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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Screening and Qualification of BME Feedthrough Capacitors for a Space Project

Surface mount technology feedthrough ceramic capacitors are gaining popularity in Hi-Rel systems due to small size and great filtering characteristics. In this work, BME feedthrough capacitors compliant with AEC-Q200 requirements have been evaluated, screened and qualified for a space project. Evaluation included analysis of the effect of post-soldering thermal shocks, temperature dependencies of leakage currents, distribution of breakdown voltages, assessments of high-current capability, and thermal resistance of the parts. The parts have been screened and qualified at conditions close to the military requirements for ceramic capacitors. No failures were detected during screening including burning-in, but two samples failed during monitored 2000 hour life testing at 125C and two times rated voltage. Failure analysis revealed manufacturing defects that required additional analysis of screening and qualification test conditions. Highly accelerated life testing (HALT) has been carried out to assess reliability acceleration factors and the probability of failure at the use conditions. An approach to selection of adequate burning-in and life test conditions is discussed.

Alexander Teverovsky↗
NASA NTRSDate not supplied

High-Throughput Screening of Li Solid-State Electrolytes With Bond Valence Methods and Graph Neural Networks

Li-based solid-state electrolyte (Li-SSE) materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. We present a high-throughput screening approach for Li-SSE materials using a combination of bond-valence methods and graph neural networks. We demonstrate the screening approach with a dataset containing tens of thousands of Li-containing compounds. Furthermore, we combine the machine-learning screening procedure with an isovalent substitution scheme to generate and screen additional Li SSE candidates beyond existing databases. Finally, we discuss relative importances of geometric and bond-valence quantities in the training of graph neural networks, providing insight for future modeling of ionic conductivity in Li-SSE materials.

Materials discovery↗
NASA NTRSDate not supplied

Screening of Li-Based Solid Electrolytes Using Bond-Valence Methods and Graph Neural Networks

Li-based solid-state electrolyte (Li-SSE) materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. We present a high-throughput screening approach for Li-SSE materials using a combination of bond-valence methods and graph neural networks. We demonstrate the screening approach with a dataset containing tens of thousands of Li-containing compounds. Furthermore, we combine the machine-learning screening procedure with an isovalent substitution scheme to generate and screen additional Li SSE candidates beyond existing databases. Finally, we discuss relative importances of geometric and bond-valence quantities in the training of graph neural networks, providing insight for future modeling of ionic conductivity in Li-SSE materials.

Materials discovery↗
DOE OSTI2014

A Screen Space GPGPU Surface LIC Algorithm for Distributed Memory Data Parallel Sort Last Rendering Infrastructures

The surface line integral convolution(LIC) visualization technique produces dense visualization of vector fields on arbitrary surfaces. We present a screen space surface LIC algorithm for use in distributed memory data parallel sort last rendering infrastructures. The motivations for our work are to support analysis of datasets that are too large to fit in the main memory of a single computer and compatibility with prevalent parallel scientific visualization tools such as ParaView and VisIt. By working in screen space using OpenGL we can leverage the computational power of GPUs when they are available and run without them when they are not. We address efficiency and performance issues that arise from the transformation of data from physical to screen space by selecting an alternate screen space domain decomposition. We analyze the algorithm's scaling behavior with and without GPUs on two high performance computing systems using data from turbulent plasma simulations.

Loring, Burlen↗
DOE OSTI2020

Using the Monte Carlo Method to Evaluate the Reliability of Screening Multifamily Housing for Radon

When screening for radon in a multifamily housing complex using a fixed sample density (e.g., testing 1 in 10 (10%) or 1 in 4 units (25%)), the statistical confidence is dependent upon the assumed elevated radon frequency. For example, testing 25% of units in a complex estimated to have eight units with elevated radon levels will provide 90% confidence. However, if it is assumed that, in the same complex, there are only three units with elevated radon levels, the confidence drops to around 58% for the same sample density. Furthermore, in the previous example, if elevated radon levels are not found during the screening, all that can be stated is that the screening provides 90% confidence that there are no more than seven units in the complex with elevated radon levels. To more fully illustrate this uncertainty, ten separate multifamily housing radon data sets with 1 to 10 units with radon levels ≥4 pCi/L (Table 1) were selected for analysis using the Monte Carlo statistical method. Unlike other mathematically based statistical approaches, the Monte Carlo statistical method relies on repeated analysis of randomly selected data. from a 100% sampled complex at various sample densities. Success for each simulation is defined as finding at least one unit with elevated radon levels. In this statistical method, confidence in the overarching conclusion can be greatly enhanced by repeating the simulated screening hundreds or even thousands of times. For this study, each of the ten data sets was simulated 1,000 times. For each simulation, the data set was randomized three times before the fixed percentage of data was selected.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

