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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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Adsorptive Capture of Iodide by Metal-Organic Framework from Off-Gas Condensate Simulate
Millions of gallons of liquid nuclear wastes generated due to nuclear weapon development during the Cold War are in tank storage at several Department of Energy (DOE) sites across the country. DOE is responsible for disposal of the tank nuclear waste and clean-up of the contaminated sites. These efforts are complex and challenging technically and are costly financially, with the predicted overall cost reaching $377 billion over the next few decades [1]. The current practice of nuclear waste treatment and tank closure is to separate high-level waste (HLW) and low-level waste (LLW) [2]. The HLW is then vitrified into a borosilicate-based glass waste form [3], while the LLW is immobilized into cementitious grout or vitrified into glass [4]. However, these treatment processes have met unsolved technical problems
Condensation Particle Counter (CPC) Instrument Handbook
The Model 3772 CPC is a compact, rugged, and full-featured instrument that detects airborne particles down to 10 nm in diameter, at an aerosol flow rate of 1.0 lpm, over a concentration range from 0 to 1x104 #/cc. This CPC is ideally suited for applications without high concentration measurements, such as basic aerosol research, filter and air-cleaner testing, particle counter calibrations, environmental monitoring, mobile aerosol studies, particle shedding and component testing, and atmospheric and climate studies.
CAP 50050 Cargo Tritium Condensation
Abstract not provided.
Interfacial chemistry in geologic nanopores (condensed version).
Abstract not provided.
On-the-Fly Energy Condensation for Whole-Core Multiphysics Simulations
As the nuclear energy industry considers ways to achieve improved economics in the current fleet of light-water reactors (LWRs), one possible approach is to operate each cycle longer. This causes a greater portion of the fuel to be burned and reduces the frequency of outages, which ultimately reduces the cost to operate the reactor. However, this also leads to higher burnup fuels than have traditionally been allowed in these reactors. There are concerns about integrity of high-burnup (HBu) fuel, especially during accident conditions such as loss-of-coolant accidents (LOCAs), as shown by Capps et al. To investigate these concerns, advanced modeling and simulation capabilities are under development to determine the susceptibility of HBu fuel to fuel fragmentation, relocation, and dispersion (FFRD). Improvements have previously been made to fuel performance capabilities to model these phenomena more accurately; multiphysics simulations have also been conducted to determine the power and burnup histories of the HBu fuel, which are needed as inputs to the fuel performance calculations. Most recently, new statistical approaches have been developed to identify a subset of fuel rods that have greater FFRD susceptibility, reducing the total number of fuel performance simulations required.
Probing Interactions in Low-Dimensional Systems: Exciton Condensation in SiGe Bilayers.
Abstract not provided.
Exciton condensation and valley splitting in Si/SiGe bilayers.
Abstract not provided.
Aerosol micro-physics in smoke plumes: condensation, coagulation, and deposition
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Applying deep learning methods to develop new models of molecular charge transfer, nonadiabatic dynamics, and nonlinear spectroscopy in the condensed phase
Photon- and field-induced charge transfer has central importance in the generation and storage of electricity, the novel properties of materials, photo-induced catalysis, and electro-optic activity (e.g., photovoltaic cells, fuel cells, and organic chromophores for use in optical fibers and light-emission diodes). These non-equilibrium electronic and chemical transformations are probed by ultrafast, nonlinear spectroscopies. Accurate simulations play a crucial role in our ability to understand, optimize, and control these transformations. This project applies modern deep learning and machine learning (ML) methods to dramatically improve models of electronic dynamics, electronic-nuclear dynamics, and spectroscopic measurements for improved simulations of chemistry in complex environments, far from equilibrium phenomena, and processes in extreme environments, such as materials exposed to strong or resonant fields. This project develops accurate neural net models that go beyond predictive capability to also provide new insight into the fundamental physics underlying electron and nuclear dynamics. To achieve its objectives, this project explores and develops customized versions of high-capacity deep learning algorithms/models. These techniques are developed with an emphasis on fundamental chemical insight, not just predictive accuracy, to assist the development of the next generation of quantum simulation methods.
