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Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models (Final Report)

Laity, George R.; Robinson, Allen C.; Cuneo, M.E.; Alam, Mary K.; Beckwith, Kristian B.; Bennett, Nichelle L.; Bettencourt, Matthew T.; Bond, Stephen D.; Cochrane, Kyle C.; Criscenti, Louise C.; Cyr, Eric C.; Laros, James H.; Drake, Richard R.; Evstatiev, Evstati G.; Fierro, Andrew S.; Gardiner, Thomas A.; Laros, James H.; Goeke, Ronald S.; Hamlin, Nathaniel D.; Hooper, Russell H.; Koski, Jason K.; Lane, James M.; Larson, Steven R.; Leung, Kevin L.; McGregor, Duncan A.; Miller, Philip R.; Miller, Sean M.; Ossareh, Susan J.; Phillips, Edward G.; Simpson, Sean S.; Sirajuddin, David S.; Smith, Thomas M.; Swan, Matthew S.; Thompson, Aidan P.; Tranchida, Julien G.; Bortz-Johnson, Asa J.; Welch, Dale R.; Russell, Alex M.; Watson, Eric D.; Rose, David V.; McBride, Ryan D.

This report describes the high-level accomplishments from the Plasma Science and Engineering Grand Challenge LDRD at Sandia National Laboratories. The Laboratory has a need to demonstrate predictive capabilities to model plasma phenomena in order to rapidly accelerate engineering development in several mission areas. The purpose of this Grand Challenge LDRD was to advance the fundamental models, methods, and algorithms along with supporting electrode science foundation to enable a revolutionary shift towards predictive plasma engineering design principles. This project integrated the SNL knowledge base in computer science, plasma physics, materials science, applied mathematics, and relevant application engineering to establish new cross-laboratory collaborations on these topics. As an initial exemplar, this project focused efforts on improving multi-scale modeling capabilities that are utilized to predict the electrical power delivery on large-scale pulsed power accelerators. Specifically, this LDRD was structured into three primary research thrusts that, when integrated, enable complex simulations of these devices: (1) the exploration of multi-scale models describing the desorption of contaminants from pulsed power electrodes, (2) the development of improved algorithms and code technologies to treat the multi-physics phenomena required to predict device performance, and (3) the creation of a rigorous verification and validation infrastructure to evaluate the codes and models across a range of challenge problems. These components were integrated into initial demonstrations of the largest simulations of multi-level vacuum power flow completed to-date, executed on the leading HPC computing machines available in the NNSA complex today. These preliminary studies indicate relevant pulsed power engineering design simulations can now be completed in (of order) several days, a significant improvement over pre-LDRD levels of performance.

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Photocatalytic Material Surfaces for SARS-CoV-2 Virus Inactivation

Negrete, Oscar N.; Bradfute, Steven; Larson, Steven R.; Sinha, Anupama S.; Coombes, Kenneth R.; Goeke, Ronald S.; Keenan, Lisa A.; Duay, Jonathon W.; Van Heukelom, Michael V.; Meserole, Stephen M.; Jacobs-Gedrim, Robin B.

Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) can be spread through close contact or through fomite mediated transmission. This study details the fabrication and analysis of a photocatalyst surface which can rapidly inactivate SARS-COV-2 to limit spread of the virus by fomite mediated transmission. The surface being developed at Sandia for this purpose is a minimally hazardous Ag-Ti0 2 nanomaterial which is engineered to have high photocatalytic activity. Initial results at Sandia California in a BSL-2 safe surrogate virus- Vesicular Stomatitis Virus (VSV) show a significant difference between the photocatalyst material under exposure to visible light than controls. Additionally, UV-A light (365 nm) was found to eliminate SARS-COV-2 after 9 hours on all tested surfaces with irradiance of 15 mW/cm 2 equivalent to direct circumsolar irradiance.

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5 Results
5 Results