THERMAL ANALYSIS OF THE RHIC ARC DIPOLE MAGNET COLD MASS WITH THE EIC BEAM SCREEN

The EIC will make use of the existing RHIC storage rings with their superconducting (SC) magnet arcs. A stain-less-steel beam screen with co-laminated copper and a thin amorphous carbon (aC) film on the inner surface will be installed in the beam pipe of the SC magnets. The copper will reduce the beam-induced resistive-wall (RW) heating from operation with the higher intensity EIC beams, that if not addressed would make the magnets quench. Limiting the RW heating is also important to achieve an adequately low vacuum level. The aC coating will reduce secondary electron yield which could also cause heating and limit in-tensity. Among all the RHIC SC magnets, the arc dipoles present the biggest challenge to the design and installation of beam screens. The arc dipoles, which make up for 78% (2.5 km) length of all SC magnets in RHIC, expect the larg-est RW heating due to their smallest aperture. These mag-nets are also the longest (9.45 m each), thus experiencing the largest temperature rise over their length, and have a large sagitta (48.5 mm) that increases the difficulty to in-stall the beam screen in place. This paper presents a de-tailed thermal analysis of the magnet-screen system.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Radon Vapor Intrusion Screening Level Calculator - 17041

The U.S. Environmental Protection Agency has produced a web-based calculator for the assessment of cancer risk from radon in soil, soil gas, and pore water seeping into above-ground buildings. Like the chemical vapor intrusion screening level (VISL) calculator, the radon VISL (RVISL) provides screening levels in subsurface soil and water that are protective of preliminary remediation goals (PRGs) for radon in air that are based on either cancer risk or Applicable or Relevant and Appropriate Requirements (ARARs). In addition to the screening levels calculated, the RVISL can also calculate the risk from radon concentrations in soil, water, and air. The exposure routes evaluated in the RVISL are inhalation and external exposure from submersion in radon. Two source term options are provided for the user: one without radioactive decay and one with decay. Sources continually generating radon (Rn-222 and Rn-220), such as below ground uranium, would best be modeled with the 'without decay' models. Radon is the second leading cause of lung cancer. Radon is released from the normal decay of uranium, thorium, and radium in rocks and soil. It is an invisible, odorless, tasteless gas that seeps up through the ground and diffuses into the air. In areas without adequate ventilation, such as underground mines, radon can accumulate to levels that substantially increase the risk of lung cancer. Radon can enter homes through cracks in floors, walls, or foundations, and collect indoors. It can also be released from building materials, or from water obtained from wells that contain radon. Radon levels can be higher in homes that are well insulated, tightly sealed, and/or built on soil rich in the elements uranium, thorium, and radium. Basement and first floors typically have the highest radon levels because of their closeness to the ground. The RVISL will also allow for the calculation of screening levels for thoron (Rn-220) and Rn-219. The RVISL will be useful in assessing the final cleanup goals for subsurface soils where direct contact is not assumed. These sites can be landfills, buried waste cells or naturally occurring. By calculating protective levels of radon in subsurface soils, the likelihood of exceeding CERCLA protective standards (either risk range or ARARs) can be reduced. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Protein engineering of aldolase LbDERA for enhanced activity toward real substrates with a high-throughput screening method coupled with an aldehyde dehydrogenase

