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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 19 records

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

59 BASIC BIOLOGICAL SCIENCES↗

Testing a novel peptide drug towards a goal of reducing mortality in critically ill COVID19 patients

COVID 19 has been devastating the globe over the past year, and although our knowledge of how the disease progresses is constantly evolving, there is a significant amount we now about the mechanisms underlying COVID19. There is growing evidence that a 'cytokine storm' is a significant driver of mortality associated with COVID19, with studies showing high levels of hallmark inflammatory indicators in critically ill COVID19 patients. This essentially consists of the patient's immune system going awry and causing white blood cells to constantly release a large number of small molecules called cytokines. The result of this is further activation of the immune system, which ends up attacking not only infected but also healthy patient tissues, resulting in organ failure.

59 BASIC BIOLOGICAL SCIENCES↗

A modeling framework for designing and evaluating curbside traffic management policies at Dallas-Fort Worth International Airport

Emerging mobility technologies are changing the transportation system landscape. This is especially evident at airports, such as the Dallas-Fort Worth International Airport (DFW). Without careful analysis, these changes could lead to inefficient and costly airport operations. This paper presents a modeling framework that integrates travel mode encoding, demand projection, and microsimulation to enable airports to develop, simulate, and evaluate curbside traffic managements policies and measure their impact. Here, the framework is utilized to analyze several traffic scenarios and policies for DFW: a baseline scenario which represents DFW traffic pattern as observed in 2018 and projected to 2045, a transit network company (TNC) electrification policy, a TNC queuing policy, a policy that increased transit ridership, a bus-only policy which considers the use of only buses inside DFW, an autonomous vehicle (AV) policy which investigates the impact of autonomous vehicle (AV) adoption on airport operations, and an example COVID-19 scenario which models the impact of the COVID19 pandemic. The simulations’ results demonstrate that: increasing the DFW transit ridership postpones the need for airport curbside expansion the most; encouraging shared-mobility with the bus-only policy produces the most savings in curbside congestion delays; automation and electrification for all passenger vehicle trips to/from DFW generates the most saving in fuel consumption and emissions; and uncontrolled AV adoption incurs the highest increase in fuel consumption, delay, and emissions and could require immediate airport capacity extension. Without policy intervention or investment in additional infrastructure capacity, these results predict the current operations would face significant congestion on high demand days starting as early as 2028. While derived in close partnership with DFW, the methodology presented here can be generalized to any airport.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantitative methods and modeling to assess COVID–19–interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches

The coronavirus disease 2019 (COVID-19) has presented unprecedented challenges to the generic drug development, including interruptions in bioequivalence (BE) studies. Per guidance published by the US Food and Drug Administration (FDA) during the COVID-19 public health emergency, any protocol changes or alternative statistical analysis plan for COVID-19-interrupted BE study should be accompanied with adequate justifications and not lead to biased equivalence determination. In this study, we used a modeling and simulation approach to assess the potential impact of study outcomes when two different batches of a Reference Standard (RS) were to be used in an in vivo pharmacokinetic BE study due to the RS expiration during the COVID-19 pandemic. Simulations were performed with hypothetical drugs under two scenarios: (1) uninterrupted study using a single batch of an RS, and (2) interrupted study using two batches of an RS. The acceptability of BE outcomes was evaluated by comparing the results obtained from interrupted studies with those from uninterrupted studies. The simulation results demonstrated that using a conventional statistical approach to evaluate BE for COVID-19-interrupted studies may be acceptable based on the pooled data from two batches. An alternative statistical method which includes a “batch” effect to the mixed effects model may be used when a significant “batch” effect was found in interrupted four-way crossover studies. However, such alternative method is not applicable for interrupted two-way crossover studies. Overall, the simulated scenarios are only for demonstration purpose, the acceptability of BE outcomes for the COVID19-interrupted studies could be case-specific.

60 APPLIED LIFE SCIENCES↗

Solar Ready Vets: Recruiting and Retaining Military Talent in the Solar Workforce

The solar industry stands to benefit from a more diverse, robust and resilient workforce as we continue to emerge from COVID19 disruptions and expand our industry’s role as a mainstream part of the American energy sector. Veterans and transitioning service members have strong leadership experience and critical thinking skills that make them outstanding candidates for solar careers in today’s fast-changing world. This session will inform solar companies about how they can engage with the U.S. Department of Energy funded Solar Ready Vets Network and the Solar Ready Vets Corporate Fellowship Program, which are expanding and strengthening a nationwide pipeline of transitioning military service members and veterans into technical and leadership roles in the American solar workforce.

14 SOLAR ENERGY↗

Bioscience COVID Rapid Response Report

The COVID-19 disease outbreak and its impact on global health and economies have highlighted the national security threat posed by pathogens with pandemic potential and the need for rapid development of effective diagnostics and medical countermeasures. The Bioscience IA selected for funding rapid COVID LDRD project proposals that addressed critical R&D gaps in pandemic response that could be accomplished in 1-3 months with the requested funding. In total, the Bioscience IA funded nine rapid projects that addressed 1) rapid and accurate methods for SARS-CoV-2 RNA detection, 2) modeling tools to help prioritize populations for diagnostic testing, 3) bioinformatic tools to track SARS-CoV-2 genomic sequence changes over time, 4) molecular inhibitors of SARS-CoV-2 cellular infection, and 5) method for rapid staging of COVID19 disease to enable administration of more effective treatments. In addition, LDRD funded one larger project to be completed in FY21 that leverages Sandia capabilities to address the need for platform diagnostics and therapeutics that can be rapidly tailored against emerging pathogen targets.

59 BASIC BIOLOGICAL SCIENCES↗

Adaptive Recovery Model: Designing Systems for Testing Tracing and Vaccination to Support COVID-19 Recovery Planning.

