle hygroscopicity, the thermodynamic regimes and measurement methods are quite different. Aerosol particles, especially organic particles, can exhibit higher hygroscopicity for droplet activation than that for hygroscopic growth. In the subsaturated regime, the hygroscopicity of organic particles can also vary strongly with RH. However, global climate models usually treat organic species in aerosols with a constant hygroscopicity, potentially introducing substantial uncertainties in the quantification of aerosol radiative effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Isotope effects on transport in LHD

Abstract Isotope effects are one of the most important issues for predicting future reactor operations. Large helical device (LHD) is the presently working largest stellarator/helical device using super conducting helical coils. In LHD, deuterium experiments started in 2017. Extensive studies regarding isotope effects on transport have been carried out. In this paper, the results of isotope effect studies in LHD are reported. The systematic studies were performed adjusting operational parameters and nondimensional parameters. In L mode like normal confinement plasma, where internal and edge transport barriers are not formed, the scaling of global energy confinement time ( τ E ) with operational parameters shows positive mass dependence ( M 0.27 ; where M is effective ion mass) in electron cyclotron heating plasma and no mass dependence ( M 0.0 ) in neutral beam injection heating plasma. The non-negative ion mass dependence is anti-gyro-Bohm scaling. The role of the turbulence in isotope effects was also found by turbulence measurements and gyrokinetic simulation. Better accessibility to electron and ion internal transport barrier (ITB) plasma is found in deuterium (D) plasma than in hydrogen (H). Gyro kinetic non-linear simulation shows reduced ion heat flux due to the larger generation of zonal flow in deuterium plasma. Peaked carbon density profile plays a prominent role in reducing ion energy transport in ITB plasma. This is evident only in plasma with deuterium ions. New findings on the mixing and non-mixing states of D and H particle transports are reported. In the mixing state, ion particle diffusivities are higher than electron particle diffusivities and D and H ion density profiles are almost identical. In the non-mixing state, ion particle diffusivity is much lower than electron diffusivity. Deuterium and hydrogen ion profiles are clearly different. Different turbulence structures were found in the mixing and non-mixing states suggesting different turbulence modes play a role.

Physics↗
DOE OSTI2025

Stabilizing Non-Abelian Topological Order Against Heralded Noise via Local Lindbladian Dynamics

An important open question for the current generation of highly controllable quantum devices is understanding which phases can be realized as stable steady states under local quantum dynamics. In this work, we show how robust steady-state phases with both Abelian and non-Abelian mixed-state topological order can be stabilized, in two spatial dimensions, against generic “heralded” noise using active dynamics that incorporate measurement and feedback, modeled as a fully local Lindblad master equation. These topologically ordered steady states are two-way connected to pure topologically ordered ground states using local quantum channels, and preserve quantum information for a time that is exponentially large in the system size. Specifically, we present explicit constructions of families of local Lindbladians for both Abelian (ℤ 2 ) and non-Abelian (𝐷 4 ) topological order whose steady states host mixed-state topological order when the noise is below a threshold strength. As the noise strength is increased, these models exhibit first-order transitions to intermediate mixed-state phases where they encode robust classical memories, followed by (first-order) transitions to a trivial steady state at high noise rates. When the noise is imperfectly heralded, steady-state order disappears but our active dynamics significantly enhances the lifetime of the encoded logical information. To carry out the numerical simulations for the non-Abelian 𝐷 4 case, we introduce a generalized stabilizer tableau formalism that permits efficient simulation of the non-Abelian Lindbladian dynamics.