A new high-throughput method for screening 2-deoxyribose-5-phosphate aldolase variants with a higher activity toward aldol reaction of unnatural aldehydes was established for the first time by coupling with an aldehyde dehydrogenase LeADH. The error-prone PCR and site-directed saturation mutagenesis libraries of aldolase LbDERA were constructed and screened using the high-throughput method. Two improved variants, LbDERA{sub T29L} and LbDERA{sub F163Y}, were identified and combined, giving a double mutant LbDERA{sub T29L/F163Y} which showed 7-fold higher activity than the native enzyme. The crystal structure of LbDERA{sub T29L/163Y} obtained by X-ray diffraction with 1.77 Å resolution revealed the structural changes responsible for the significant activity improvement. - Highlights: • A high-throughput method for screening aldolase variants was established. • A variant LbDERA{sub T29L/F163Y} with 7-fold improved activity was identified. • The crystal structure reveals structure changes responsible for activity improvement.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Screening of Therapeutic Agents for COVID-19 Using Machine Learning and Ensemble Docking Studies

The current pandemic demands a search for therapeutic agents against the novel coronavirus SARS-CoV-2. In this work, we present an efficient computational strategy that combines machine learning (ML)-based models and high-fidelity ensemble docking studies to enable rapid screening of possible therapeutic ligands. Targeting the binding affinity of molecules for either the isolated SARS-CoV-2 S-protein at its host receptor region or the S-protein:human ACE2 interface complex, we screen ligands from drug and biomolecule data sets that can potentially limit and/or disrupt the host-virus interactions. Top scoring one hundred eighty-seven ligands (with 75 approved by the Food and Drug Administration) are further validated by all atom docking studies. Important molecular descriptors ( 2 χ n , topological surface area, and ring count) and promising chemical fragments (oxolane, hydroxy, and imidazole) are identified to guide future experiments. Overall, this work expands our knowledge of small-molecule treatment against COVID-19 and provides a general screening pathway (combining quick ML models with expensive high-fidelity simulations) for targeting several chemical/biochemical problems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

“Multiagent” Screening Improves Directed Enzyme Evolution by Identifying Epistatic Mutations

Enzyme evolution has enabled numerous advances in biotechnology and synthetic biology, yet still requires many iterative rounds of screening to identify optimal mutant sequences. This is due to the sparsity of the fitness landscape, which is caused by epistatic mutations that only offer improvements when combined with other mutations. We report an approach that incorporates diverse substrate analogues in the screening process, where multiple substrates act like multiple agents navigating the fitness landscape, identifying epistatic mutant residues without a need for testing the entire combinatorial search space. We initially validate this approach by engineering a malonyl-CoA synthetase and identify numerous epistatic mutations improving activity for several diverse substrates. The majority of these mutations would have been missed upon screening for a single substrate alone. We expect that this approach can accelerate a wide array of enzyme engineering programs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Screening of the Protective Actions under the Laser Irradiation of Bio-Objects: Experimental Results and Physical Model

The screening of protective radiations that occur during laser radiation of biological tissues have been experimentally studied. The metallic and dielectric screens with different shape have been used for screening. The physical model of generation of the secondary radiation that generates the protective effects, which lead to a substantial increase in the environmental resistance of living organisms placed nearby, has been suggested. It has been assumed that this radiation is mainly concentrated in the frequency range lower than 10 GHz.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Probing specificities of alcohol acyltransferases for designer ester biosynthesis with a high–throughput microbial screening platform

Alcohol acyltransferases (AATs) enables microbial biosynthesis of a large space of esters by condensing an alcohol and an acyl-CoA. However, substrate promiscuity of AATs prevents microbial biosynthesis of designer esters with high selectivity. Here, we developed a high-throughput microbial screening platform that facilitates rapid identification of AATs for designer ester biosynthesis. First, we established a microplate-based culturing technique with in situ fermentation and extraction of esters. We validated its capability in rapid profiling of the alcohol substrate specificity of 20 chloramphenicol acetyltransferase variants derived from Staphylococcus aureus (CAT Sa ) for microbial biosynthesis of acetate esters with various exogeneous alcohol supply. By coupling the microplate-based culturing technique with a previously established colorimetric assay, we developed a high-throughput microbial screening platform for AATs. We demonstrated that this platform could not only probe the alcohol substrate specificity of both native and engineered AATs but also identify the beneficial mutations in engineered AATs for enhanced ester synthesis. Here, we anticipate the high-throughput microbial screening platform provides a useful tool to identify novel wildtype and engineered AATs that have important roles in nature and industrial biocatalysis for designer bioester production.

