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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Scale-invariant machine-learning model accelerates the discovery of quaternary chalcogenides with ultralow lattice thermal conductivity

We design an advanced machine-learning (ML) model based on crystal graph convolutional neural network that is insensitive to volumes (i.e., scale) of the input crystal structures to discover novel quaternary chalcogenides, AMM'Q 3 (A/M/M' = alkali, alkaline earth, post-transition metals, lanthanides, and Q = chalcogens). These compounds are shown to possess ultralow lattice thermal conductivity (κ l ), a desired requirement for thermal-barrier coatings and thermoelectrics. Upon screening the thermodynamic stability of ~1 million compounds using the ML model iteratively and performing density-functional theory (DFT) calculations for a small fraction of compounds, we discover 99 compounds that are validated to be stable in DFT. Taking several DFT-stable compounds, we calculate their κ l using Peierls–Boltzmann transport equation, which reveals ultralow κ l (<2 Wm -1 K -1 at room temperature) due to their soft elasticity and strong phonon anharmonicity. Our work demonstrates the high efficiency of scale-invariant ML model in predicting novel compounds and presents experimental-research opportunities with these new compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Workflow for High-throughput Screening of Enzyme Mutant Libraries Using Matrix-assisted Laser Desorption/Ionization Mass Spectrometry Analysis of Escherichia coli Colonies

High-throughput molecular screening of microbial colonies and DNA libraries are critical procedures that enable applications such as directed evolution, functional genomics, microbial identification, and creation of engineered microbial strains to produce high-value molecules. A promising chemical screening approach is the measurement of products directly from microbial colonies via optically guided matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Measuring the compounds from microbial colonies bypasses liquid culture with a screen that takes approximately 5 s per sample. We describe a protocol combining a dedicated informatics pipeline and sample preparation method that can prepare up to 3,000 colonies in under 3 h. The screening protocol starts from colonies grown on Petri dishes and then transferred onto MALDI plates via imprinting. The target plate with the colonies is imaged by a flatbed scanner and the colonies are located via custom software. The target plate is coated with MALDI matrix, MALDI-MS analyzes the colony locations, and data analysis enables the determination of colonies with the desired biochemical properties. This workflow screens thousands of colonies per day without requiring additional automation. The wide chemical coverage and the high sensitivity of MALDI-MS enable diverse screening projects such as modifying enzymes and functional genomics surveys of gene activation/inhibition libraries.

Choe, Kisurb↗
DOE OSTI2025

Exploration of structure-activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment linking and active learning

The macrodomain of severe acute respiratory syndrome coronavirus 2 nonstructural protein 3 is required for viral pathogenesis and is an emerging antiviral target. We previously performed an x-ray crystallography–based fragment screen and found submicromolar inhibitors by fragment linking. However, these compounds had poor membrane permeability and liabilities that complicated optimization. Here, we developed a shape-based virtual screening pipeline—FrankenROCS. We screened the Enamine high-throughput collection of 2.1 million compounds, selecting 39 compounds for testing, with the most potent binding with a 130 μM median inhibitory concentration (IC 50 ). We then paired FrankenROCS with an active learning algorithm (Thompson sampling) to efficiently search the Enamine REAL database of 22 billion molecules, testing 32 compounds with the most potent binding with a 220 μM IC 50 . Further optimization led to analogs with IC 50 values better than 10 μM. This lead series has improved membrane permeability and is poised for optimization. FrankenROCS is a scalable method for fragment linking to exploit synthesis-on-demand libraries.

Science & Technology - Other Topics↗
DOE OSTI2024

HDBind: encoding of molecular structure with hyperdimensional binary representations

