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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 OSTI2026

Splat Quenching as a High Throughput Rapid Solidification Testing Method for Developing Additive Manufacturing Alloys

Splat quenching as a high throughput rapid solidification screening tool is evaluated. Samples were made using known alloys (SS316, IN625, Ti-5553) to evaluate and establish the microstructures for a variety of alloy systems as well as the predicted cooling rates. The samples are inductively heated and levitated prior to being struck between two platens that produce a high contact pressure and a thin sample resulting in cooling rates on the order of 10 6 to 10 7 K/s. Process parameters were evaluated with analytical models in addition to numerical simulations to provide an effect of process variables such as substrate material, melt superheat, and platen velocity on the resulting solidification. The splat thickness was found to be controlled by platen velocity, melt superheat, as well as the feedstock volume. The sample thickness is the key controlling factor for varying the average cooling rate experienced by the splat quenched sample. The splat quenching techniques can reach regions of rapid solidification space that meet and exceed laser and electron beam techniques across the sample. In conclusion, the results of the study provide a useful foundation in understanding the splat quenching technique and its potential as a low effort tool to explore rapid solidification effects on alloys.

Alloy Design↗
DOE OSTI2021

New high-throughput endstation to accelerate the experimental optimization pipeline for synchrotron X-ray footprinting

Synchrotron X-ray footprinting (XF) is a growing structural biology technique that leverages radiation-induced chemical modifications via X-ray radiolysis of water to produce hydroxyl radicals that probe changes in macromolecular structure and dynamics in solution states of interest. The X-ray Footprinting of Biological Materials (XFP) beamline at the National Synchrotron Light Source II provides the structural biology community with access to instrumentation and expert support in the XF method, and is also a platform for development of new technological capabilities in this field. Hee, the design and implementation of a new high-throughput endstation device based around use of a 96-well PCR plate form factor and supporting diagnostic instrumentation for synchrotron XF is described. This development enables a pipeline for rapid comprehensive screening of the influence of sample chemistry on hydroxyl radical dose using a convenient fluorescent assay, illustrated here with a study of 26 organic compounds. The new high-throughput endstation device and sample evaluation pipeline now available at the XFP beamline provide the worldwide structural biology community with a robust resource for carrying out well optimized synchrotron XF studies of challenging biological systems with complex sample compositions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Optimizing metaproteomics database construction: lessons from a study of the vaginal microbiome

Metaproteomics, a method for untargeted, high-throughput identification of proteins in complex samples, provides functional information about microbial communities and can tie functions to specific taxa. Metaproteomics often generates less data than other omics techniques, but analytical workflows can be improved to increase usable data in metaproteomic outputs. Identification of peptides in the metaproteomic analysis is performed by comparing mass spectra of sample peptides to a reference database of protein sequences. Although these protein databases are an integral part of the metaproteomic analysis, few studies have explored how database composition impacts peptide identification. Here, we used cervicovaginal lavage (CVL) samples from a study of bacterial vaginosis (BV) to compare the performance of databases built using six different strategies. We evaluated broad versus sample-matched databases, as well as databases populated with proteins translated from metagenomic sequencing of the same samples versus sequences from public repositories. Smaller sample-matched databases performed significantly better, driven by the statistical constraints on large databases. Additionally, large databases attributed up to 34% of significant bacterial hits to taxa absent from the sample, as determined orthogonally by 16S rRNA gene sequencing. We also tested a set of hybrid databases which included bacterial proteins from NCBI RefSeq and translated bacterial genes from the samples. These hybrid databases had the best overall performance, identifying 1,068 unique human and 1,418 unique bacterial proteins, ~30% more than a database populated with proteins from typical vaginal bacteria and fungi. Our findings can help guide the optimal identification of proteins while maintaining statistical power for reaching biological conclusions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2018

