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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
DOE OSTI2024

Electronic structure and optical properties of halide double perovskites from a Wannier-localized optimally-tuned screened range-separated hybrid functional

Halide double perovskites are a chemically diverse and growing class of compound semiconductors that are promising for optoelectronic applications. However, the prediction of their fundamental gaps and optical properties with density functional theory (DFT) and ab initio many-body perturbation theory has been a significant challenge. Recently, a nonempirical Wannier-localized optimally tuned screened range-separated hybrid (WOT-SRSH) functional has been shown to accurately produce the fundamental band gaps of a wide set of semiconductors and insulators, including lead halide perovskites. Here, in this study, we apply the WOT-SRSH functional to five halide double perovskites and compare the results with those obtained from other known functionals and previous GW calculations. We also use the approach as a starting point for GW calculations and we compute the band structures and optical absorption spectrum for Cs 2 AgBiBr 6 , using both time-dependent DFT and the GW-Bethe-Salpeter equation approach. We show that the WOT-SRSH functional leads to accurate fundamental and optical band gaps, as well as optical absorption spectra, consistent with spectroscopic measurements, thereby establishing WOT-SRSH as a viable method for the accurate prediction of optoelectronic properties of halide double perovskites.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Development of a novel minigenome and recombinant VSV expressing Seoul hantavirus glycoprotein-based assays to identify anti-hantavirus therapeutics

Seoul virus (SEOV) is an emerging global health threat that can cause hemorrhagic fever with renal syndrome (HFRS), which results in case fatality rates of ~2%. There are no approved treatments for SEOV infections. We developed a cell-based assay system to identify potential antiviral compounds for SEOV and generated additional assays to characterize the mode of action of any promising antivirals. Here, to test if candidate antivirals targeted SEOV glycoprotein-mediated entry, we developed a recombinant reporter vesicular stomatitis virus expressing SEOV glycoproteins. To facilitate the identification of candidate antiviral compounds targeting viral transcription/replication, we successfully generated the first reported minigenome system for SEOV. This SEOV minigenome (SEOV-MG) screening assay will also serve as a prototype assay for discovery of small molecules inhibiting replication of other hantaviruses, including Andes and Sin Nombre viruses. Ours is a proof-of-concept study in which we tested several compounds previously reported to have activity against other negative-strand RNA viruses using our newly developed hantavirus antiviral screening systems. These systems can be used under lower biocontainment conditions than those needed for infectious viruses, and identified several compounds with robust anti-SEOV activity. Our findings have important implications for the development of anti-hantavirus therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Drugging the entire human proteome: Are we there yet?

Each of the ~20 000 proteins in the human proteome is a potential target for compounds that bind to it and modify its function. The 3D structures of most of these proteins are now available. Here, we discuss the prospects for using these structures to perform proteome-wide virtual HTS (VHTS). Furthermore, we compare physics-based (docking) and AI VHTS approaches, some of which are now being applied with large databases of compounds to thousands of targets. Although preliminary proteome-wide screens are now within our grasp, further methodological developments are expected to improve the accuracy of the results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Hybrid functional calculations of electronic structure and carrier densities in rare-earth monopnictides

The structural parameters and electronic structure of rare-earth pnictides are calculated using density functional theory (DFT) with the Heyd, Scuseria, and Ernzerhof (HSE06) screened hybrid functional. Specifically, we focus on RE-V compounds, with RE=La, Gd, Er, and Lu, and V=As, Sb, and Bi, and analyze the effects of spin-orbit coupling and treating the RE4$\textit{f}$ electrons as valence electrons in the projector augmented wave approach. The results of HSE06 calculations are compared with DFT within the generalized gradient approximation (DFT-GGA) and other previous calculations. We find that all these RE-V compounds are semimetals with electron pockets at the $\textit{X}$ point and hole pockets at Γ. Whereas in DFT-GGA the carrier density is significantly overestimated, the computed carrier densities using HSE06 is in good agreement with the available experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Search for Stable and Low-Energy Ce–Co–Cu Ternary Compounds Using Machine Learning

Cerium-based intermetallics have garnered significant research attention as potential new permanent magnets. In this study, we explore the compositional and structural landscape of Ce−Co−Cu ternary compounds using a machine learning (ML)- guided framework integrated with first-principles calculations. We employ a crystal graph convolutional neural network (CGCNN), which enables efficient screening for promising candidates, significantly accelerating the material discovery process. With this approach, we predict five stable compounds, Ce 3 Co 3 Cu, CeCoCu 2 , Ce 12 Co 7 Cu, Ce 11 Co 9 Cu, and Ce 10 Co 11 Cu 4 , with formation energies below the convex hull, along with hundreds of low-energy (possibly metastable) Ce−Co−Cu ternary compounds. Firstprinciples calculations reveal that several structures are both energetically and dynamically stable. Notably, two Co-rich low-energy compounds, Ce 4 Co 33 Cu and Ce 4 Co 31 Cu 3 , are predicted to have high magnetizations.