Traditional methods for identifying “hit” molecules from a large collection of potential drug-like candidates rely on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have a significant limitation in that they require exceptional computing capabilities for even relatively small collections of molecules. Increasingly large and complex state-of-the-art deep learning approaches have gained popularity with the promise to improve the productivity of drug design, notorious for its numerous failures. However, as deep learning models increase in their size and complexity, their acceleration at the hardware level becomes more challenging. Hyperdimensional Computing (HDC) has recently gained attention in the computer hardware community due to its algorithmic simplicity relative to deep learning approaches. The HDC learning paradigm, which represents data with high-dimension binary vectors, allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas (computer vision, bioinformatics, mass spectrometery, remote sensing, edge devices, etc.). To the best of our knowledge, our work is the first to consider HDC for the task of fast and efficient screening of modern drug-like compound libraries. We also propose the first HDC graph-based encoding methods for molecular data, demonstrating consistent and substantial improvement over previous work. We compare our approaches to alternative approaches on the well-studied MoleculeNet dataset and the recently proposed LIT-PCBA dataset derived from high quality PubChem assays. We demonstrate our methods on multiple target hardware platforms, including Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), showing at least an order of magnitude improvement in energy efficiency versus even our smallest neural network baseline model with a single hidden layer. Our work thus motivates further investigation into molecular representation learning to develop ultra-efficient pre-screening tools. We make our code publicly available at https://github.com/LLNL/hdbind.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

In‐Silico Device Performance Prediction of Cosensitizer Dye Pairs for Dye‐Sensitized Solar Cells

Abstract Endeavors in the field of dye‐sensitized solar cells (DSCs) have shown great promise when adopting a data‐driven approach to materials discovery, such as successful molecular‐scale predictions of light‐harvesting chromophores. However, predictions of DSC dyes would become much more sophisticated if a molecular‐to‐macroscopic DSC device prediction methodology existed. Thereby, a fully computational pipeline is presented that predicts device‐performance parameters of DSCs which contain varying dye combinations. Optimal pairing of complementary dyes is identified via a data‐driven workflow that affords cosensitized DSCs with maximum power‐conversion efficiencies. Six high‐performing DSC dyes are paired with partner dyes that are screened from a database of 8488 compounds using sequential heuristic filters. Existing models that predict short‐circuit‐current density ( J SC ) and open‐circuit voltage ( V OC ) parameters are adapted to predict singly sensitized and cosensitized DSC performance. The predictions for J sc values of singly sensitized devices match experimental literature values with comparable accuracy to more computationally costly methods. Five out of six dye pairings are predicted to have greater J SC values when cosensitized compared to their corresponding singly sensitized devices, including two pairs that show strong J sc boosts of +13% and +12% when cosensitized. Thus, the prospect of an entirely in‐silico prediction pipeline for DSC performance that can be used to realize the fully automated design of optimized cosensitized DSCs is demonstrated.

14 SOLAR ENERGY↗
DOE OSTI2021

Unique Diacidic Fragments Inhibit the OXA-48 Carbapenemase and Enhance the Killing of Escherichia coli Producing OXA-48

Despite the advances in β-lactamase inhibitor development, limited options exist for the class D carbapenemase known as OXA-48. OXA-48 is one of the most prevalent carbapenemases in carbapenem-resistant Enterobacteriaceae infections and is not susceptible to most available β-lactamase inhibitors. Here, we screened various low-molecular-weight compounds (fragments) against OXA-48 to identify functional scaffolds for inhibitor development. Several biphenyl-, naphthalene-, fluorene-, anthraquinone-, and azobenzene-based compounds were found to inhibit OXA-48 with low micromolar potency despite their small size. Co-crystal structures of OXA-48 with several of these compounds revealed key interactions with the carboxylate-binding pocket, Arg214, and various hydrophobic residues of β-lactamase that can be exploited in future inhibitor development. A number of the low-micromolar-potency inhibitors, across different scaffolds, synergize with ampicillin to kill Escherichia coli expressing OXA-48, albeit at high concentrations of the respective inhibitors. Additionally, several compounds demonstrated micromolar potency toward the OXA-24 and OXA-58 class D carbapenemases that are prevalent in Acinetobacter baumannii . In conclusion, this work provides foundational information on a variety of chemical scaffolds that can guide the design of effective OXA-48 inhibitors that maintain efficacy as well as potency toward other major class D carbapenemases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Supercomputing Pipelines Search for Therapeutics Against COVID-19

The urgent search for drugs to combat SARS-CoV-2 has included the use of supercomputers. The use of general-purpose graphical processing units (GPUs), massive parallelism, and new software for high-performance computing (HPC) has allowed researchers to search the vast chemical space of potential drugs faster than ever before. We developed a new drug discovery pipeline using the Summit supercomputer at Oak Ridge National Laboratory to help pioneer this effort, with new platforms that incorporate GPU-accelerated simulation and allow for the virtual screening of billions of potential drug compounds in days compared to weeks or months for their ability to inhibit SARS-COV-2 proteins. Here, this effort will accelerate the process of developing drugs to combat the current COVID-19 pandemic and other diseases.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1972