Software System for the Mars 2020 Mission Sampling and Caching Testbeds

The development of the Sampling and Caching Subsystem (SCS) of the Mars 2020 Rover Mission is highly dependent on testing of prototype hardware and software operating in explicit conditions as part of integrated testbeds. To achieve relevant integration of hardware and software while maintaining rapid algorithm development capabilities and high testing throughput, the Controls and Autonomy for Sample Acquisition and Handling (CASAH) software system was developed. CASAH is an implementation of the Intelligent Robotics System Architecture (IRSA),which mimics JPL Flight Software (FSW) in that it is divided into hierarchical modules that run separate processes that communicate via message passing, each module is assigned an owner that is a single developer, and the operator initiates requests via a text-based interface that interprets sequences of commands.IRSA enables a modular breakdown of CASAH that follows that of 2020 Flight Software,so developers can take an algorithm from a module in CASAH and re-code it into the same module in FSW. As deployment of CASAH has grown to ten testbeds - each with different hardware and objectives - bottom-up design decisions have been intentionally made to keep the system lightweight and maintainable by a very small team. To date, CASAH has been used to run 1393 different tests. This work describes CASAH, the testbeds and functionality it supports, the tools used to manage the development and sharing of code, and the features of the software. Lessons learned over the past three years of development and deployment are provided.

Vieira, Peter↗
DOE OSTI2023

Metabolic multireactor: Practical considerations for using simple oxygen sensing optodes for high-throughput batch reactor metabolism experiments

We present a system for carrying out small batch reactor oxygen consumption experiments on water and sediment samples for environmental questions. In general, it provides several advantages that can help researchers achieve impactful experiments at relatively low costs and high data quality. In particular, it allows for multiple reactors to be operated and their oxygen concentrations to be measured simultaneously, providing high throughput and high time-resolution data, which can be advantageous. Most existing literature on similar small batch-reactor metabolic studies is limited to either only a few samples, or only a few time points per sample, which can restrict the ability for researchers to learn from their experiments. The oxygen sensing system is based very directly on the work of Larsen, et al. [2011], and similar oxygen sensing technology is widely used in the literature. As such we do not delve deeply into the specifics of the fluorescent dye sensing mechanism. Instead, we focus on practical considerations. We describe the construction and operation of the calibration and experimental systems, and answer many of the questions likely to come up when other researchers choose to build and operate a similar system themselves (questions we ourselves had when we first built the system). In this way, we hope to provide an approachable and easy to use research article that can help other researchers construct and operate a similar system that can be tailored to ask their own research questions, with a minimum of confusion and missteps along the way.

3D printing↗
DOE OSTI2021

Assessment of TMT Labeling Efficiency in Large-Scale Quantitative Proteomics: The Critical Effect of Sample pH

Isobaric labeling via tandem mass tag (TMT) reagents enables sample multiplexing prior to LC–MS/MS, facilitating high-throughput large-scale quantitative proteomics. Consistent and efficient labeling reactions are essential to achieve robust quantification; therefore, embedded in our clinical proteomic protocol is a quality control (QC) sample that contains a small aliquot from each sample within a TMT set, referred to as “Mixing QC.” This Mixing QC enables the detection of TMT labeling issues by LC–MS/MS before combining the full samples to allow for salvaging of poor TMT labeling reactions. While TMT labeling is a valuable tool, factors leading to poor reactions are not fully studied. We observed that relabeling does not necessarily rescue TMT reactions and that peptide samples sometimes remained acidic after resuspending in 50 mM HEPES buffer (pH 8.5), which coincided with low labeling efficiency (LE) and relatively low median reporter ion intensities (MRIIs). To obtain a more resilient TMT labeling procedure, we investigated LE, reporter ion missingness, the ratio of mean TMT set MRII to individual channel MRII, and the distribution of log 2 reporter ion ratios of Mixing QC samples. We discovered that sample pH is a critical factor in LE, and increasing the buffer concentration in poorly labeled samples before relabeling resulted in the successful rescue of TMT labeling reactions. Moreover, resuspending peptides in 500 mM HEPES buffer for TMT labeling resulted in consistently higher LE and lower missing data. By better controlling the sample pH for labeling and implementing multiple methods for assessing labeling quality before combining samples, we demonstrate that robust TMT labeling for large-scale quantitative studies is achievable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A Smart Vision-Aided RICH (Robotic Interface Control and Handling) System for VULCAN

