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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Screening of the Suzuki Cross-Coupling Reaction Using Desorption Electrospray Ionization in High-Throughput and in Leidenfrost Droplet Experiments

Suzuki cross-coupling is a widely performed reaction, typically using metal catalysts under heated conditions. Acceleration of the Suzuki cross-coupling reaction has been previously explored in microdroplets using desorption electrospray ionization mass spectrometry (DESI-MS). Building upon previous work, presented here is the use of a high-throughput DESI-MS screening system to identify optimal reaction conditions. Multiple reagents, bases, and stoichiometries were screened using the automated system at rates that approach 10,000 reaction mixture systems per hour. The DESI-MS system utilizes reaction acceleration in microdroplets to allow rapid screening. The results of screening of an array of reaction mixtures using this technique are presented as product ion images via standard MS imaging software, facilitating quick readout. Instructive comparisons are provided with another method of generating droplets for reaction acceleration—the Leidenfrost technique. Acceleration factors greater than 200 were measured for brominated substrates, paralleling the DESI-MS results. Acceleration factors dropped to near unity with highly substituted pyridines, attributable to a steric effect. The reaction proceeded in the absence of a base in Leidenfrost droplets although no product formation was seen without base in the bulk or in the DESI-MS screening experiments. These differences between Leidenfrost chemistry and the bulk and in droplets formed in high-throughput DESI are tentatively attributed to extremes of pH associated with the surfaces of Leidenfrost droplets. .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

On-the-fly machine-learning for high-throughput experiments: search for rare-earth-free permanent magnets

Advanced materials characterization techniques with ever-growing data acquisition speed and storage capabilities represent a challenge in modern materials science, and new procedures to quickly assess and analyze the data are needed. Machine learning approaches are effective in reducing the complexity of data and rapidly homing in on the underlying trend in multi-dimensional data. Here, we show that by employing an algorithm called the mean shift theory to a large amount of diffraction data in high-throughput experimentation, one can streamline the process of delineating the structural evolution across compositional variations mapped on combinatorial libraries with minimal computational cost. Data collected at a synchrotron beamline are analyzed on the fly, and by integrating experimental data with the inorganic crystal structure database (ICSD), we can substantially enhance the accuracy in classifying the structural phases across ternary phase spaces. We have used this approach to identify a novel magnetic phase with enhanced magnetic anisotropy which is a candidate for rare-earth free permanent magnet.

Kusne, AG↗
DOE OSTI2018

High-throughput sequencing of the chloroplast and mitochondrion of Chlamydomonas reinhardtii to generate improved de novo assemblies, analyze expression patterns and transcript speciation, and evaluate diversity among laboratory strains and wild isolates

Chlamydomonas reinhardtii is a unicellular chlorophyte alga that is widely studied as a reference organism for understanding photosynthesis, sensory and motile cilia, and for development of an algal-based platform for producing biofuels and bio-products. Its highly repetitive, ~205-kbp circular chloroplast genome and ~15.8-kbp linear mitochondrial genome were sequenced prior to the advent of high-throughput sequencing technologies. Here, high coverage shotgun sequencing was used to assemble both organellar genomes de novo. These new genomes correct dozens of errors in the prior genome sequences and annotations. Gen-ome sequencing coverage indicates that each cell contains on average 83 copies of the chloroplast genome and 130 copies of the mitochondrial genome. Using protocols and analyses optimized for organellar tran-scripts, RNA-Seq was used to quantify their relative abundances across 12 different growth conditions. Forty-six percent of total cellular mRNA is attributable to high expression from a few dozen chloroplast genes. RNA-Seq data were used to guide gene annotation, to demonstrate polycistronic gene expression, and to quantify splicing of psaA and psbA introns. In contrast to a conclusion from a recent study, we found that chloroplast transcripts are not edited. Unexpectedly, cytosine-rich polynucleotide tails were observed at the 3’-end of all mitochondrial transcripts. A comparative genomics analysis of eight laboratory strains and 11 wild isolates of C. reinhardtii identified 2658 variants in the organellargenomes, which is 1/10th as much genetic diversity as is found in the nucleus.

ftsH↗
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 OSTI2019

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to characterize. However, to understand the thermodynamic and kinetic controls on greenhouse gas (carbon dioxide [CO 2 ] and methane [CH 4 ]) production resulting from the decomposition of NOM, a molecular-level characterization coupled with microbial proteome analyses is necessary. Further, climate and environmental changes are expected to perturb natural ecosystems, potentially upsetting complex interactions that influence both the supply of organic matter substrates and the microorganisms performing the transformations. A detailed molecular characterization of the organic matter, microbial proteomics, and the pathways and transformations by which organic matter is decomposed will be necessary to predict the direction and magnitude of the effects of environmental changes. This article describes a methodological throughput for comprehensive metabolite characterization in a single sample by direct injection Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), gas chromatography mass spectrometry (GC-MS), nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography mass spectrometry (LC-MS), and proteomics analysis. Furthermore, this approach results in a fully-paired dataset which improves statistical confidence for inferring pathways of organic matter decomposition, the resulting CO 2 and CH 4 production rates, and their responses to environmental perturbation. Herein we present results of applying this method to NOM samples collected from peatlands; however, the protocol is applicable to any NOM sample (e.g., peat, forested soils, marine sediments, etc.).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Component Particle Structure in Heterogeneous Disordered Ensembles Extracted from High-Throughput Fluctuation X-Ray Scattering

The ring angular correlation function is a characteristic feature determined by the particle structure. Averaging over a large number of ring angular correlation functions calculated from x-ray diffraction patterns will cancel out the cross correlations between different particles and converge to the autocorrelation functions of single particles. Applied on heterogeneous disordered ensembles, the retrieved function is a linear combination of a single-particle autocorrelation function multiplied by the molar ratios in a heterogeneous system. Using this relation, the ring angular correlation functions of the individual component particles in the heterogeneous system can be retrieved through the high throughput fluctuation x-ray scattering technique. This method is demonstrated with a simulated heterogeneous system composed of nanorods, nanoprism, and nanorice.