Investigating spatial variability of aerosol, cloud condensation nuclei, and ice nucleating particles in mountainous terrain
The ASR-supported Surface Atmosphere Integrated field Laboratory (SAIL) in the East River Watershed (ERW) of the Upper Colorado River Basin in southwestern Colorado ran from fall 2021 to spring 2023. Two monitoring sites were deployed in the East River Watershed as part of SAIL. The two sites were the Aerosol Observation System (AOS) located on Crested Butte Ski Mountain, and the ARM Mobile Facility (AMF-2), located at the Rocky Mountain Biological Laboratory in Gothic, Colorado. To gain a more comprehensive understanding of aerosols in complex, mountainous terrain, Handix Scientific deployed SAIL-Net, a distributed network of six measurement nodes spanning the domain of the SAIL research area from October 2021 to July 2023. Each node measured aerosol particles between 140 nm and 3.4 μm in diameter using a small particle counter (POPS, (Gao et al., 2016)), CNN using a miniature CCN counter (CloudPuck), and INP using the Time-Resolved Aerosol Filter Sampler (TRAPS, Creamean et al. (2018)). Our approach was similar to other studies that aimed to better characterize and understand aerosols and gas-phase pollutants using networks of lower-cost sensors (Caubel et al., 2019; Kelly et al., 2021; Asher et al., 2022). Such studies have identified neighborhood-level variations in pollutant concentrations (Schneider et al., 2017; Popoola et al., 2018; Caubel et al., 2019). Small-scale variations such as this are poorly represented in models and poorly measured by a single monitoring system (Caubel et al., 2019). Previous work has shown the representation error (the ability of measurements to represent a larger area) increases with complex orography, leading to decreases in model accuracy (Schutgens et al., 2017). The overall goal of SAIL-Net was to improve our understanding of the variability of aerosol in ERW, thus increasing our knowledge of aerosol-cloud interactions in this region and informing the usefulness of distributed networks of measurements for future studies.
Probing Condensed-Phase Structure and Dynamics in Hierarchical Zeolites and Nanosheets for Catalytic Upgradation of Biomass (Final Report)
Understanding complex reaction pathways in systems governed by multi-scale collective interactions across time and length scales remains a central scientific challenge. This project was guided by the hypothesis that the interplay among oligomers, solvents, and active sites can be tuned by a suitable choice of solvation environment and pore architecture in solid-acid catalysts to direct chemical transformations relevant to biomass conversion. Zeolites and zeolite nanosheets were used as model platforms, allowing for the interaction of macromolecules with the surface of the zeolite nanosheets and with smaller pores that host catalytically active sites. To investigate these coupled phenomena, we employ a multi-scale computational framework that integrates molecular-level descriptions with advanced sampling approaches to capture key physical and chemical interactions. Our work through this project improved fundamental understanding of how reactants and solid-acid catalysts interact in solvent-rich environments, thereby enabling the rational design of catalytic systems that upgrade biomass with enhanced selectivity and energy efficiency. In addition, the project developed advanced sampling methodologies critical for disentangling complex, reactive processes in multi-component catalytic environments.
Shunt-Connected FACTS and Synchronous Condensers
In recent years, the electric-transmission system has undergone a significant transformation marked by a greater integration of renewable-energy sources like wind and solar, the phasing out of thermal generation plants, and a concerted effort towards electrifying energy consumption. To keep pace with the integration of renewable-energy sources and the escalating demands of industries and households, it is imperative to expand and modernize the existing power infrastructure. These upgrades are essential to maintain grid stability, enhance power delivery, and boost overall efficiency of the system. However, challenges have emerged with the growing complexity of power grids, particularly in the realms of voltage control, transient stability, and power-quality management.
Water condensation in unsaturated mineral-organic assemblages - Nano-FTIR
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Detection of Polar Compounds Condensed on Particulate Matter Using Capillary Electrophoresis-Mass Spectrometry
A new analytical method to aid in the understanding of the organic carbon (OC) phase of particulate matter (PM) from advanced compression ignition (ACI) operating modes, is presented. The presence of NO2 and unburned fuel aromatics in ACI emissions, and the low exhaust temperatures that result from this low temperature combustion strategy, provide the right conditions for the formation of carboxylic acids and nitroaromatic compounds. These polar compounds contribute to OC in the PM and are not typically measured using nonpolar solvent extraction methods such as the soluble organic fraction (SOF) method. The new extraction and detection method employs capillary electrophoresis with electrospray ionization mass spectrometry (CE-ESI MS) and was specifically developed to determine polar organic compounds in the ACI PM emissions. The new method identified both nitrophenols and aromatic carboxylic acids in the ACI PM. The ACI air-fuel stratification mode and NOx emissions were found to correlate with the presence and amount of the individual polar species identified.
Condensation in Pyro-cumulonimbus Outflow Explains Large Stratospheric Smoke Mass Injection and Thickly Coated Black Carbon
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Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Summer 2017
Eastern North Atlantic (ENA) Aerosol Mask (ENA-AM) is a mask developed to isolate high concentration aerosol events and identify the regional baseline in one minute time resolution CPC measurements collected at ENA central site during summer 2017(July 22 to August 20). ENA-AM is based on the statistically different behavior of adjacent data points during background and pollution peaks measurements. Measurements that differ by more than α times the standard deviation (σm) of the data below the median plus the two points after are masked by ENA-AM.
Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Winter 2017
Eastern North Atlantic (ENA) Aerosol Mask (ENA-AM) is a mask developed to isolate high concentration aerosol events and identify the regional baseline in one minute time resolution CPC measurements collected at ENA central site during Winter 2017(December 1-30). ENA-AM is based on the statistically different behavior of adjacent data points during background and pollution peaks measurements. Measurements that differ by more than α times the standard deviation (σm) of the data below the median plus the two points after are masked by ENA-AM.