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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 127 records · Page 7
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 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 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 OSTI2025

Solvent Screening for Separation Processes Using Machine Learning and High-Throughput Technologies

As the chemical industry shifts toward sustainable practices, there is a growing initiative to replace conventional fossil-derived solvents with environmentally friendly alternatives such as ionic liquids (ILs) and deep eutectic solvents (DESs). Artificial intelligence (AI) plays a key role in the discovery and design of novel solvents and the development of green processes. This review explores the latest advancements in AI-assisted solvent screening with a specific focus on machine learning (ML) models for physicochemical property prediction and separation process design. Additionally, this paper highlights recent progress in the development of automated high-throughput (HT) platforms for solvent screening. Finally, this paper discusses the challenges and prospects of ML-driven HT strategies for green solvent design and optimization. To this end, this review provides key insights to advance solvent screening strategies for future chemical and separation processes.

Artificial intelligence↗
DOE OSTI2025

Investigating the effect of screen-printed structured graphite electrodes with low tortuosity for high-capacity and fast-charging lithium-ion batteries

A flexible screen-printed graphite electrode was fabricated as an anode for developing fast-charging lithium-ion batteries with low tortuosity. A homogenous anode ink was prepared by mixing graphite as the active material, carbon black (C45) as the conductive additive, and polyvinylidene fluoride (PVDF) as the binder in N-Methyl-2-pyrrolidone (NMP) solvent. The ink was deposited on a flexible copper foil via a stainless-steel screen consisting of an array of pores, that act as secondary pore networks (SPNs), using the screen-printing process. Lithium-ion battery half-cells were assembled using the printed graphite anode, lithium metal foil as the counter electrode, and 1.2 M lithium hexafluorophosphate (LiPF 6 ) in ethyl carbonate: ethyl methyl carbonate (EC: EMC = 3:7) as the electrolyte. The effect of SPNs on the cell performance was investigated by performing formation, rate and cycling tests on the assembled cells, at different C-rates. It was observed that the cells consisting of SPNs with a pore size of 100 μm and edge-to-edge distance of 100 μm between the pores exhibited significantly higher specific capacities of 168 and 129 mAh/g when compared to reference cells without SPNs, which had capacities of 120 and 85 mAh/g, at high C-rates of 4 C and 6 C, respectively. The cells with SPNs also demonstrated excellent cycling performance with ~ 95% capacity retention after 100 cycles at 2 C.

Fast charging lithium-ion battery↗
DOE OSTI2025

Analysis of Screening Current Effects in a Hybrid Nb$_{3}$Sn/REBCO Superconducting Accelerator Magnet Using a T - A Formulation

To explore the feasibility of using high-temperature superconducting (HTS) REBCO coated conductors in future accelerator magnets, two REBCO flat racetrack coils were fabricated using 4-mm wide EuBCO tapes at the High Energy Accelerator Research Organization (KEK). These coils were tested as an insert inside a Nb$_{3}$Sn common-coil dipole magnet, which provides a background field of up to $\sim$ 9.5T, at the Brookhaven National Laboratory (BNL). REBCO tapes offer exceptionally high critical current density under strong magnetic fields; however, they also exhibit significant magnetization due to screening currents, leading to magnetic field errors. Here, this study presents a 2D finite element model of screening current-induced fields (SCIF) in REBCO coils using the T-A formulation, along with the results obtained. Simulations were then performed for two KEK test cases: one where the REBCO conductors were oriented with the HTS tapes parallel to the background field, and another where the tapes were perpendicular to it. Since screening currents also influence the stress distribution and increase the peak stress in the coils, the mechanical effects of these currents were analyzed. The implications of these simulation and test results for the design of Nb$_{3}$Sn/REBCO superconducting accelerator magnets are discussed.

Accelerator magnets↗
DOE OSTI2025

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to national security, public health, and the economy. Development of new vaccines and antibodies for emerging viral threats requires substantial resources and time, and traditional development platforms for vaccines and antibodies are often too slow to combat continuously evolving immunological escape variants, reducing their efficacy over time. Previously, we designed a next-generation synthetic humanized nanobody (Nb) phage display library and demonstrated that this library could be used to rapidly identify highly specific and potent neutralizing heavy chain-only antibodies (HCAbs) with prophylactic and therapeutic efficacy in vivo against the original SARS-CoV-2. In this study, we used a combination of high throughput screening and machine learning (ML) models to identify HCAbs with potent efficacy against SARS-CoV-2 viral variants of interest (VOIs) and concern (VOCs). To start, we screened our highly diverse Nb phage display library against several pre-Omicron VOI and VOC receptor binding domains (RBDs) to identify panels of cross-reactive HCAbs. Using HCAb affinity for SARS-CoV-2 VOI and VOCs (pre-Omicron variants) and model features from other published data, we were able to develop a ML model that successfully identified HCAbs with efficacy against Omicron variants, independent of our experimental biopanning workflow. This biopanning informed ML approach reduced the experimental screening burden by 78% to 90% for the Omicron BA.5 and Omicron BA.1 variants, respectively. The combined approach can be applied to other emerging viruses with pandemic potential to rapidly identify effective therapeutic antibodies against emerging variants.

