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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

Geochemical Modeling Using OLI Systems Mixed Solvent Electrolyte Model in Support of the Waste Isolation Pilot Plant

Aqueous electrolyte thermodynamic models were developed for synthetic Salado (GWB) and Castile (ERDA-6) brines to inform the experimental design and to facilitate laboratory data interpretation in geochemical studies supporting disposal in the Waste Isolation Pilot Plant (WIPP). The thermodynamic models, which include the relevant vapor-liquid-solid equilibria for the oxidation-reduction conditions of interest, enable computation of system parameters such as activity-based pH, E h [vs. standard hydrogen electrode (SHE)], ionic strength, total dissolved solids, and solution density; the chemical speciation of all phases; saturation tendencies for thermodynamically feasible solids; and changes in brine chemistry because of the addition of H 2 (g), argon, MgO, Fe(0), and other waste form components. The impacts of oxidation-reduction potential (ORP) and pH on aqueous speciation and dominant solid phases were also assessed with the aid of real-solution Pourbaix diagrams for key elements of interest. In addition to the OLI modeling results, limited measurement data for pH and ORP standards are provided, analyzed, and discussed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Leveraging AI and Spatial Data to Unlock Pipeline Integrity Insights: NETL’s Advanced Infrastructure Integrity Model (AIIM)

Maintaining the integrity of natural gas infrastructure plays a critical role in ensuring energy security. Robust, data-driven foundational AI models for pipeline integrity can help address risk management and mitigation issues. Trusted foundational models can help with industry adoption and accelerate innovation by enhancing integrity predictions, reduce costs, and informing infrastructure build-out. The AIIM dashboard was released in 2022 and utilizes multi-ML models for ensemble-type insights. It was expanded to include analytics on reported incidents. It was developed as an ESRI Dashboard to support data visualization & interrogation and contains pipeline data and model results.

Advanced Infrastructure Integrity Model (AIIM)↗

Utilizing AI and Spatial Data to Identify & Rapidly Disseminate Energy Infrastructure Insights

GeoGov Summit Final Presentation entitled "Utilizing AI and Spatial Data to Identify & Rapidly Disseminate Energy Infrastructure Insights". Maintaining the integrity of energy infrastructure plays a critical role in ensuring energy security. Robust foundational AI models using data from federal, state, industry, and other sources can help address integrity risk management & mitigation issues as well as evaluate extended use strategies. Trusted foundational models can help with industry adoption and accelerate innovation by enhancing integrity predictions, reduce costs, and informing infrastructure build-out. Coordination, collaboration & data sharing to develop robust models to aid in: Optimizing operations; Minimizing costs; Ensuring energy security.

Advanced Infrastructure Integrity Model (AIIM)↗

Evaluating Compliance Inspection Data to Understand Emissions from Marginal Conventional Oil & Gas Wells in New York State

It is estimated that over half (~66%) of active oil and gas wells are marginally productive, producing less than 15 barrels of oil equivalent per day. This presentation showcases an evaluation of New York State compliance inspection reports and discusses the current capabilities of machine learning to identify high-risk MCWs that could be targeted during methane emission reduction efforts and future model deployments. Findings are valuable to the New York Department of Environmental Conservation and other state oil and gas regulatory agencies seeking to prioritize the spending of Methane Emission Reduction Program funds to plug marginal conventional wells with emissions.

compliance inspection data↗

ICARUS: new voyage to sterile neutrino search in the Short Baseline Program

The ICARUS collaboration operated the 760-ton T600 detector in a successful three-year physics run at the underground LNGS laboratories studying neutrino oscillations with the CNGS neutrino beam from CERN, and searching for atmospheric neutrino interactions. ICARUS performed a sensitive search for LSND-like anomalous νe appearance in the CNGS beam, which contributed to the constraints on the allowed parameters to a narrow region around $Δm^2=1 e\text{V}^2$, where all the experimental results can be coherently accommodated at 90% C.L. After a significant overhaul at CERN, the T600 detector has been installed at Fermilab. In 2020 cryogenic commissioning began with detector cool down, liquid Argon filling and recirculation. ICARUS has started operations and is presently in its commissioning phase with the aim of collecting its first neutrino events from the Booster Neutrino Beam and the NuMI off-axis beam. The main goal of the first year of ICARUS data taking will then be the definitive verification of the recent claim by NEUTRINO-4 short baseline reactor experiment both in the $ν_μ$ channel with the BNB and in the $ν_e$ with NuMI. After the first year of operations, ICARUS will commence its search for evidence of a sterile neutrino jointly with the SBND near detector, within the Short Baseline Neutrino (SBN) program. The ICARUS exposure to the NuMI beam will also give the possibility for other physics studies such as light dark matter searches and neutrino-Argon cross section measurements. The proposed contribution addresses ICARUS achievements, its status and plans for the new run at Fermilab and the ongoing developments of the analysis tools needed to fulfill its physics program.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Small Particle Aerosol Exposure of African Green Monkeys to MERS-CoV as a Model for Highly Pathogenic Coronavirus Infection