Fluctuation X-ray Scattering, high throughput, Het↗
DOE OSTI2021

A High-Throughput Method to Define Additive Manufacturing Process Parameters: Application to Haynes 282

This paper demonstrates how an analytical and experimental method can be used to rapidly define the 45 additive manufacturing settings for a new alloy where the process parameters were previously unknown. A nickel-based superalloy, Haynes 282, was chosen for the analysis. An experimental matrix of focused processing parameters was predicted with a dimensionless number and 100 samples were printed using the Selective Laser Melting technique. High-throughput measurements validated the predicted process conditions needed to achieve desired density and hardness. The whole process was completed in 16 hours. The new technique was confirmed with analytical processing maps adopted by the metal additive manufacturing community. With the predicted set of process parameters, microstructural characterizations and tensile testing were used to confirm the predictions. The resultant as-fabricated microstructures have refined length scales of both microsegregation and secondary phase distributions. As a result, the mechanical properties were comparable within the predicted processing window and exhibited high strength and high ductility.

Laser Material Processing↗
DOE OSTI2015

A generalized method for high throughput in-situ experiment data analysis: An example of battery materials exploration

A generalized method is introduced to extract critical information from series of ranked correlated data. The method is generally applicable to all types of spectra evolving as a function of any arbitrary parameter. This approach is based on correlation functions and statistical scedasticity formalism. Numerous challenges in analyzing high throughput experimental data can be tackled using the herein proposed method. We applied this method to understand the reactivity pathway and formation mechanism of a Li-ion battery cathode material during high temperature synthesis using in-situ highenergy X-ray diffraction. We demonstrate that Pearson's correlation function can easily unravel all major phase transition and, more importantly, the minor structural changes which cannot be revealed by conventionally inspecting the series of diffraction patterns. Furthermore, a two-dimensional (2D) reactivity pattern calculated as the scedasticity along all measured reciprocal space of all successive diffraction pattern pairs unveils clearly the structural evolution path and the active areas of interest during the synthesis. The methods described here can be readily used for on-the-fly data analysis during various in-situ operando experiments in order to quickly evaluate and optimize experimental conditions, as well as for post data analysis and large data mining where considerable amount of data hinders the feasibility of the investigation through point-by-point inspection.

25 ENERGY STORAGE↗
DOE OSTI2018

Assessing High-Throughput Descriptors for Prediction of Transparent Conductors

The growth of materials databases has offered significant quantities of data to mine for new energy materials using high-throughput screening methodologies. One application of interest to energy and optoelectronics is the prediction of new high performing p-type transparent conductors (TCs). Yet, screening methods for such materials have never been validated over the breadth of computed materials properties. In this study, we compile an experimental data set of 74 bulk crystal structures corresponding to known state-of-the-art n-type and p-type TCs and compute a series of corresponding computational descriptor properties. Our goals are to (1) compare computational descriptors to experimentally demonstrated properties of real materials in the data set, (2) determine the ability of ground state, density functional theory (DFT)-based computational screening methodologies to identify these experimentally realized TCs, and (3) use this understanding to estimate reasonable screening cutoffs for four commonly used descriptors. First, stability calculations demonstrate that most materials in the data set have an energy above the convex hull ( E hull ) of <100 meV/atom, and we also propose a Pourbaix analysis technique to estimate moisture stability. Second, we find a lenient cutoff for the DFT PBE band gap of 0.5 eV is sufficient to include a majority of the wide gap candidates and exclude narrow gap compounds. Next, the effective mass, m *, is found to correlate weakly to conductivity in the p-type materials as compared with n-type materials, which may motivate an increase in the m * cutoff as well. Lastly, we perform an uncertainty analysis and literature comparison for the branch point energy (BPE), a qualitative descriptor for dopability. We discover the BPEs of most n-type materials to lie near the conduction band and those of most p-type materials to lie at midgap; this is a significant distinction, implying BPE to be a more definitive descriptor for n-type TC materials. By assessing the validity of this simple screening methodology via comparing experimental data to computational descriptors, we aim to motivate and strengthen future materials discovery efforts in the field of transparent conductors and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2018

X-ray spectrometer throughput model for (selected) flat Bragg crystal spectrometers on laser plasma facilities

At large laser faculties, such as OMEGA and the National Ignition Facility (NIF), x-ray spectrometers are provided by the facility to diagnose plasma conditions or monitor backlighters. Often the calibration of these spectrometers is unknown or out of date. In response to this situation, we present a simple ray trace method to calibrate flat crystal spectrometers using only basic information regarding the optical design of the spectrometer. This model is then used to output photometric throughput estimates, dispersion, solid angle, and spectral resolution estimates. This model is applied to the mono angle crystal spectrometer and Super Snout I at the NIF and the X-Ray Spectrometer at the OMEGA laser facility

47 OTHER INSTRUMENTATION↗
DOE OSTI2010

Cosputtered composition-spread reproducibility established by high-throughput x-ray fluorescence

We describe the characterization of sputtered yttria-zirconia composition spread thin films by x-ray fluorescence (XRF). We also discuss our automated analysis of the XRF data, which was collected in a high throughput experiment at the Cornell High Energy Synchrotron Source. The results indicate that both the composition reproducibility of the library deposition and the composition measurements have a precision of better than 1 atomic percent.

36 MATERIALS SCIENCE↗