High-flux neutron beams and high-efficiency detectors enable rapid neutron diffraction measurements at the Engineering Materials Diffractometer (VULCAN) at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory (ORNL). To optimize beam time utilization, efficient sample exchange, alignment, and automated measurements are essential. Recent advances in artificial intelligence (AI) have expanded the capabilities of robotic systems. Here, we report the development of a Robotic Interactive Control and Handling (RICH) system for sample handling at VULCAN, designed to support high-throughput experiments and reduce overhead time. The RICH system employs a six-axis desktop robot integrated with AI-based computer vision models capable of recognizing and localizing samples in real time from instrument and depth-resolving cameras. Vision algorithms combine these detections to align samples with designated measurement positions or place them within complex sample environments such as furnaces. This integration of machine learning-assisted vision with robotic handling demonstrates the feasibility of autonomous sample detection and preparation, offering a pathway toward fully unmanned neutron scattering experiments.

automation↗
DOE OSTI2026

Simultaneous Determination of Halogens and Metals in Waste Plastic Pyrolysis Oil by Inductively Coupled Plasma Mass Spectrometry

A major barrier to integrating pyrolysis-derived oil into conventional refinery technology is the presence of impurities, particularly halogens and metals, that can deactivate catalysts. This study presents a novel, cost-effective approach for the simultaneous analysis of a subset of halogens, metals, nonmetals, and metalloids in complex, industrially relevant distilled pyrolysis oil samples, this was previously achievable only through multiple techniques. Excellent results were obtained using a widely accessible inductively coupled plasma mass spectrometry (ICP-MS) method with helium gas mode and standard laboratory consumables, enabling high-throughput analysis and efficient evaluation of adsorbent performance. Sample preparation is straightforward, requiring only dilution in a compatible matrix, and provides accurate and precise quantification, with 75%–137% spike recovery for Be, Ti, V, Cr, Fe, Ni, Co, Cu, As, Se, Mo, Cd, Sb, Tl, and Pb, and 62%–65% spike recovery for Cl and 109%–133% spike recovery for Br. Additionally, an enhanced version of the method using ICP-MS/MS and hydrogen gas is described, which has higher accuracy with 69%–112% spike recovery for Be, B, Ti, V, Fe, Co, Ni, Cu, As, Se, Mo, Cd, Sb, Tl, and Pb, with 85%–102% spike recovery for Cl and 63%–93% spike recovery for Br. Helium mode detection limits for industrially relevant elements (V, Fe, Ni, Cu, As, and Pb) are less than 1.7 µg/kg, and less than 0.2 mg/kg for Br and Cl. Furthermore, this methodology facilitates rapid systematic evaluation of adsorption capacities of materials under time-on-stream conditions and supports robust comparisons across diverse operating environments.

Lazarcik, James [University of Wisconsin-Madison, ↗
DOE OSTI2024

High throughput battery failure experimental platform

Addressing the need to increase the sample set to understand the causes of lithium battery thermal runaway, we conceived of an experimental platform with capability to increase the number of runaway experiments (currently 3-5 per week), while also collecting detailed electrochemical impedance spectroscopy measurements (EIS). Once expanded, the platform would enable data collection on 10s to 100s of cells that all experience runaway, thereby creating a statistical database necessary to identify early indication of risk. A primary containment unit to house cylindrical cells of variety NMC811 and of size 21700 (21 mm diameter by 70 mm length) was designed with features such as debris containment, preloaded cells in an exchangeable port, nitrogen ventilation, and exhaust containment. We performed the first overcharge abuse experiments of several 21700 cells, handpicked because of different initial EIS, and demonstrated that EIS changes dramatically during early stages of overcharge, but in a different manner than previous pouch cell experiments. The abuse experiments also revealed the discharge pattern and debris field created during runaway, as well as the cell temperature control and overheat, that must be considered in the primary containment apparatus. We designed and built a switching relay system to permit measurement of EIS without an active charging circuit, and created instrument control software for charging, EIS, and cell temperature control. The late-start funding was insufficient to fully construct the primary containment unit, but the foundational design and knowhow is available for any future work.

