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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High-throughput platform for yeast morphological profiling predicts the targets of bioactive compounds

Abstract Morphological profiling is an omics-based approach for predicting intracellular targets of chemical compounds in which the dose-dependent morphological changes induced by the compound are systematically compared to the morphological changes in gene-deleted cells. In this study, we developed a reliable high-throughput (HT) platform for yeast morphological profiling using drug-hypersensitive strains to minimize compound use, HT microscopy to speed up data generation and analysis, and a generalized linear model to predict targets with high reliability. We first conducted a proof-of-concept study using six compounds with known targets: bortezomib, hydroxyurea, methyl methanesulfonate, benomyl, tunicamycin, and echinocandin B. Then we applied our platform to predict the mechanism of action of a novel diferulate-derived compound, poacidiene. Morphological profiling of poacidiene implied that it affects the DNA damage response, which genetic analysis confirmed. Furthermore, we found that poacidiene inhibits the growth of phytopathogenic fungi, implying applications as an effective antifungal agent. Thus, our platform is a new whole-cell target prediction tool for drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

High-throughput injection-acceleration of electron bunches from a linear accelerator to a laser wakefield accelerator

Plasma-based accelerators (PBAs) driven by either intense lasers (laser wakefield accelerators, LWFAs) or particle beams (plasma wakefield accelerators, PWFAs), can accelerate charged particles at extremely high gradients compared to conventional radio-frequency (RF) accelerators. In the past two decades, great strides have been made in this field, making PBA a candidate for next-generation light sources and colliders. However, these challenging applications necessarily require beams with good stability, high quality, controllable polarization and excellent reproducibility. To date, such beams are generated only by conventional RF accelerators. As such, it is important to demonstrate the injection and acceleration of beams first produced using a conventional RF accelerator, by a PBA. In some recent studies on LWFA staging and external injection-acceleration in PWFA only a very small fraction (from below 0.1% to few percent) of the injected charge (the coupling efficiency) was accelerated. For future colliders where beam energy will need to be boosted using multiple stages, the coupling efficiency per stage must approach 100%. Here we report the first demonstration of external injection from a photocathode-RF-gun-based conventional linear accelerator (LINAC) into a LWFA and subsequent acceleration without any significant loss of charge or degradation of quality, which is achieved by properly shaping and matching the beam into the plasma structure. Furthermore, this is an important step towards realizing a high-throughput, multi-stage, high-energy, hybrid conventional-plasma accelerator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

High-throughput single-cell transcriptomics of bacteria using combinatorial barcoding

Microbial split-pool ligation transcriptomics (microSPLiT) is a high-throughput single-cell RNA sequencing method for bacteria. With four combinatorial barcoding rounds, microSPLiT can profile transcriptional states in hundreds of thousands of Gram-negative and Gram-positive bacteria in a single experiment without specialized equipment. As bacterial samples are fixed and permeabilized before barcoding, they can be collected and stored ahead of time. During the first barcoding round, the fixed and permeabilized bacteria are distributed into a 96-well plate, where their transcripts are reverse transcribed into cDNA and labeled with the first well-specific barcode inside the cells. The cells are mixed and redistributed two more times into new 96-well plates, where the second and third barcodes are appended to the cDNA via in-cell ligation reactions. Finally, the cells are mixed and divided into aliquot sub-libraries, which can be stored until future use or prepared for sequencing with the addition of a fourth barcode. It takes 4 days to generate sequencing-ready libraries, including 1 day for collection and overnight fixation of samples. Here, the standard plate setup enables single-cell transcriptional profiling of up to 1 million bacterial cells and up to 96 samples in a single barcoding experiment, with the possibility of expansion by adding barcoding rounds. The protocol requires experience in basic molecular biology techniques, handling of bacterial samples and preparation of DNA libraries for next-generation sequencing. It can be performed by experienced undergraduate or graduate students. Data analysis requires access to computing resources, familiarity with Unix command line and basic experience with Python or R.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

High-throughput dataset of impurity adsorption on common catalysts in biomass upgrading applications

Abstract An extensive dataset consisting of adsorption energies of pernicious impurities present in biomass upgrading processes on common catalysts and support materials has been generated. This work aims to inform catalyst and process development for the conversion of biomass-derived feedstocks to fuels and chemicals. A high-throughput workflow was developed to execute density functional theory calculations for a diverse set of atomic (Al, B, Ca, Cl, Fe, K, Mg, Mn, N, Na, P, S, Si, Zn) and molecular (COS, H 2 S, HCl, HCN, K 2 O, KCl, NH 3 ) species on 35 unique surfaces for transition-metal (Ag, Au, Co, Cu, Fe, Ir, Ni, Pd, Pt, Re, Rh, Ru) and metal-oxide (Al 2 O 3 , MgO, anatase-TiO 2 , rutile-TiO 2 , ZnO, ZrO 2 ) catalysts and supports. Approximately 3,000 unique adsorption geometries and corresponding adsorption energies were obtained.