This report documents a new approach to designing disease control policies that allocate scarce testing, contact tracing, and vaccination resources to better control community transmission of COVID19 or similar diseases. The Adaptive Recovery Model (ARM) combines a deterministic compartmental disease model with a stochastic network disease propagation model to enable us to simulate COVID-19 community spread through the lens of two complementary modeling motifs. ARM contact networks are derived from cell-phone location data that have been anonymized and interpreted as individual arrivals to specic public locations. Modeling disease spread over these networks allows us to identify locations within communities conducive to rapid disease spread. ARM applies this model- and data-derived abstractions of community transmission to evaluate the effectiveness of disease control measures including targeted social distancing, contact tracing, testing and vaccination. The architecture of ARM provides a unique capacity to help decision makers understand how best to deploy scarce testing, tracing and vaccination resources to minimize disease-spread potential in a community. This document details the novel mathematical formulations underlying ARM, presents a dynamical stability analysis of the deterministic model components, a sensitivity analysis of control parameters and network structure, and summarizes a process for deriving contact networks from cell-phone location data. An example use case steps through applying ARM to evaluate three targeted social distancing policies using Bernalillo County, New Mexico as an exemplar test locale. This step-by-step analysis demonstrates how ARM can be used to measure the relative performance of competing public health policies. Initial scenario tests of ARM shows that ARMs design focus on resource utilization rather than simple incidence prediction can provide decision makers with additional quantitative guidance for managing ongoing public health emergencies and planning future responses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantitative form and fit of N95 filtering facepiece respirators are retained after dry and humid heat treatments for coronavirus deactivation

Re-use of filtering facepiece respirators (FFRs, commonly referred to as N95s) normally meant for single use only is becoming common in healthcare facilities due to shortages caused by the COVID19 pandemic. Here we report that mouse hepatitis virus (MHV) initially seeded on FFR filter material is inactivated (6 log reduction as measured by 50% tissue culture infective dose (TCID50)) after dry heating at 75 °C for 30 minutes. We also find that the quantitative fit of FFRs after heat treatment at this temperature, under dry conditions or at 90% relative humidity, is not affected by single or ten heating cycles. Previous studies have reported that the filtration efficiency of FFR filters is not negatively impacted by these heating conditions. These results suggest that thermal inactivation of coronaviruses is a potentially rapid and widely deployable method to re-use N95 FFRs in emergency situations where reusing FFRs is a necessity and broad-spectrum sterilization is unavailable. However, we also found that a heat source that emits radiation (e.g., an exposed heating element) results in rapid qualitative degradation of the FFR. Finally, we discuss differences in the results reported here and other recent studies investing heat as a means to recycle FFRs and suggest that overall wear time and donning/doffing cycles are important factors that need to be considered.

36 MATERIALS SCIENCE↗

Collaborative VR/AR Data Visualization Tool

This is the final report on Phase II SBIR for the development of a collaborative VR data visualization tool. In the 15 months of the Phase II, we have met and exceeded most objectives that we outlined for ourselves in the proposal. COVID19 has caused us to do some thing differently, but in fact the outcome is better for the development - we were meant to have traveled to institutions in the UK and EU to show the capabilities in April, but instead we have got into an iterative cycle in-house of weekly testing of the new features and functions. This is working well, so we will soon have the ability to share the application with collaborators in remote locations, without the need to travel. We are also making short videos of the features to share with those afar, again mitigating the need to travel and demonstrate in-person our new capabilities. That said, we are behind on getting input from the Beta testers, but when we do get their input it will be to test features and functions that are working, and not failing due to some glitch, which in turn will more likely lead to the acceptance of the product. One of our goals is to have a near-term commercial product, and we are tantalizingly close to it with commercial interest from LANL, Survice and other entities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Metal (Cu,Al)/CNT Composite Wires for Energy Efficient Motors

This report summarizes the main results of research project on Metal/CNT nanocomposites conducted at University of Central Florida (UCF). It should be noted that the project was budgeted for three years, but the budget period 3 was unfortunately not funded and conducted in COVID19 pandemic years due to many reasons. The demonstration plan on the small motors was also removed according to the discussion with the DOE program manager. All research activities were focused on the (Cu,Al)/CNT material development and wire extrusion. Existing methods to fabricate Metal/CNTs were usually suffering from agglomeration of CNTs due to their density and stiffness differences. A new method is studied by the UCF research team, where CNTs are surface treated firstly, then coated with pure metals (i.e., Al, Cu, and Nickle). The metal encapsulation on CNT is expected to significantly improve the interfacial bonding between CNTs and the intimated metal matrices. The coated CNT powders were used to make sample materials through sintering, then a customized wire extrusion process was employed to fabricate wires. Measurement of material property improvements in mechanical strength, thermal conductivity, and electrical conductivity were conducted on both cylinder samples and extruded wires. In addition to the sintering process, casting on metal coated CNT powder was also investigated. The best results we achieved are summarized as follows. (1) The measured thermal conductivity of Al/CNT composite made with Ni-encapsulated CNTs and pure Al powders is about 85% better than that of pure aluminum fabricated. The measured electrical conductivity of fabricated Al/CNT is about 14-20% better than that of pure aluminum. (2) The measured electrical conductivity of Cu/CNT is about 14.5% better than that of pure copper fabricated. (3) The mechanical strengths of both Cu/CNT and Al/CNT (with about 1% wt. CNTs) are 70% better than pure metals although losing some material ductility. (4) Two-stage wire extrusion at high temperatures were designed and successfully conducted to fabricate wires of Metal/CNTs.

36 MATERIALS SCIENCE↗

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↗

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↗

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↗