2-phenhylethyl acetate↗
DOE OSTI2025

Low-Cost, Screen-Printed Silver Metal Complex Inks for Silicon Heterojunction Solar Cells

Screen printing using metal particle pastes, the current photovoltaic industry metallization standard, provides fast and reliable metal grids for silicon solar cells. Recently, metal complex or reactive metal inks are attracting research interest due to their significantly low cost and higher performance compared to traditional nanoparticle silver pastes. In this work, we demonstrate, for the first time, screen-printed high-efficiency silicon heterojunction solar cells metallized by silver metal complex inks on industrial G1-size (158.75 x 158.75 mm2) wafers. We demonstrate screen-printed Ag metal complex ink grid patterns with continuous fingers ~100-120 ..mu..m wide. The printed Ag grid is very thin (~1 ..mu..m), which is an order of magnitude thinner than the current ~20-30 ..mu..m fingers printed with low-temperature nanoparticle-based pastes. Double printing allows silicon heterojunction devices with efficiencies >20%. This is the highest efficiency so far, to our knowledge, of industrial solar cell precursors using this metallization technology. Simulation results suggested that increasing the thickness of the metal film does not significantly improve efficiency due to the dense, highly conductive films. So, a single print of ~1 ..mu..m finger would be enough to produce cells that perform similarly to a ~20 ..mu..m thick nanoparticle paste printed cells. Additionally, solar cells printed on G1 wafers with silver metal complex ink required more than 10 times less silver (~0.03 g) compared to those using silver/copper nanoparticle paste (~0.4 g of Ag). These results indicate that metal complex inks are a very promising replacement for silver nanoparticle pastes for industrial-scale metallization in an age of resource scarcity and high costs of noble metals.

14 SOLAR ENERGY↗
DOE OSTI2025

Combining computational modeling and experimental library screening to affinity-mature VEEV-neutralizing antibody F5

Engineered monoclonal antibodies have proven to be highly effective therapeutics in recent viral outbreaks. However, despite technical advancements, an ability to rapidly adapt or increase antibody affinity and by extension, therapeutic efficacy, has yet to be fully realized. We endeavored to stand-up such a pipeline using molecular modeling combined with experimental library screening to increase the affinity of F5, a monoclonal antibody with potent neutralizing activity against Venezuelan Equine Encephalitis Virus (VEEV), to recombinant VEEV (IAB) E1E2 antigen. We modeled the F5/E1E2 binding interface and generated predictions for mutations to improve binding using a Rosetta-based approach and dTERMen, an informatics approach. The modeling was complicated by the fact that a high-resolution structure of F5 is not available and the H3 loop of F5 exceeds the length for which current modeling approaches can determine a unique structure. A subset of the predicted mutations from both methods were incorporated into a phage display library of scFvs. This library and a library generated by error-prone PCR were screened for binding affinity to the recombinant antigen. Results from the screens identified favorable mutations which were incorporated into 12 human-IgG1 variants. The best variant, containing eight mutations, improved KD from 0.63 nM (parental) to 0.01 nM. While this did not improve neutralization or therapeutic potency of F5 against IAB, it did increase cross-reactivity to other closely related VEEV epizootic and enzootic strains, demonstrating the potential of this method to rapidly adapt existing therapeutics to emerging viral strains.

affinity-maturation↗
DOE OSTI2015

Anti-pulmonary fibrotic activity of salvianolic acid B was screened by a novel method based on the cyto-biophysical properties