Study, selection, and preparation of solid cationic conductors

Crystal chemical principles and transport theory were used to predict structures and specific compounds which might find application as solid electrolytes in rechargeable high energy and high power density batteries operating at temperatures less than 200 C. More than twenty compounds were synthesized or obtained and screened by nuclear magnetic resonance and conductivity. Many were densified by sintering or hot pressing. Encouraging results were obtained for nine of these materials but none have yet been good ionic conductors at low temperature.

Roth, W. L.↗
NASA NTRS2012

Non-Toxic, Low-Freezing, Drop-In Replacement Heat Transfer Fluids

A non-toxic, non-flammable, low-freezing heat transfer fluid is being developed for drop-in replacement within current and future heat transfer loops currently using water or alcohol-based coolants. Numerous water-soluble compounds were down-selected and screened for toxicological, physical, chemical, compatibility, thermodynamic, and heat transfer properties. Two fluids were developed, one with a freezing point near 0 C, and one with a suppressed freezing point. Both fluids contain an additive package to improve material compatibility and microbial resistance. The optimized sub-zero solution had a freezing point of 30 C, and a freezing volume expansion of 10-percent of water. The toxicity of the solutions was experimentally determined as LD(50) greater than 5g/kg. The solutions were found to produce minimal corrosion with materials identified by NASA as potentially existing in secondary cooling loops. Thermal/hydrodynamic performance exceeded that of glycol-based fluids with comparable freezing points for temperatures Tf greater than 20 C. The additive package was demonstrated as a buffering agent to compensate for CO2 absorption, and to prevent microbial growth. The optimized solutions were determined to have physically/chemically stable shelf lives for freeze/thaw cycles and longterm test loop tests.

Cutbirth, J. Michael↗
DOE OSTI2021

Computational and experimental search for potential polyanionic K-ion cathode materials

Discovering high-energy cathode materials is critical to construct K-ion batteries for practical applications. Owing to the great success of layered oxides in Li- and Na-ion systems, K layered cathodes have also been investigated in recent years. However, the much larger size of K + compared to Li or Na introduces strong K + –K + interaction within the layer, which results in a sloped voltage profile thereby limiting the specific capacity and operating voltage. In contrast, polyanionic materials with a three-dimensional K + arrangement can effectively mitigate K + –K + interaction. In this work, ten K polyanionic compounds with theoretical capacity >100 mA h g –1 are screened from the Inorganic Crystal Structure Database as potential cathode materials for K-ion batteries. Among the ten proposed compounds, K 2 MnP 2 O 7 , K 2 Mn 2 P 2 O 7 F 2 , K 2 Fe 2 P 2 O 7 F 2 , and K 6 V 2 (PO 4 ) 4 with average voltage <4.5 V are synthesized and evaluated electrochemically. While the re-insertion of K into these compounds is not fully reversible, it may be related to the very high migration barrier that we compute for K ions. In addition, we show the successful synthesis of a series of K 3 V 3–x Cr x (PO 4 ) 4 (x = 0, 1, 2, 3) compounds. Among these, K 3 V 2 Cr(PO 4 ) 4 exhibits the largest reversible capacity, as revealed by the in situ investigation. Lastly, we find that the redox couples in many of these compounds sit at remarkably high potential, even higher than in equivalent Li compounds, which brings both opportunities and challenges in the future research of K polyanion cathodes.

25 ENERGY STORAGE↗
DOE OSTI2021

Accelerated Discovery and Design of Ultralow Lattice Thermal Conductivity Materials Using Chemical Bonding Principles