09 BIOMASS FUELS↗
DOE OSTI2019

High-throughput investigation of crystal-to-glass transformation of Ti–Ni–Cu ternary alloy

A high-throughput investigation of metallic glass formation via solid-state reaction was reported in this paper. Combinatorial multilayered thin-film chips covering the entire Ti-Ni-Cu ternary system were prepared using ion beam sputtering technique. Microbeam synchrotron X-ray diffraction (XRD) and X-ray fluorescence (XRF) measurements were conducted, with 1,325 data points collected from each chip, to map out the composition and the phase constitution before and after annealing at 373 K for 110 hours. The composition dependence of the crystal-to-glass transition by solid-state reaction was surveyed using this approach. The resulting composition-phase map is consistent with previously reported results. Time-of-flight secondary ion mass spectroscopy (ToF-SIMS) was performed on the representative compositions to determine the inter-diffusion between layers, the result shows that the diffusion of Ti is the key factor for the crystal-to-glass transition. In addition, both layer thickness and layer sequence play important roles as well. This work demonstrates that combinatorial chip technique is an efficient way for systematic and rapid study of crystal-to-glass transition for multi-component alloy systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multi-beam X-ray ptychography for high-throughput coherent diffraction imaging

X-ray ptychography is a rapidly developing coherent diffraction imaging technique that provides nanoscale resolution on extended field-of-view. However, the requirement of coherence and the scanning mechanism limit the throughput of ptychographic imaging. Herein, we propose X-ray ptychography using multiple illuminations instead of single illumination in conventional ptychography. Multiple locations of the sample are simultaneously imaged by spatially separated X-ray beams, therefore, the obtained field-of-view in one scan can be enlarged by a factor equal to the number of illuminations. We have demonstrated this technique experimentally using two X-ray beams focused by a house-made Fresnel zone plate array. Two areas of the object and corresponding double illuminations were successfully reconstructed from diffraction patterns acquired in one scan, with image quality similar with those obtained by conventional single-beam ptychography in sequence. Multi-beam ptychography approach increases the imaging speed, providing an efficient way for high-resolution imaging of large extended specimens.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Enabling high-throughput enzyme discovery and engineering with a low-cost, robot-assisted pipeline

Abstract As genomic databases expand and artificial intelligence tools advance, there is a growing demand for efficient characterization of large numbers of proteins. To this end, here we describe a generalizable pipeline for high-throughput protein purification using small-scale expression in E. coli and an affordable liquid-handling robot. This low-cost platform enables the purification of 96 proteins in parallel with minimal waste and is scalable for processing hundreds of proteins weekly per user. We demonstrate the performance of this method with the expression and purification of the leading poly(ethylene terephthalate) hydrolases reported in the literature. Replicate experiments demonstrated reproducibility and enzyme purity and yields (up to 400 µg) sufficient for comprehensive analyses of both thermostability and activity, generating a standardized benchmark dataset for comparing these plastic-degrading enzymes. The cost-effectiveness and ease of implementation of this platform render it broadly applicable to diverse protein characterization challenges in the biological sciences.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-throughput feedback-enabled optogenetic stimulation and spectroscopy in microwell plates

Abstract The ability to perform sophisticated, high-throughput optogenetic experiments has been greatly enhanced by recent open-source illumination devices that allow independent programming of light patterns in single wells of microwell plates. However, there is currently a lack of instrumentation to monitor such experiments in real time, necessitating repeated transfers of the samples to stand-alone analytical instruments, thus limiting the types of experiments that could be performed. Here we address this gap with the development of the optoPlateReader (oPR), an open-source, solid-state, compact device that allows automated optogenetic stimulation and spectroscopy in each well of a 96-well plate. The oPR integrates an optoPlate illumination module with a module called the optoReader, an array of 96 photodiodes and LEDs that allows 96 parallel light measurements. The oPR was optimized for stimulation with blue light and for measurements of optical density and fluorescence. After calibration of all device components, we used the oPR to measure growth and to induce and measure fluorescent protein expression in E. coli . We further demonstrated how the optical read/write capabilities of the oPR permit computer-in-the-loop feedback control, where the current state of the sample can be used to adjust the optical stimulation parameters of the sample according to pre-defined feedback algorithms. The oPR will thus help realize an untapped potential for optogenetic experiments by enabling automated reading, writing, and feedback in microwell plates through open-source hardware that is accessible, customizable, and inexpensive.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

High-throughput screening for discovery of benchtop separations systems for selected rare earth elements