Antibodies↗
DOE OSTI2024

Screening Analysis of Terrestrial Enhanced Rock Weathering of Igneous Rocks and Industrial Waste Materials

This poster, presented at the 17th Greenhouse Gas Control Technology Conference, reports on an NETL screening level techno-economic assessment of enhanced weathering (EW). EW is a promising emerging carbon dioxide removal approach that involves harnessing and accelerating the natural weathering process by which atmospheric CO2 passively reacts with exposed alkaline minerals and is removed from the atmosphere. Two primary cases utilizing different sources of alkaline material are considered: (1) utilizing naturally occurring mined igneous rocks, and (2) utilizing industrial waste materials. The analysis highlights that utilizing materials with high weathering potential in suitable locations may result in relatively low levelized cost of captured. NETL is publishing a detailed and transparent report titled “Enhanced Weathering: Techno-Economic and Life Cycle Screening Analysis” that includes more detail on the screening level techno-economic analysis and includes a life cycle analysis.

carbon dioxide removal↗
NASA NTRS2012

Cloud Screening and Quality Control Algorithm for Star Photometer Data: Assessment with Lidar Measurements and with All-sky Images

This paper presents the development and set up of a cloud screening and data quality control algorithm for a star photometer based on CCD camera as detector. These algorithms are necessary for passive remote sensing techniques to retrieve the columnar aerosol optical depth, delta Ae(lambda), and precipitable water vapor content, W, at nighttime. This cloud screening procedure consists of calculating moving averages of delta Ae() and W under different time-windows combined with a procedure for detecting outliers. Additionally, to avoid undesirable Ae(lambda) and W fluctuations caused by the atmospheric turbulence, the data are averaged on 30 min. The algorithm is applied to the star photometer deployed in the city of Granada (37.16 N, 3.60 W, 680 ma.s.l.; South-East of Spain) for the measurements acquired between March 2007 and September 2009. The algorithm is evaluated with correlative measurements registered by a lidar system and also with all-sky images obtained at the sunset and sunrise of the previous and following days. Promising results are obtained detecting cloud-affected data. Additionally, the cloud screening algorithm has been evaluated under different aerosol conditions including Saharan dust intrusion, biomass burning and pollution events.

data quality control algorithm↗
NASA NTRS2014

A Predictive Bubble Point Pressure Model for Porous Liquid Acquisition Device Screens

This article presents a simplified model for porous screen channel liquid acquisition devices based on a maximum bubble point pressure method from Adamson and Gast (1997). To validate the model, three 304 stainless steel (325 × 2300, 450 × 2750, and 510 × 3600) mesh samples were tested in methanol, acetone, isopropyl alcohol, and water. Screen pores are estimated based on analysis from scanning electron microscopy, historical data, and current test data. Results show that the bubble point pressure is proportional to the surface tension of the fluid only when accounting for nonzero contact angles. The previous assumption that bubble point pressure scales inversely with effective pore diameter is shown to be invalid, as the second finest 450 × 2750 produced the highest bubble point of the three screens. The simplified bubble point model can be used to make predictions for any pure fluid when pore diameters are based on bubble point tests and not SEM analysis.

Liquid Acquisition Device↗
NASA NTRSDate not supplied

Electron Screened and Enhanced Nuclear Reactions

In 1954, Salpeter calculated nuclear reaction rates would increase via weak and strong electron screening in stars. Astrophysical observations and laboratory astrophysics experiments have confirmed that electron screening reduces the Coulomb Barrier between charged particles. Fermi degenerate strong screening occurs when the electron density exceeds 10e23 electrons/cm3 in the cores of gas giant planets, White Dwarf Stars, the conduction bands of metals, deuterated LENR materials and Inertial Confinement Fusion targets at maximum compression. We have modelled these quantum mechanical effects with Density Functional Theory codes.

electron screening↗
DOE OSTI2025

Compatibility Screening of Explosive‐Inert Mixtures

Inert materials are necessary components in explosive devices and they must be tested for compatibility with the explosive materials to ensure that the device will function as expected over its lifetime in representative environments. True compatibility testing is time-consuming and expensive and so compatibility screening is often used as an early assessment. The screening is carried out with analytical methods run at temperatures exceeding those that the device will encounter in its lifetime. Shortcomings of this approach are discussed and improvements using a transient contact method and microcalorimetry are proposed. Typical screening results and microcalorimetry results are compared for a polyurethane adhesive—PBX 9502 combination.