Emerging coronaviruses are a global public health threat because of the potential for person-to-person transmission and high mortality rates. Middle East respiratory syndrome coronavirus (MERS-CoV) emerged in 2012, causing lethal respiratory disease in $\gg$35% of cases. Primate models of coronavirus disease are needed to support development of therapeutics, but few models exist that recapitulate severe disease. For initial development of a MERS-CoV primate model, 12 African green monkeys were exposed to 10 3 , 10 4 , or 10 5 PFU target doses of aerosolized MERS-CoV. We observed a dose-dependent increase of respiratory disease signs, although all 12 monkeys survived for the 28-day duration of the study. This study describes dosedependent effects of MERS-CoV infection of primates and uses a route of infection with potential relevance to MERSCoV transmission. Aerosol exposure of African green monkeys might provide a platform approach for the development of primate models of novel coronavirus diseases.

59 BASIC BIOLOGICAL SCIENCES↗

High deuteron and neutron yields from the interaction of a petawatt laser with a cryogenic deuterium jet

A compact high-flux, short-pulse neutron source would have applications from nuclear astrophysics to cancer therapy. Laser-driven neutron sources can achieve fluxes much higher than spallation and reactor neutron sources by reducing the volume and time in which the neutron-producing reactions occur by orders of magnitude. We report progress towards an efficient laser-driven neutron source in experiments with a cryogenic deuterium jet on the Texas Petawatt laser. Neutrons were produced both by laser-accelerated multi-MeV deuterons colliding with Be and mixed metallic catchers and by d (d,n) 3 He fusion reactions within the jet. We observed deuteron yields of 10 13 /shot in quasi-Maxwellian distributions carrying ~8-10% of the input laser energy. We obtained neutron yields greater than 10 10 /shot and found indications of a deuteron-deuteron fusion neutron source with high peak flux (>10 22 cm -2 s -1 ). The estimated fusion neutron yield in our experiment is one order of magnitude higher than any previous laser-induced dd fusion reaction. Though many technical challenges will have to be overcome to convert this proof-of-principle experiment into a consistent ultra-high flux neutron source, the neutron fluxes achieved here suggest laser-driven neutron sources can support laboratory study of the rapid neutron-capture process, which is otherwise thought to occur only in astrophysical sites such as core-collapse supernova, and binary neutron star mergers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Arabidopsis thaliana EARLY RESPONSIVE TO DEHYDRATION 7 Localizes to Lipid Droplets via Its Senescence Domain

Lipid droplets (LDs) are neutral-lipid-containing organelles found in all kingdoms of life and are coated with proteins that carry out a vast array of functions. Compared to mammals and yeast, relatively few LD proteins have been identified in plants, particularly those associated with LDs in vegetative (non-seed) cell types. Thus, to better understand the cellular roles of LDs in plants, a more comprehensive inventory and characterization of LD proteins is required. Here, we performed a proteomics analysis of LDs isolated from drought-stressed Arabidopsis leaves and identified EARLY RESPONSIVE TO DEHYDRATION 7 (ERD7) as a putative LD protein. mCherry-tagged ERD7 localized to both LDs and the cytosol when ectopically expressed in plant cells, and the protein’s C-terminal senescence domain (SD) was both necessary and sufficient for LD targeting. Phylogenetic analysis revealed that ERD7 belongs to a six-member family in Arabidopsis that, along with homologs in other plant species, is separated into two distinct subfamilies. Notably, the SDs of proteins from each subfamily conferred targeting to either LDs or mitochondria. Further, the SD from the ERD7 homolog in humans, spartin, localized to LDs in plant cells, similar to its localization in mammals; although, in mammalian cells, spartin also conditionally localizes to other subcellular compartments, including mitochondria. Disruption of ERD7 gene expression in Arabidopsis revealed no obvious changes in LD numbers or morphology under normal growth conditions, although this does not preclude a role for ERD7 in stress-induced LD dynamics. Consistent with this possibility, a yeast two-hybrid screen using ERD7 as bait identified numerous proteins involved in stress responses, including some that have been identified in other LD proteomes. Collectively, these observations provide new insight to ERD7 and the SD-containing family of proteins in plants and suggest that ERD7 may be involved in functional aspects of plant stress response that also include localization to the LD surface.