Chemical structure↗
DOE OSTI2022

Corrosivity Screening of Pyrolysis Bio-Oils by Short-Term Alloy Exposures. Laboratory Analytical Procedure (LAP), Issue Date: May 12, 2022

Bio-oils contain organic acids and oxygenated compounds that can lead to corrosion issues during bio-oil processing and storage. This Laboratory Analytical Procedure (LAP) allows for rapid screening of a bio-oil's corrosivity without the need for complex equipment and long-term exposures. A robust and repeatable method for assessing the corrosivity of bio-oils is necessary in order to remove materials degradation as an obstacle to research, upgrading, use and storage of bio-oils. This LAP involves the incubation of a representative alloy, 410 stainless steel (410 SS), specimen in bio-oil over a period of 48 hours at 50 degrees C in a sealed container. The corrosive species in the bio-oil react with and deplete alloy elements such as iron (Fe) and/or chromium (Cr) from the specimen into the bio-oil solution. The depletion of Fe and Cr from the specimen results in a significant mass loss that can be recorded. The mass loss is directly correlated to the corrosivity of a bio-oil. Examples of bio-oils in scope include the ones produced by fast pyrolysis and catalytic fast pyrolysis, as well as liquids produced from hydrothermal liquefaction.

09 BIOMASS FUELS↗
DOE OSTI2022

Electron-phonon coupling strength from ab initio frozen-phonon approach

In this work, we propose a fast method for high-throughput screening of potential superconducting materials. The method is based on calculating metallic screening of zone-center phonon modes, which provides an accurate estimate for the electron-phonon coupling strength. This method is complementary to the recently proposed Rigid Muffin Tin (RMT) method, which amounts to integrating the electronphonon coupling over the entire Brillouin zone (as opposed to the zone center), but in a relatively inferior approximation. We illustrate the use of this method by applying it to MgB 2 , where the high-temperature superconductivity is known to be driven largely by the zone-center modes, and compare it to a sister compound AlB 2 . We further illustrate the usage of this descriptor by screening a large number of binary hydrides, for which accurate first-principle calculations of electron-phonon coupling have been recently published. Together with the RMT descriptor, this method opens a way to perform initial high-throughput screening in search of conventional superconductors via machine learning or data mining.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Machine Learning Approach for the Prediction of Formability and Thermodynamic Stability of Single and Double Perovskite Oxides

Perovskite oxides continue to attract huge interest due to their fascinating and wide-ranging properties for diverse applications. The tunability of these properties may be further enhanced by increasing their compositional complexity via double perovskite-ordered configurations containing multiple cations. In this work, we focus on an exhaustive chemical space of single and double oxide perovskites and optimally explore this space to identify novel compositions that are likely to form stable compounds. Critically, we examine the relationship between formability, the practical ability to synthesize a compound, and stability, the thermodynamic preference to form the structure. Our formability and stability training data sets were enumerated from the available experimental literature and in-house density functional theory computations and contained 1505 and 3469 examples, respectively, representing state-of-the-art in the current open literature in perovskite and double perovskite compounds. Subsequently, cross-validated and highly accurate machine learning classification models are built using these training data sets and employed to screen for novel stable oxide perovskites. The study identifies (1) atomic features relevant to prediction of formability and stability in perovskite and double perovskite compounds, (2) the importance of including energy contributions due to local structural relaxations going beyond the high symmetry perovskite phase, and (3) 437,828 double perovskite compounds that are likely to be stable and 891,188 compounds that are likely to be formable. From the intersection of this large chemical space of formable and stable oxide perovskites, 414 compositions are identified as the most promising candidates for future experimental synthesis of novel oxide perovskites. The developed models may be generalized and have implications beyond perovskite discovery if applied to other families of compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Exploring novel HIV ‐1 reverse transcriptase inhibitors with drug‐resistant mutants: A double mutant surprise