36 MATERIALS SCIENCE↗
DOE OSTI2026

>24% screen printed Cu contacted n-TOPCon solar cells with successful implementation of LECO process

In this paper, we report the successful fabrication of >24.0 % efficiency n-TOPCon Si solar cells with screen-printed, fire-through Cu contact to n-TOPCon on the rear side and Ag contacted boron emitter on the front side by implementing optimized firing and LECO conditions. The highest efficiency (24.3%) Cu contacted n-TOPCon cell in this study showed excellent cell performance parameters with V oc >730 mV, J sc of 41.1 mA/cm 2 and FF of 80.8%, resulting in an absolute efficiency gap of 0.2% between Cu-contacted and fully Ag contacted n-TOPCon cells (24.5%). The mini-module fabricated with the Cu contacted n-TOPCon cell showed excellent reliability and durability of open-circuit voltage (V oc ), pseudo fill factor (pFF) and efficiency after prolonged damp-heat tests. Such high efficiency screen printed Cu contacted n-TOPCon cells provide unique opportunity to replace very expensive Ag contact on n-TOPCon with cheaper screen printable Cu metal pastes.

14 SOLAR ENERGY↗
DOE OSTI2025

Investigating Fast Scanning Calorimetry and Differential Scanning Calorimetry as Screening Tools for Thermoset Polymer Material Compatibility with Laser-Based Powder Bed Fusion

As additive manufacturing (AM) technology has developed and progressed, a constant topic of research in the area is expanding the library of materials to be used with these techniques. Among AM methods that utilize polymers, laser-based powder bed fusion (PBF-LB) has preferentially used thermoplastic polymers as its starting materials, but the deposition and material joining method employed in PBF-LB may also be compatible with powdered thermoset polymer precursors as feedstocks. To assess the compatibility of candidate thermosetting polymers and PBF-LB, characterization techniques and protocols that link fundamental material behavior to material behavior in the processing environment are needed. Therefore, the objectives of this work are to compare the curing behavior measured with two different calorimetry techniques that can operate in different heating rate regimes, differential scanning calorimetry (DSC) and fast scanning calorimetry (FSC), and to assess the capabilities of these techniques to act as materials screening tools for PBF-LB. A commercial polyester powder coating is used as a model material to evaluate the potential of obtaining complimentary information for material screening through a combination of calorimetry methods, and its non-isothermal curing behavior is measured at heating rates between 5 °C/min and 7500 °C/min. Curing exotherms are observed with both calorimetry techniques, and comparing the enthalpy associated with curing shows that incomplete curing occurs at higher heating rates, with relative conversion values of approximately 30%. The curing data are fit with two isoconversional models, Friedman and Starink, which show a reduced activation energy at higher heating rates as well, signifying a lower barrier to curing at the conditions used in the FSC experiments. Overall, the results of this work indicate that using these two calorimetry techniques as tiered screening tools can provide valuable information about how curing may proceed in PBF-LB and inform materials selection and design activities for additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Rapid Evaluation of Amine-Functionalized Solvents for Biomass Deconstruction Using High-Throughput Screening and One-Pot Enzymatic Saccharification

Efficient and sustainable pretreatment of lignocellulosic biomass is critical for biofuel and biochemical production, yet its optimization is often hindered by slow, labor-intensive experimental methods. Here, we report the first demonstration of a custom-built, miniaturized, high-throughput screening platform integrated with one-pot enzymatic saccharification, enabling parallel evaluation of solvent type, feedstock, and temperature with minimal material use and high reproducibility. As a proof-of-concept, the HTX platform was used to screen five amine-functionalized solvents, including isopropanolamine, butylamine, N-methylbutylamine, ethanolamine, and ethanolamine acetate across three bioenergy crops (sorghum, poplar, and switchgrass) and pretreatment temperatures ranging from 80 to 140 °C. Vacuum drying successfully removed more than 99% of the solvents from the pretreated biomass, eliminating the need for water washing prior to saccharification. Isopropanolamine and N-methylbutylamine yielded the highest glucose (70–80%) and xylose (58–67%) release, with trends reflecting feedstock recalcitrance. The produced hydrolysates supported robust growth of an engineered strain of the yeast Rhodosporidium toruloides, confirming biocompatibility. This high-throughput platform provides a scalable, feedstock-agnostic framework for rapid pretreatment screening, accelerating solvent–feedstock pairing and process optimization. Its ability to integrate pretreatment, solvent removal, saccharification, and microbial conversion in a miniaturized format offers significant advantages for cost-competitive biorefinery development.

Biomass↗