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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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28 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Optimizing Sub-Sampled STEM Imaging for Beam Sensitive Materials and Dynamic Processes

The goal of this research is to quantify how sub-sampling and inpainting (broadly classified as methods in Artificial Intelligence) can be used to obtain the highest resolution images under any experimental conditions, and to use this to reproducibly control dynamic in-situ processes in gases and liquids on the nanoscale. As atomic diffusion under non-extreme conditions is typically in the sub-ms time domain, the ability to use this sub-sampling approach to reduce the effect of the electron beam and to speed-up the imaging process represents the optimum combination of spatial and temporal resolution achievable in a conventional microscope. This LDRD funding demonstrated the feasibility of imaging dynamics in complex energy systems using this methodology by establishing the optimum experimental sampling conditions (optimizing the number of pixels, speed, contrast and resolution) for each experiment. For in-situ liquid cell experiments this analysis shows that simply by distributing the same dose and dose rate maximally in space and time, the kinetics for radiolysis products can be modified significantly. The final stage of this work, i.e. the experimental demonstration of its use for nucleation and growth, was severely curtailed by issues with COVID19. However, all the experiments are designed and currently underway, with the goal to complete the final demonstration and publication as soon as safety concerns for laboratory access are met.

36 MATERIALS SCIENCE↗
DOE OSTI2022

SMC Reinforced by Recycled or Textile Carbon Fiber

There is a significant need to expand material options for SMC that has traditionally used glass fibers for decades. There are several integral issues related to chopping and conveying a range of materials including glass, carbon, basalt, thermoplastic tapes, and recycled fibers. These are in a variety of forms including continuous tows, discontinuous agglomerates such as pyrolyzed carbon fibers that could be used to produce a range of SMC intermediates. Standard/conventional SMC processing is limited to cutting rotors specifically for glass and compounding with thermoset polyesters and some epoxies. The multi-material, multi-format line developed in this project is flexible to enable custom conveying and uses an interchangeable rotor dedicated for specific material types. The overall tasks undertaken in this project included: evaluation of the fiber feed mechanism, effect of textile grade carbon, evaluating servo motor controlling of conveyor, evaluate doctor box resin feed, evaluate compaction unit, evaluation of different formulations, and develop automation such as PLC programming. The new multi-material SMC line Version 2 (SCM-V2) incorporated servo motors over induction motors which gave the overall cutter system precision control and made it quiet. The addition of a 14-roll compaction unit at the end of the line in SMC-V2 enabled higher material wet out which was a limitation in the SMC Version 1 (SMC-V1). The cutters were further updated to reduce the cantilever overhang of the fiber which enabled more uniform cut lengths for glass, carbon, and basalt fibers. The overall instrumentation and system control including a remote control operation was enabled in the SMC-V2. The line speed is capable of 10-20 ft/minute. The cutting modules were designed and engineered for cutting glass, basalt and textile grade carbon in 300k and 450-600k format widths. The cutting trials were established for a range of fiber types. The study also demonstrated the utility of the line to cut and produce basalt fiber SMC. Initial trials were conducted on the properties from recycled carbon fiber (rCF) mats in epoxy resin. Overall, the Covid19 situation constrained the team from accessing the SMC line for over 18 months. Despite this challenge major advancements were made.

36 MATERIALS SCIENCE↗
NASA NTRS2021

First Measurements of Ambient PM2.5 in Kinshasa, Democratic Republic of Congo and Brazzaville, Republic of Congo Using Field-calibrated Low-cost Sensors

Estimates of air pollution mortality in sub-Saharan Africa are limited by a lack of surface observations of fine particulate matter (PM2.5). Despite being large metropolises, Kinshasa, Democratic Republic of the Congo (DRC), population 14.3 million, and Brazzaville, Republic of the Congo (ROC), population 2.4 million, have no reference air pollution monitors at the time of writing. Recently, a few reference monitors have been deployed in other parts of sub-Saharan Africa, including Kampala, Uganda. A low-cost PurpleAir PM2.5 monitor was collocated next to the Kampala US Embassy BAM-1020 (Met One Beta Attenuation Monitor) starting in August 2019. Raw PurpleAir data are strongly correlated with the BAM (r(exp 2) = 0.88), but have a mean absolute error of approximately 14 μg/cu.m. Two calibration models, multiple linear regression and a random forest approach, decrease mean absolute error (MAE) from 14.3 μg/cu.m to 3.4 µg/cu.m or less and improve the the r(exp 2) from 0.88 to 0.96. Given )the similarity in climate and emissions in Kampala, we apply the collocated field correction factors to four PurpleAir sensors in Kinshasa, DRC and one in neighboring Brazzaville, ROC deployed beginning April 2018. Annual average PM2.5 for 2019 in Kinshasa is estimated at 43.5 µg/cu.m, more than 4 times higher than WHO Interim Target 1 of 10 µg/cu.m. Surface PM2.5 and aerosol optical depth were each about 40% lower during the 2020 COVID19 lockdown period compared to the same time period in 2019, which cannot be explained by changes in meteorology or wildfire emissions alone. Our results highlight the need for clean air solutions implementation in the Congo.