54 ENVIRONMENTAL SCIENCES↗

Seventh User Workshop on High-Power Lasers at the Linac Coherent Light Source

We report on a seventh annual workshop in a series focused on science realized by the combination of hard X-ray free electron lasers with high power optical lasers, hosted at the SLAC National Accelerator Laboratory in Menlo Park, CA. Members from the user community of the Matter in Extreme Conditions (MEC) endstation of the Linac Coherent Light Source (LCLS) and other scientists met with local scientists to discuss developments at LCLS and MEC and related facilities, including experimental results and future plans.

47 OTHER INSTRUMENTATION↗

Identification and Characterization of Lipid Droplet-Associated Protein (LDAP) Isoforms from Tung Tree (Vernicia fordii)

Lipid droplets (LDs) are cytoplasmic organelles responsible primarily for the storage of neutral lipids, such as triacyclglycerols (TAGs). Derived from the endoplasmic reticulum bilayer, LDs are composed of a hydrophobic lipid core encased by a phospholipid monolayer and surface-associated proteins. To date, only a relatively few LD ‘coat’ proteins in plants have been identified and characterized, most of which come from studies of the model plant Arabidopsis thaliana. To expand our knowledge of the plant LD proteome, the LD-associated protein (LDAP) family from the tung tree (Vernicia fordii), whose seeds are rich in a commercially valuable TAG containing the conjugated fatty acid α-eleostearic acid (C18:3Δ9cis,11trans,13trans [α-ESA]), was identified and characterized. Based on the tung tree transcriptome, three LDAP isoforms (VfLDAP1-3) were elucidated and the encoded proteins distinctly clustered into three clades along with their respective isoforms from other angiosperm species. Ectopic expression of the VfLDAPs in Nicotiana benthamiana leaves revealed that they localized specifically to LDs and influenced LD numbers and sizes, as well as increasing TAG content and altering TAG fatty acid composition. Interestingly, in a partially reconstructed TAG-ESA biosynthetic pathway, the co-expression of VfLDAP3 and, to a lesser degree, VfLDAP2, significantly increased the content of α-ESA stored within the LDs. These results suggest that the VfLDAPs can influence the steady-state content and composition of TAG in plant cells and that certain LDAP isoforms may have evolved to more efficiently package TAGs into LDs containing unusual fatty acids, such as α-ESA.

Plant Sciences↗

System and method for extracting ethanol from a fermentation broth

The present invention is directed to a system and method for producing an organic compound using fermentation wherein multiple components of the system are recycled within the system. The system and method allow for extraction of a high concentration of the organic compound from the fermentation broth in a continuous system that allows recycling of the biomass, aqueous fermentation broth and extraction solvents. The system and method are particularly well adapted for producing and extracting ethanol.

09 BIOMASS FUELS↗

Assessing Current and Future Infrastructure Hazards

Project Objective Execute intelligent analytics via an advanced analytical framework, to assess the current state of offshore infrastructure, evaluate infrastructure life, and identify technologies to reduce infrastructure hazards, costs, and extend infrastructure life. Approach &amp; Results thus Far• Build comprehensive dataset• Perform data-driven analytics to evaluate infrastructure integrity<p> 1. Remaining lifespan</p><p> 2. Likelihood of future risk</p><p>• Apply data-driven advanced spatial, statistical, and Machine Learning (ML) models to quantify existing infrastructure integrity</p><p>• Release data and models through a smart, online platform hosted by Energy Data eXchange (EDX)</p>

Romeo, Lucy F.↗

Infrastructure and Metocean Technology

<strong>Research Problem: </strong>Changes in the ocean environment (i.e., mudslides or burial from subsea currents, strong weather events or natural fluctuations) have been linked to <strong>billions of dollars of impacts</strong>. These events can have a significant effect on the <strong>success and longevity </strong>of offshore infrastructure, as well as affect <strong>safety and cost </strong>during exploration and production activities.<strong>Research Approach: (1) </strong>Determine current state of knowledge regarding hazardous metocean and bathymetric conditions, and data availability regarding these conditions and historic events. (2) EY19 -Evaluate if Ml/AI model can be developed to better identify current hazardous metocean and bathymetric conditions. (3) EY 20 + -develop, train, and test ML/AI model to identify current conditions and forecast changes and vulnerability that may impact offshore infrastructure and operations. <strong>Benefit: </strong>Improved characterization of seabed related hazards in the offshore environment will help to manage and minimize costs and risks during drilling and production operations, and help prevent catastrophic incidents.

Duran, Rodrigo↗