Semiconductors with very low lattice thermal conductivities are highly desired for applications relevant to thermal energy conversion and management, such as thermoelectrics and thermal barrier coatings. Although the crystal structure and chemical bonding are known to play vital roles in shaping heat transfer behavior, material design approaches of lowering lattice thermal conductivity using chemical bonding principles are uncommon. In this work, an effective strategy of weakening interatomic interactions and therefore suppressing lattice thermal conductivity based on chemical bonding principles is presented and a high-efficiency approach of discovering low κ L materials by screening the local coordination environments of crystalline compounds is developed. The resulting first-principles calculations uncover 30 hitherto unexplored compounds with (ultra)low lattice thermal conductivities from 13 prototype crystal structures contained in the Inorganic Crystal Structure Database. Furthermore, an approach of rationally designing high-performance thermoelectrics is demonstrated by additionally incorporating cations with stereochemically active lone-pair electrons. Here these results not only provide atomic-level insights into the physical origin of the low lattice thermal conductivity in a large family of copper/silver-based compounds but also offer an efficient approach to discover and design materials with targeted thermal transport properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Radiofluorination of oxazole-carboxamides for preclinical PET neuroimaging of GSK-3

Glycogen synthase kinase 3 (GSK-3) is an enzyme that is dysregulated in oncology neurodegeneration, neuroinflammation and several mental health illnesses. As such, GSK-3 is a long-sought after target for positron emission tomography (PET) imaging and therapeutic intervention. Herein, we report on the development and radiofluorination of two oxazole-4- carboxamides, including one bearing a non-activated aromatic ring. Both compounds demonstrated excellent selectivity in a kinase screen and inhibit GSK-3 with high affinity. [ 18 F]OCM-49 was synthesized from [ 18 F]fluoride using a copper-mediated reaction of an aryl boronic acid precursor, while [ 18 F]OCM-50 used a trimethylammonium triflate precursor, and both radiotracers were translated for preclinical PET imaging in rodents. Due to superior radiochemical yields and brain uptake (peak standardized uptake value of ~2.0), [ 18 F]OCM-50 was further evaluated in non-human primate and also showed good brain uptake and rapid clearance. Finally, further studies to consider clinical translation of both radiotracers are underway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Development of optimized drug-like small molecule inhibitors of the SARS-CoV-2 3CL protease for treatment of COVID-19

The SARS-CoV-2 3CL protease is a critical drug target for small molecule COVID-19 therapy, given its likely druggability and essentiality in the viral maturation and replication cycle. Based on the conservation of 3CL protease substrate binding pockets across coronaviruses and using screening, we identified four structurally distinct lead compounds that inhibit SARS-CoV-2 3CL protease. After evaluation of their binding specificity, cellular antiviral potency, metabolic stability, and water solubility, we prioritized the GC376 scaffold as being optimal for optimization. We identified multiple drug-like compounds with <10nM potency for inhibiting SARS-CoV-2 3CL and the ability to block SARS-CoV-2 replication in human cells, obtained co-crystal structures of the 3CL protease in complex with these compounds, and determined that they have pan-coronavirus activity. We selected one compound, termed coronastat, as an optimized lead and characterized it in pharmacokinetic and safety studies in vivo. Coronastat represents a new candidate for a small molecule protease inhibitor for the treatment of SARS-CoV-2 infection for eliminating pandemics involving coronaviruses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A New Drug Discovery Platform: Application to DNA Polymerase Eta and Apurinic/Apyrimidinic Endonuclease 1

The ability to quickly discover reliable hits from screening and rapidly convert them into lead compounds, which can be verified in functional assays, is central to drug discovery. The expedited validation of novel targets and the identification of modulators to advance to preclinical studies can significantly increase drug development success. Our SaXPyTM (“SAR by X-ray Poses Quickly”) platform, which is applicable to any X-ray crystallography-enabled drug target, couples the established methods of protein X-ray crystallography and fragment-based drug discovery (FBDD) with advanced computational and medicinal chemistry to deliver small molecule modulators or targeted protein degradation ligands in a short timeframe. Our approach, especially for elusive or “undruggable” targets, allows for (i) hit generation; (ii) the mapping of protein–ligand interactions; (iii) the assessment of target ligandability; (iv) the discovery of novel and potential allosteric binding sites; and (v) hit-to-lead execution. These advances inform chemical tractability and downstream biology and generate novel intellectual property. We describe here the application of SaXPy in the discovery and development of DNA damage response inhibitors against DNA polymerase eta (Pol η or POLH) and apurinic/apyrimidinic endonuclease 1 (APE1 or APEX1). Notably, our SaXPy platform allowed us to solve the first crystal structures of these proteins bound to small molecules and to discover novel binding sites for each target.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

MOD silver metallization for photovoltaics

The development of flat plate solar arrays is reported. Photovoltaic cells require back side metallization and a collector grid system on the front surface. Metallo-organic decomposition (MOD) silver films can eliminate most of the present problems with silver conductors. The objectives are to: (1) identify and characterize suitable MO compounds; (2) develop generic synthesis procedures for the MO compounds; (3) develop generic fabrication procedures to screen printable MOD silver inks; (4) optimize processing conditions to produce grid patterns and photovoltaic cells; and (5) develop a model which describes the adhesion between the fired silver film and the silicon surface.