25 ENERGY STORAGE↗
DOE OSTI2024

RT-QuIC detection of chronic wasting disease prion in platelet samples of white-tailed deer

Chronic wasting disease (CWD) is a prion disease of captive and free-ranging cervids. Currently, a definitive diagnosis of CWD relies on immunohistochemistry detection of PrP Sc in the obex and retropharyngeal lymph node (RPLN) of the affected cervids. For high-throughput screening of CWD in wild cervids, RPLN samples are tested by ELISA followed by IHC confirmation of positive results. Recently, real-time quacking-induced conversion (RT-QuIC) has been used to detect CWD positivity in various types of samples. To develop a blood RT-QuIC assay suitable for CWD diagnosis, this study evaluated the assay sensitivity and specificity with and without ASR1-based preanalytical enrichment and NaI as the main ionic component in assay buffer. A total of 23 platelet samples derived from CWD-positive deer (ELISA +/IHC +) and 30 platelet samples from CWD-negative (ELISA-) deer were tested. The diagnostic sensitivity was 43.48% (NaCl), 65.22% (NaI), 60.87% (NaCl-ASR1) or 82.61% (NaI-ASR1). The diagnostic specificity was 96.67% (NaCl), 100% (NaI), 100% (NaCl-ASR1), or 96.67% (NaI-ASR1). The probability of detecting CWD prion in platelet samples derived from CWD-positive deer was 0.924 (95% CRI: 0.714, 0.989) under NaI-ASR1 experimental condition and 0.530 (95% CRI: 0.156, 0.890) under NaCl alone condition. The rate of amyloid formation (RFA) was greatest under the NaI-ASR1 condition at 10 -2 (0.01491, 95% CRI: 0.00675, 0.03384) and 10 -3 (0.00629, 95% CRI: 0.00283, 0.01410) sample dilution levels. Incorporation of ASR1-based preanalytical enrichment and NaI as the main ionic component signifcantly improved the sensitivity of CWD RT-QuIC on deer platelet samples. Blood test by the improved RT-QuIC assay may be used for antemortem and postmortem diagnosis of CWD.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A capillary-based microfluidic device enables primary high-throughput room-temperature crystallographic screening

A novel capillary-based microfluidic strategy to accelerate the process of small-molecule-compound screening by room-temperature X-ray crystallography using protein crystals is reported. The ultra-thin microfluidic devices are composed of a UV-curable polymer, patterned by cleanroom photolithography, and have nine capillary channels per chip. The chip was designed for ease of sample manipulation, sample stability and minimal X-ray background. 3D-printed frames and cassettes conforming to SBS standards are used to house the capillary chips, providing additional mechanical stability and compatibility with automated liquid- and sample-handling robotics. These devices enable an innovative in situ crystal-soaking screening workflow, akin to high-throughput compound screening, such that quantitative electron density maps sufficient to determine weak binding events are efficiently obtained. This work paves the way for adopting a room-temperature microfluidics-based sample delivery method at synchrotron sources to facilitate high-throughput protein-crystallography-based screening of compounds at high concentration with the aim of discovering novel binding events in an automated manner.