Abstract HIV‐1 reverse transcriptase (RT) remains a key target for HIV drug development. As successful management of the disease requires lifelong treatment, the emergence of resistance mutations is inevitable, making development of new RT inhibitors, which remain effective against resistant variants crucial. To this end, previous computationally guided drug design efforts have resulted in catechol diether compounds, which inhibit wildtype RT with picomolar affinities and appear to be promising preclinical candidates. To confirm that these compounds remain potent against Y181C, a widespread mutation conferring resistance to first generation inhibitors, they were screened against the HIV‐1 N119 clinical isolate, reported as a Y181C single mutant. In comparison to a molecular clone with the same mutation, N119 appears less susceptible to inhibition by our preclinical candidate compounds. A more detailed sequencing effort determined that N119 was misidentified and carries V106A in combination with Y181C. While both indolizine and naphthalene substituted catechol diethers are potent against the classical Y181C single mutant, the addition of V106A confers more resistance against the indolizine derivatives than the naphthalene derivatives. Crystal structures presented in this study highlight key features of the naphthyl group, which allow these compounds to remain potent in the double mutant, including stronger interactions with F227 and less reliance on V106 for stabilization of the ethoxy‐uracil ring, which makes critical hydrogen bonds with other residues in the binding pocket.

Biochemistry & Molecular Biology↗
NASA NTRS1985

Metallo-organic decomposition films

A summary of metallo-organic deposition (MOD) films for solar cells was presented. The MOD materials are metal ions compounded with organic radicals. The technology is evolving quickly for solar cell metallization. Silver compounds, especially silver neodecanoate, were developed which can be applied by thick-film screening, ink-jet printing, spin-on, spray, or dip methods. Some of the advantages of MOD are: high uniform metal content, lower firing temperatures, decomposition without leaving a carbon deposit or toxic materials, and a film that is stable under ambient conditions. Molecular design criteria were explained along with compounds formulated to date, and the accompanying reactions for these compounds. Phase stability and the other experimental and analytic results of MOD films were presented.

Gallagher, B. D.↗
DOE OSTI2021

Design of High-Performance Lead-Free Quaternary Antiperovskites for Photovoltaics via Ion Type Inversion and Anion Ordering

The emergence of halide double perovskites significantly increases the compositional space for lead-free and air-stable photovoltaic absorbers compared to halide perovskites. Nevertheless, most halide double perovskites exhibit oversized band gaps (>1.9 eV) or dipole-forbidden optical transition, which are unfavorable for efficient single-junction solar cell applications. The current device performance of halide double perovskite is still inferior to that of lead-based halide perovskites, such as CH 3 NH 3 PbI 3 (MAPbI 3 ). Here, by ion type inversion and anion ordering on perovskite lattice sites, two new classes of pnictogen-based quaternary antiperovskites with the formula of X 6 B 2 AA' and X 6 BB'A 2 are designed. Phase stability and tunable band gaps in these quaternary antiperovskites are demonstrated based on first-principles calculations. Further photovoltaic-functionality-directed screening of these materials leads to the discovery of 5 stable compounds (Ca 6 N 2 AsSb, Ca 6 N 2 PSb, Sr 6 N 2 AsSb, Sr 6 N 2 PSb, and Ca 6 NPSb 2 ) with suitable direct band gaps, small carrier effective masses and low exciton binding energies, and dipole-allowed strong optical absorption, which are favorable properties for a photovoltaic absorber material. The calculated theoretical maximum solar cell efficiencies based on these five compounds are all larger than 29%, comparable to or even higher than that of the MAPbI 3 based solar cell. Finally, our work reveals the huge potential of quaternary antiperovskites in the optoelectronic field and provides a new strategy to design lead-free and air-stable perovskite-based photovoltaic absorber materials.

three-dimensional electronic transport↗
DOE OSTI2021

Pandemic drugs at pandemic speed: infrastructure for accelerating COVID-19 drug discovery with hybrid machine learning- and physics-based simulations on high-performance computers

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie at the interface between machine learning methods, in this case, developed for linear accelerators, and physics-based methods. The two in silico methods, each have their own advantages and limitations which, interestingly, complement each other. Here, we present an innovative infrastructural development that combines both approaches to accelerate drug discovery. The scale of the potential resulting workflow is such that it is dependent on supercomputing to achieve extremely high throughput. We have demonstrated the viability of this workflow for the study of inhibitors for four COVID-19 target proteins and our ability to perform the required large-scale calculations to identify lead antiviral compounds through repurposing on a variety of supercomputers.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1975

Automated mass spectrometer/analysis system: A concept

System performs rapid multiple analyses of entire compound classes or individual compounds on small amounts of sample and reagent. Method will allow screening of large populations for metabolic disorders and establishment of effective-but-safe levels of therapeutic drugs in body fluids and tissues.