Vest, G. M.↗
NASA NTRS1991

Methods development for total organic carbon accountability

This report describes the efforts completed during the contract period beginning November 1, 1990 and ending April 30, 1991. Samples of product hygiene and potable water from WRT 3A were supplied by NASA/MSFC prior to contract award on July 24, 1990. Humidity condensate samples were supplied on August 3, 1990. During the course of this contract chemical analyses were performed on these samples to qualitatively determine specific components comprising, the measured organic carbon concentration. In addition, these samples and known standard solutions were used to identify and develop methodology useful to future comprehensive characterization of similar samples. Standard analyses including pH, conductivity, and total organic carbon (TOC) were conducted. Colorimetric and enzyme linked assays for total protein, bile acid, B-hydroxybutyric acid, methylene blue active substances (MBAS), urea nitrogen, ammonia, and glucose were also performed. Gas chromatographic procedures for non-volatile fatty acids and EPA priority pollutants were also performed. Liquid chromatography was used to screen for non-volatile, water soluble compounds not amenable to GC techniques. Methods development efforts were initiated to separate and quantitate certain chemical classes not classically analyzed in water and wastewater samples. These included carbohydrates, organic acids, and amino acids. Finally, efforts were initiated to identify useful concentration techniques to enhance detection limits and recovery of non-volatile, water soluble compounds.

Benson, Brian L.↗
DOE OSTI2022

CeTaN 3 and CeNbN 3 : Prospective Nitride Perovskites with Optimal Photovoltaic Band Gaps

Perovskites constitute an exceptionally tunable materials family with diverse applications in electronics, optoelectronics, energy, and quantum technologies. Out of the thousands of known perovskites, the majority of compounds are oxides, halides, and chalcogenides. In contrast, only two nitride perovskites are currently known. In this work we perform a thorough ab initio computational screening of possible nitride perovskites, and we identify two new compounds, CeNbN 3 and CeTaN 3 , with band gaps in the near-infrared to visible range, depending on temperature. In their room-temperature orthorhombic phase, we predict that both compounds exhibit direct or quasidirect band gaps in the range 1.1–2.0 eV, with the Pnma phases matching the Shockley–Queisser limit for photovoltaic energy conversion efficiency. Further, these compounds are also predicted to be strong light absorbers, with absorption coefficients surpassing those of high-performance semiconductors such as GaAs and CH 3 NH 3 PbI 3 . The present findings reveal a potentially new class of nitride semiconductors with promise for electronics, optoelectronics, and light harvesting and for integration with existing nitride-based lighting technology.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Development of a Universal Second-Tier Newborn Screening LC–MS/MS Method for Amino Acids, Lysophosphatidylcholines, and Organic Acids

First-tier MS-based newborn screening by flow injection analysis can have high presumptive positive rates, often due to isomeric/isobaric compounds or poor biomarker specificity. These presumptive positive samples can be analyzed by second-tier screening assays employing separations such as liquid chromatography–mass spectrometry (LC–MS/MS), which increases test specificity and drastically reduces false positive referrals. The ability to screen for multiple disorders in a single multiplexed test simplifies workflows and maximizes public health laboratories’ resources. In this study, we developed and validated a highly multiplexed second-tier method for dried blood spots using a hydrophilic interaction liquid chromatography (HILIC) column coupled to an MS/MS system. The LC–MS/MS method was capable of simultaneously detecting second-tier biomarkers for maple syrup urine disease, homocystinuria, methylmalonic acidemia, propionic acidemia, glutaric acidemia type 1, glutaric acidemia type 2, guanidinoacetate methyltransferase deficiency, short-chain acyl-CoA dehydrogenase deficiency, adrenoleukodystrophy, and Pompe disease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