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

Non-target RNA depletion strategy to improve sensitivity of next-generation sequencing for the detection of RNA viruses in poultry

PCR-based assays have become the benchmark for detecting pathogens of poultry and other livestock; however, these techniques are limited in their ability to detect multiple infecting agents, provide limited genetic information on the pathogen, and, for RNA viruses, must be reviewed frequently to assure high sensitivity and specificity. In contrast, untargeted, high-throughput sequencing can rapidly detect all infecting agents in a sample while providing genomic sequence information to allow more in-depth characterization of viruses. Although next-generation sequencing (NGS) offers many advantages, one of its primary limitations is low sensitivity to pathogens given the abundance of host and other non-target sequences in sequencing libraries. We explored methods for improving the sensitivity of NGS to detect respiratory and enteric viruses in poultry from RNA extracts of swab samples. We employed commercial and custom-designed negative enrichment strategies to selectively deplete the most abundant rRNA reads from the host and non-target bacteria; host RNA was diminished from up to 40% of total reads to as low as 3%, and the total number of reads assigned to abundant bacterial classes were reduced greatly. Our treatment resulted in up to a 700-fold increase in the number of viral reads, detection of a greater number of viral agents, and higher average genome coverage for pathogens. Depletion assays added only 2 h to the NGS library preparation workflow. Custom depletion probe design offered significant cost savings (US$7–12 per sample) compared to commercial kits (US$30–50 per sample).

Parris, D. Joshua↗
DOE OSTI2022

Abundance of Major Cell Wall Components in Natural Variants and Pedigrees of Populus trichocarpa

The rapid analysis of biopolymers including lignin and sugars in lignocellulosic biomass cell walls is essential for the analysis of the large sample populations needed for identifying heritable genetic variation in biomass feedstocks for biofuels and bioproducts. In this study, we reported the analysis of cell wall lignin content, syringyl/guaiacyl (S/G) ratio, as well as glucose and xylose content by high-throughput pyrolysis-molecular beam mass spectrometry (py-MBMS) for >3,600 samples derived from hundreds of accessions of Populus trichocarpa from natural populations, as well as pedigrees constructed from 14 parents (7 × 7). Partial Least Squares (PLS) regression models were built from the samples of known sugar composition previously determined by hydrolysis followed by nuclear magnetic resonance (NMR) analysis. Key spectral features positively correlated with glucose content consisted of m/z 126, 98, and 69, among others, deriving from pyrolyzates such as hydroxymethylfurfural, maltol, and other sugar-derived species. Xylose content positively correlated primarily with many lignin-derived ions and to a lesser degree with m/z 114, deriving from a lactone produced from xylose pyrolysis. Models were capable of predicting glucose and xylose contents with an average error of less than 4%, and accuracy was significantly improved over previously used methods. The differences in the models constructed from the two sample sets varied in training sample number, but the genetic and compositional uniformity of the pedigree set could be a potential driver in the slightly better performance of that model in comparison with the natural variants. Broad-sense heritability of glucose and xylose composition using these data was 0.32 and 0.34, respectively. In summary, we have demonstrated the use of a single high-throughput method to predict sugar and lignin composition in thousands of poplar samples to estimate the heritability and phenotypic plasticity of traits necessary to develop optimized feedstocks for bioenergy applications.

09 BIOMASS FUELS↗
DOE OSTI2023

Advanced techniques in automated high-resolution scanning transmission electron microscopy

Scanning transmission electron microscopy is a common tool used to study the atomic structure of materials. It is an inherently multimodal tool allowing for the simultaneous acquisition of multiple information channels. Despite its versatility, however, experimental workflows currently rely heavily on experienced human operators and can only acquire data from small regions of a sample at a time. Here, we demonstrate a flexible pipeline-based system for high-throughput acquisition of atomic-resolution structural data using an all-piezo sample stage applied to large-scale imaging of nanoparticles and multimodal data acquisition. As a result, the system is available as part of the user program of the Molecular Foundry at Lawrence Berkeley National Laboratory.