Boettger, H. G.↗
NASA NTRS1978

Static evaluation of surface coatings for compliant gas bearings in an oxidizing atmosphere to 650 C

Hard wear-resistant coatings and soft low shear strength coatings were developed for an air-lubricated compliant journal bearing for a future automotive gas turbine engine. The coatings were expected to function in either 540 or 650 C ambient. Soft lubricant coatings were generally limited in temperature. Therefore emphasis was on the hard wear-resistant coatings. The coating materials covered were TiC, B4C, Cr3C2, WC, SiC, CrB2, TiB2, Cr2O3, Al2O3, Si3N4, Tribaloy 800, CaF2, CaF2-BaF2 eutectic, Ni-Co, silver, CdO-graphite and proprietary compounds. The coatings on test coupons were subjected to static oven screening tests. The test consisted of exposure of material samples in an oven for 300 h at the maximum temperature (540 or 650 C) and ten temperature cycles from room temperature to the maximum service temperature. On the basis of the specimen examinations the following coatings were recommended for future wear tests: TiC (sputtered), Cr2O3 (sputtered), Si3N4 (sputtered), CdO and graphite (fused), Kaman DES (a proprietary coating), CrB2 (plasma sprayed), Cr3C2 (detonation gun) and NASA PS-106 (plasma sprayed).

Bhushan, B.↗
NASA NTRS2003

An Experimental Investigation of Hypergolic Ignition Delay of Hydrogen Peroxide with Fuel Mixtures

An experimental investigation of hypergolicity and ignition delay of fuel mixtures with hydrogen peroxide is presented. Example results of high speed photography and schleiren from drop tests are shown. Also, a discussion of the sensitivity to experimental parameters such as drop size and subsequent uncertainty considerations of ignition delay results is presented. It is shown that using the described setup on the mixtures presented, the precision uncertainty is on the order of 6% of average ignition delay and 5% of average decomposition delay. This represents sufficient repeatability for first order discrimination of ignition delay for propellant development and screening. Two mixtures, each using commonly available amines and transition metal compounds, are presented as examples that result in ignition delays on the order of 10 milliseconds.

Blevins, John A.↗
NASA NTRSDate not supplied

Hierarchical screening for Li-based solid electrolytes using fast, interpretable machine-learned potentials

Li-based solid-state electrolyte 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. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates. Finally, we apply the hierarchical workflow to screen for ionic conductivity across a database of Li-containing compounds.

Materials discovery↗
DOE OSTI2024

A goldilocks computational protocol for inhibitor discovery targeting DNA damage responses including replication-repair functions

While many researchers can design knockdown and knockout methodologies to remove a gene product, this is mainly untrue for new chemical inhibitor designs that empower multifunctional DNA Damage Response (DDR) networks. Here, we present a robust Goldilocks (GL) computational discovery protocol to efficiently innovate inhibitor tools and preclinical drug candidates for cellular and structural biologists without requiring extensive virtual screen (VS) and chemical synthesis expertise. By computationally targeting DDR replication and repair proteins, we exemplify the identification of DDR target sites and compounds to probe cancer biology. Our GL pipeline integrates experimental and predicted structures to efficiently discover leads, allowing early-structure and early-testing (ESET) experiments by many laboratories. By employing an efficient VS protocol to examine protein-protein interfaces (PPIs) and allosteric interactions, we identify ligand binding sites beyond active sites, leveraging in silico advances for molecular docking and modeling to screen PPIs and multiple targets. A diverse 3,174 compound ESET library combines Diamond Light Source DSI-poised, Protein Data Bank fragments, and FDA-approved drugs to span relevant chemotypes and facilitate downstream hit evaluation efficiency for academic laboratories. Two VS per library and multiple ranked ligand binding poses enable target testing for several DDR targets. This GL library and protocol can thus strategically probe multiple DDR network targets and identify readily available compounds for early structural and activity testing to overcome bottlenecks that can limit timely breakthrough drug discoveries. By testing accessible compounds to dissect multi-functional DDRs and suggesting inhibitor mechanisms from initial docking, the GL approach may enable more groups to help accelerate discovery, suggest new sites and compounds for challenging targets including emerging biothreats and advance cancer biology for future precision medicine clinical trials.

59 BASIC BIOLOGICAL SCIENCES↗