Various methods have been used to evaluate anti-fibrotic activity of drugs. However, most of them are complicated, labor-intensive and lack of efficiency. This study was intended to develop a rapid method for anti-fibrotic drugs screening based on biophysical properties. A549 cells in vitro were stimulated with transforming growth factor-β1 (TGF-β1), and fibrogenesis was confirmed by conventional immunological assays. Meanwhile, the alterations of cyto-biophysical properties including morphology, roughness and stiffness were measured utilizing atomic force microscopy (AFM). It was found that fibrogenesis was accompanied with changes of cellular biophysical properties. TGF-β1-stimulated A549 cells became remarkably longer, rougher and stiffer than the control. Then, the effect of N-acetyl-L-cysteine (NAC) as a positive drug on ameliorating fibrogenesis in TGF-β1-stimulated A549 cells was verified respectively by immunological and biophysical markers. The result of Principal Component Analysis showed that stiffness was a leading index among all biophysical markers during fibrogenesis. Salvianolic acid B (SalB), a natural anti-oxidant, was detected by AFM to protect TGF-β1-stimulated A549 cells against stiffening. Then, SalB treatment was provided in preventive mode on a rat model of bleomycin (BLM) -induced pulmonary fibrosis. The results showed that SalB treatment significantly ameliorated BLM-induced histological alterations, blocked collagen accumulations and reduced α-SMA expression in lung tissues. All these results revealed the anti-pulmonary fibrotic activity of SalB. Detection of cyto-biophysical properties were therefore recommended as a rapid method for anti-pulmonary fibrotic drugs screening. - Highlights: • Fibrogenesis was accompanied with the changes of cyto-biophysical properties. • Cyto-biophysical properties could be markers for anti-fibrotic drugs screening. • Stiffness is a leading index among all biophysical markers. • SalB was detected to protect TGF-β1-stimulated A549 cells against stiffening. • SalB treatment ameliorated pulmonary fibrosis induced by BLM in rats.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Understanding, inhibiting, and engineering membrane transporters with high-throughput mutational screens

Promiscuous membrane transporters play vital roles across domains of life, mediating the uptake and efflux of structurally and chemically diverse substrates. Although many transporter structures have been solved, the fundamental rules of polyspecific transport remain inscrutable. In recent years, high-throughput genetic screens have solidified as powerful tools for comprehensive, unbiased measurements of variant function and hypothesis generation, but have had infrequent application and limited impact in the transporter field. In this primer, we describe the principles of high-throughput screening methods available for studying polyspecific transporters and comment on the necessity and potential of high-throughput methods for deciphering these transporters in particular. We present several screening approaches which could provide a fundamental understanding of the molecular basis of function and promiscuity in transporters. Here, we further posit how this knowledge can be leveraged to design inhibitors that combat multidrug resistance and engineer transporters as needed tools for synthetic biology and biotechnology applications.

EPIs↗
DOE OSTI2021

Screening and Validation of Molecular Targeted Radiosensitizers

The development of molecular targeted drugs with radiation and chemotherapy is critically important for improving the outcomes of patients with hard-to-treat, potentially curable cancers. However, too many preclinical studies have not translated into successful radiation oncology trials. Major contributing factors to this insufficiency include poor reproducibility of preclinical data, inadequate preclinical modeling of intertumoral genomic heterogeneity that influences treatment sensitivity in the clinic, and a reliance on tumor growth delay instead of local control (TCD50) endpoints. There exists an urgent need to overcome these barriers to facilitate successful clinical translation of targeted radiosensitizers. To this end, we have used 3-dimensional (3D) cell culture assays to better model tumor behavior in vivo. Examples of successful prediction of in vivo effects with these 3D assays include radiosensitization of head and neck cancers by inhibiting epidermal growth factor receptor or focal adhesion kinase signaling, and radioresistance associated with oncogenic mutation of KRAS. To address the issue of tumor heterogeneity, we leveraged institutional resources that allow high-throughput 3D screening of radiation combinations with small-molecule inhibitors across genomically characterized cell lines from lung, head and neck, and pancreatic cancers. This high-throughput screen is expected to uncover genomic biomarkers that will inform the successful clinical translation of targeted agents from the National Cancer Institute Cancer Therapy Evaluation Program portfolio and other sources. Screening “hits” need to be subjected to refinement studies that include clonogenic assays, addition of disease-specific chemotherapeutics, target/biomarker validation, and integration of patient-derived tumor models. The chemoradiosensitizing activities of the most promising drugs should be confirmed in TCD50 assays in xenograft models with or without relevant biomarker and using clinically relevant radiation fractionation. We predict that appropriately validated and biomarker-directed targeted therapies will have a higher likelihood than past efforts of being successfully incorporated into the standard management of hard-to-treat tumors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