4D-STEM↗
DOE OSTI2023

Statistical 3D morphology characterization of vaterite microspheres produced by engineered Escherichia coli

Hollow vaterite microspheres are important materials for biomedical applications such as drug delivery and regenerative medicine owing to their biocompatibility, high specific surface area, and ability to encapsulate a large number of bioactive molecules and compounds. We demonstrated that hollow vaterite microspheres are produced by an Escherichia coli strain engineered with a urease gene cluster from the ureolytic bacteria Sporosarcina pasteurii in the presence of bovine serum albumin. We characterized the 3D nanoscale morphology of five biogenic hollow vaterite microspheres using 3D high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) tomography. Using automated high-throughput HAADF-STEM imaging across several sample tilt orientations, we show that the microspheres evolved from a smaller more ellipsoidal shape to a larger more spherical shape while the internal hollow core increased in size and remained relatively spherical, indicating that the microspheres produced by this engineered strain likely do not contain the bacteria. The statistical 3D morphology information demonstrates the potential for using biogenic calcium carbonate mineralization to produce hollow vaterite microspheres with controlled morphologies.

3D morphology↗
NASA NTRS1992

Reconfigurable Fuzzy Cell

Flexible sensor-signal-processing circuit responds rapidly. Reconfigurable fuzzy cell provides real-time, high-throughput, interrupt-driven, multiplex conversion of sample raw signals from sensors into their grade of membership for use in fuzzy-logic control system.

Salazar, George A.↗
DOE OSTI2021

Deep Learning for Rapid Analysis of Spectroscopic Ellipsometry Data

High‐throughput experimental approaches to rapidly develop new materials require high‐throughput data analysis methods to match. Spectroscopic ellipsometry is a powerful method of optical properties characterization, but for unknown materials and/or layer structures the data analysis using traditional methods of nonlinear regression is too slow for autonomous, closed‐loop, high‐throughput experimentation. Herein, three methods (termed spectral, piecewise, and pointwise) of spectroscopic ellipsometry data analysis based on deep learning are introduced and studied. After initial training, the incremental time for inferring optical properties can be a thousand times faster than traditional methods. Results for multilayer sample structures with optically isotropic materials are presented, appropriate for high‐throughput studies of thin films of phase‐change materials such as GeSbTe (GST) alloys. Results for studies on highly birefringent layered materials are also presented, exemplified by the transition metal dichalcogenide MoS 2 . How the materials under test and the experimental objectives may guide the choice of analysis methods are discussed. The utility of our approach is demonstrated by analyzing data measured on a composition spread of GeSbTe phase‐change alloys containing 177 distinct compositions, and identifying the composition with optimal phase‐change figure of merit in only 1.4 s of analysis time.

Li, Yifei↗
DOE OSTI2024

Spatial Proteomics towards cellular Resolution

Introduction: Spatial biology is an emerging interdisciplinary field facilitating biological discoveries through the use of spatial omics technologies. Recent advancements in spatial transcriptomics, spatial genomics (e.g. genetic mutations and epigenetic marks), multiplexed immunofluorescence, and spatial metabolomics/lipidomics have enabled high-resolution spatial profiling of gene expression, genetic variation, protein expression, and metabolites/lipids profiles in tissue. These developments contribute to a deeper understanding of the spatial organization within tissue microenvironments at the molecular level. Areas covered: This report provides an overview of the untargeted, bottom-up mass spectrometry (MS)-based spatial proteomics workflow. It highlights recent progress in tissue dissection, sample processing, bioinformatics, and liquid chromatography (LC)-MS technologies that are advancing spatial proteomics toward cellular resolution. Expert opinion: The field of untargeted MS-based spatial proteomics is rapidly evolving and holds great promise. To fully realize the potential of spatial proteomics, it is critical to advance data analysis and develop automated and intelligent tissue dissection at the cellular or subcellular level, along with high-throughput LC-MS analyses of thousands of samples. In conclusion, achieving these goals will necessitate significant advancements in tissue dissection technologies, LC-MS instrumentation, and computational tools.

59 BASIC BIOLOGICAL SCIENCES↗