Monte Carlo methods↗
DOE OSTI2023

MnEdgeNet for accurate decomposition of mixed oxidation states for Mn XAS and EELS L2,3 edges without reference and calibration

Accurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer and redox centers for electronic, and electrocatalytic and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XAS) measurements of the Mn L2,3 edges are widely used for this purpose. To date, although the measurements of the Mn L2,3 edges are straightforward given the sample is prepared properly, an accurate decomposition of the mix valence states of Mn remains non-trivial. For both EELS and XAS, 2+, 3+, and 4+ reference spectra need to be taken on the same instrument/beamline and preferably in the same experimental session because the instrumental resolution and the energy axis offset could vary from one session to another. To circumvent this hurdle, in this study, we adopted a deep learning approach and developed a calibration-free and reference-free method to decompose the oxidation state of Mn L2,3 edges for both EELS and XAS. A deep learning regression model is trained to accurately predict the composition of the mix valence state of Mn. To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. With that, we created a 1.2 million-spectrum database with 1-by-3 oxidation state composition ground truth vectors. The library includes a sufficient variety of data including both EELS and XAS spectra. By training on this large database, our convolutional neural network achieves 85% accuracy on the validation dataset. We tested the model and found it is robust against noise (down to PSNR of 10) and plural scattering (up to t/λ = 1). We further validated the model against spectral data that were not used in training. In particular, the model shows high accuracy and high sensitivity for the decomposition of Mn 3 O 4 , MnO, Mn 2 O 3 , and MnO 2 . The accurate decomposition of Mn 3 O 4 experimental data shows the model is quantitatively correct and can be deployed for real experimental data. Our model will not only be a valuable tool to researchers and material scientists but also can assist experienced electron microscopists and synchrotron scientists in the automated analysis of Mn L edge data.

25 ENERGY STORAGE↗
DOE OSTI2023

Improving snow albedo modeling in the E3SM land model (version 2.0) and assessing its impacts on snow and surface fluxes over the Tibetan Plateau

With the highest albedo of the land surface, snow plays a vital role in Earth's surface energy budget and water cycle. Snow albedo is primarily controlled by snow grain properties (e.g., size and shape) and light-absorbing particles (LAPs) such as black carbon (BC) and dust. The mixing state of LAPs in snow also has impacts on LAP-induced snow albedo reduction and surface radiative forcing (RF). However, most land surface models assume that snow grain shape is spherical and LAPs are externally mixed with the snow grains. This study improves the snow radiative transfer model in the Energy Exascale Earth System Model version 2.0 (E3SM v2.0) Land Model (ELM v2.0) by considering non-spherical snow grain shapes (i.e., spheroid, hexagonal plate, and Koch snowflake) and internal mixing of dust–snow, and it systematically evaluates the impacts on the surface energy budget and water cycle over the Tibetan Plateau (TP). A series of ELM simulations with different treatments of snow grain shape, mixing state of BC–snow and dust–snow, and sub-grid topographic effects (TOP) on solar radiation are performed. Compared with two remote sensing snow products derived from the Moderate Resolution Imaging Spectroradiometer, the control ELM simulation (ELM_Control) with the default configurations of spherical snow grain shape, internal mixing of BC–snow, external mixing of dust–snow, and without TOP as well as the ELM simulation with new model features (ELM_New) can both capture the overall snow distribution reasonably. Additionally, ELM_New overall shows smaller biases in snow cover fraction than ELM_Control in spring when snowmelt is important for water management. The estimated LAP-induced RF in ELM_New ranges from 0 to 19.3 W m -2 with the area-weighted average value of 1.5 W m -2 that is comparable to the reported values in existing studies. The Koch snowflake shape, among other non-spherical shapes, shows the largest difference from the spherical shape in spring when snow processes related to the surface energy budget and water cycle have high importance. The impacts of the mixing state of LAP in snow are smaller than the shape effects and depend on snow grain shape. Compared to external mixing, internal mixing of LAP–snow can lead to larger snow albedo reduction and snowmelt, which further affect the surface energy budget and water cycle. The individual contributions of non-spherical snow shape, mixing state of LAP–snow, and local topography impacts on the snow and surface fluxes have different signs and magnitudes, and their combined effects may be negative or positive due to complex and nonlinear interactions among the factors. Overall, the changes in net solar radiation in spring due to individual and combined effects range from -28.6 to 16.9 W m -2 and -29.7 to 12.2 W m -2 , respectively. This study advances understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offers guidance for improving snow simulations and RF estimates in Earth system models under climate change.

58 GEOSCIENCES↗