Abstract Rare earth (RE) elements (scandium, yttrium, and the lanthanides) are critical for their role in sustainable energy technologies. Problems with their supply chain have motivated research to improve separations methods to recycle these elements from end of life technology. Toward this goal, we report the synthesis and characterization of the ligand tris[(1-hydroxy-2-oxo-1,2-dihydropyridine-3-carboxamido)ethyl]amine, H 3 1·TFA (TFA = trifluoroacetic acid), and complexes 1·RE (RE = La, Nd, Dy). A high-throughput experimentation (HTE) screen was developed to quantitatively determine the precipitation of 1·RE as a function of pH as well as equivalents of H 3 1·TFA. This method rapidly determines optimal conditions for the separation of RE mixtures, while minimizing materials consumption. The HTE-predicted conditions are used to achieve the lab-scale separation of Nd/Dy ( SF Nd/Dy = 213 ± 34) and La/Nd ( SF La/Nd = 16.2 ± 0.2) mixtures in acidic aqueous media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Gapped metals as thermoelectric materials revealed by high-throughput screening

The typical strategy to design high performance thermoelectric materials is to dope a semiconducting material until optimal properties are obtained. However, some known thermoelectric materials such as La 3 Te 4 , Mo 3 Sb 7 , Yb 14 MnSb 11 , and NbCoSb are actually gapped metals,i.e., their band structure displays a gap slightly above or below the band crossed by the Fermi level. This key feature makes these metals comparable to degenerate semiconductors and thus suitable for thermoelectric applications. In this work, we perform a computational high-throughput search for such gapped metals exhibiting attractive thermoelectric properties. Several thousands of metals are found to present this key feature, and about one thousand of them show decent thermoelectric properties as evaluated by a computed zT. We present the different chemistry of gapped metals we discovered such as clathrates, Chevrel phases, or transition metal dichalcogenides and discuss their previous studies as thermoelectric and their potential as new thermoelectric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High throughput exploration of the oxidation landscape in high entropy alloys

We report high entropy alloys (HEAs) have gained interest for structural applications in extreme environments. With a potentially vast chemical and phase space, there are significant opportunities to discover superior performing alloys. Crucial for most high-temperature applications is understanding and mitigating the oxidation behavior of these chemically complex alloys. Most experimental and computational HEA studies have focused on a limited set of compositions and only a fraction these compositions have been characterized for oxidation. We present a high-throughput framework that utilizes density-functional theory (DFT) in concert with a combined machine-learning model and grand-canonical linear programming for assessing phase stability, phase-fraction, chemical activity and high-temperature survivability of arbitrary HEAs. This framework considers temperature dependent contributions to the Gibbs energy of the competing phases arising from short-range order and vibrational entropy. We demonstrate the effectiveness of the framework by assessing the thermodynamic stability, oxidation behavior, chemical activity, and phase decomposition of body-centered cubic Mo-W-Ta-Ti-Zr refractory HEAs. A total of 51 compositions were analyzed and ranked in order of their survivability based on the Pareto-front analysis. Oxidation was performed at 1373 K on fours samples in air showing the difference in oxidation behavior determined experimentally through scale thickness and their mass changes. The insights on oxidation behavior presented in this work will enable the fast assessment of technologically useful HEAs needed for future structural application in extreme conditions

36 MATERIALS SCIENCE↗
DOE OSTI2022

Detection of multi-reference character imbalances enables a transfer learning approach for virtual high throughput screening with coupled cluster accuracy at DFT cost

Appropriately identifying and treating molecules and materials with significant multi-reference (MR) character is crucial for achieving high data fidelity in virtual high-throughput screening (VHTS). Despite development of numerous MR diagnostics, the extent to which a single value of such a diagnostic indicates the MR effect on a chemical property prediction is not well established. We evaluate MR diagnostics for over 10 000 transition-metal complexes (TMCs) and compare to those for organic molecules. We observe that only some MR diagnostics are transferable from one chemical space to another. By studying the influence of MR character on chemical properties (i.e., MR effect) that involve multiple potential energy surfaces (i.e., adiabatic spin splitting, ΔE H–L , and ionization potential, IP), we show that differences in MR character are more important than the cumulative degree of MR character in predicting the magnitude of an MR effect. Motivated by this observation, we build transfer learning models to predict CCSD(T)-level adiabatic ΔE H–L and IP from lower levels of theory. By combining these models with uncertainty quantification and multi-level modeling, we introduce a multi-pronged strategy that accelerates data acquisition by at least a factor of three while achieving coupled cluster accuracy (i.e., to within 1 kcal mol –1 MAE) for robust VHTS.

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

High throughput discovery of ternary Cu-Fe-Ru alloy catalysts for photo-driven hydrogen production

Light driven hydrogen production from the water splitting reaction has the ability to reduce dependence on fossil fuels in a green energy future. Here, we highlight the discovery of Cu x Ru y Fe 1-x-y nanoparticle catalysts for photo-driven hydrogen production. Through a high throughput experimental setup, robust data management pipelines and intentional experimental design, this study uncovered three highly active bimetallic systems for photo-driven hydrogen and identified a new trimetallic catalyst for this system. In most cases, the multimetallic catalysts outperformed the monometallics. Furthermore, this study highlights the expansive catalytic screening capabilities of this system in contrast to traditional catalytic selection processes through the discovery of distributions of particle compositions in binary and ternary mixtures of metals with high activity for hydrogen evolution.

08 HYDROGEN↗