Celeste McFarlane↗
DOE OSTI2020

MRT (Medical Reporting Tracker)

Medical Report Tracker (MRT) was created to respond to COVID19 data, process and analytic needs of our clinic staff. The report tracker captures data around symptoms and contacts, test results, and last work date and location. The MRT is built using Nintex Online, SharePoint Online and Power BI/Excel.

Devitt, Carrie↗
DOE OSTI2022

Scanning the RBD-ACE2 molecular interactions in Omicron variant

The emergence of new SARS-CoV-2 variants poses a threat to the human population where it is difficult to assess the severity of a particular variant of the virus. Spike protein and specifically its receptor binding domain (RBD) which makes direct interaction with the ACE2 receptor of the human has shown prominent amino acid substitutions in most of the Variants of Concern. Here, in this work, by using all-atom molecular dynamics simulations we compare the interaction of Wild-type RBD/ACE2 receptor complex with that of the latest Omicron variant of the virus. We observed a very interesting diversification of the charge, dynamics and energetics of the protein complex formed upon mutations. These results would help us in understanding the molecular basis of binding of the Omicron variant with that of SARS-CoV-2 Wild-type.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Identification of inhibitors against SARS-CoV-2 variants of concern using virtual screening and metadynamics-based enhanced sampling

Among the variants of SARS-CoV-2, some are more infectious than the Wild-type. Interestingly, these mutations enable the virus to evade the therapeutic efforts. Hence, there is a need for candidate drug molecules that can potently bind with all the variants. Here we have adopted a strategy combining virtual screening, molecular docking followed by rigorous sampling by metadynamics simulations to find candidate molecules. From our results we found four highly potent drug candidates that can bind to the Spike-RBD of all the variants of the virus. Additionally, we also found that certain signature residues on the RBM region commonly bind to each of these inhibitors. Thus, our study not only gives information on the chemical compounds, but also residues on the proteins which could be targeted for future drug and vaccine development studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics

We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spike’s full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Using intrahost single nucleotide variant data to predict SARS-CoV-2 detection cycle threshold values

Over the last four years, each successive wave of the COVID-19 pandemic has been caused by variants with mutations that improve the transmissibility of the virus. Despite this, we still lack tools for predicting clinically important features of the virus. In this study, we show that it is possible to predict the PCR cycle threshold (Ct) values from clinical detection assays using sequence data. Ct values often correspond with patient viral load and the epidemiological trajectory of the pandemic. Using a collection of 36,335 high quality genomes, we built models from SARS-CoV-2 intrahost single nucleotide variant (iSNV) data, computing XGBoost models from the frequencies of A, T, G, C, insertions, and deletions at each position relative to the Wuhan-Hu-1 reference genome. Our best model had an R 2 of 0.604 [0.593–0.616, 95% confidence interval] and a Root Mean Square Error (RMSE) of 5.247 [5.156–5.337], demonstrating modest predictive power. Overall, we show that the results are stable relative to an external holdout set of genomes selected from SRA and are robust to patient status and the detection instruments that were used. This study highlights the importance of developing modeling strategies that can be applied to publicly available genome sequence data for use in disease prevention and control.

COVID19↗
DOE OSTI2021

The SARS-CoV-2 Spike Variant D614G Favors an Open Conformational State

The COVID-19 pandemic underwent a rapid transition with the emergence of a dominant viral variant (from the “D-form” to the “G-form”) that carried an amino acid substitution D614G in its “Spike” protein. The G-form is more infectious in vitro and associated with increased viral loads. To gain insight into the molecular-level underpinnings of these characteristics, we employed microsecond all-atom simulations. Here we show that changes in the protein energetics favor a higher population of infection-capable (open) states through release of hydrogen bonds of an asymmetry present in the D-form but not the G-form. Thus, the increased infectivity of the G-form is likely due to a higher rate of profitable binding encounters with the host receptor. It is also predicted to be more neutralization sensitive due to enhanced exposure of the receptor binding domain, a key target region for neutralizing antibodies. These results are significant for vaccine design. The Molecular Dynamics Simulations datasets generated in this study, namely that of the soluble form SARS-CoV-2 Spike protein are made available here. Details of the trajectory and supporting files are given in the README.txt file.

59 BASIC BIOLOGICAL SCIENCES↗