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Results for “High throughput characterization”

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 OSTI2021

Laser-based Adhesion Strength Measurements for Advanced Manufactured Sensor Adhesion Characterization

As part of the advanced manufacturing (AM) focus of the Nuclear Energy Enabling Technologies (NEET) Advanced Sensors and Instrumentation (ASI) Program, new in-house capabilities to fabricate and test novel active and passive in-pile sensors are being developed at the Idaho National Laboratory (INL). These advanced-manufactured sensors, such as peak temperature monitors and strain gauges, must be miniaturized and be able to provide real-time feedback, all while withstanding the coupled extremes of temperature and radiation typically observed in the environment of a nuclear test reactor. Fabricating durable and robust in-pile sensors with high fidelity requires a fundamental understanding of the optimal process parameters required in the AM technique, as well as the effect of deviations from optimal process parameters on the sensor-substrate adhesion and the ultimate robustness of the sensor. This report presents the use of a laser-based, non-contact approach for characterizing the adhesion of sensors manufactured using aerosol jet printing (AJP) that comprise of silver nanoparticle inks deposited and sintered on austenitic stainless steel (SS) 316L substrates. The effect of substrate surface roughness, surface energy, ink sintering time and sintering temperature on the printed sensor topography and the sensor-substrate adhesion has been systematically investigated. The sensor-substrate interfacial adhesion strength was determined from the critical laser pulse energy required to ablate/ detach the printed sensor from the substrate. Measurements of the sensor topography using optical profilometry revealed that post-deposition sintering at 400°C for 60 minutes resulted in a reduced sensor thickness, while plasma treating the substrate prior to printing yielded sensors with uniform thickness profiles transverse to the print direction. Sintering temperature and time were found to be the dominant parameters that affected sensor-substrate adhesion, followed by substrate surface roughness. The laser-based and locally-destructive approach for adhesion strength measurements shows promise in overcoming the challenges and limitations of current standardized peel tests and can be developed into a post-fabrication process control protocol for evaluating the durability of AM printed sensors in a high throughput fashion. Future studies will investigate the use of laser-induced spallation techniques as well as non-destructive laser ultrasonic methods for sensor-substrate adhesion characterization on sensors manufactured using AJP and other AM techniques such as plasma jet printing (PJP).

42 ENGINEERING↗
DOE OSTI2024

Accelerating the identification of novel secondary metabolites in bioenergy plant root exudates using MicroED

Small molecule metabolites drive inter- and intraspecies communication and dependencies in diverse biological systems, yet a large proportion of these important chemical compounds remain uncharacterized in plants and microbes. Approximately 90% of the metabolites in root exudate profiles are unknown compounds, despite the importance of root exudate composition in plant-microbe interactions. We need advanced analytical capabilities that will support rapid discovery and structural elucidation of metabolites from biological samples that may be limited in quantity and high in complexity. To fill this gap, this project aimed to develop an integrated workflow involving metabolite extraction, separation, and crystallization from plant root exudates followed by characterization using nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry, and microcrystal electron diffraction (MicroED). Using crude root exudates from sorghum, this project successfully developed higher throughput exudate fractionation strategies to obtain pure compounds for crystallization and identified crystals in multiple fractions that diffracted. Additional efforts to increase the throughput of high-quality crystal generation for MicroED, such as crystallization screening and crystallization chaperone exploration, will be needed to further advance root exudate metabolite identification. The overall optimized sample preparation process can then be integrated with the existing data collection and data analysis pipelines for MicroED at PNNL to facilitate more rapid natural product discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A Six-Membered Concerted Mechanism for CO 2 Capture by Amines Studied under Charged Microdroplet Reaction Conditions

Carbon dioxide (CO 2 ) capture and storage represents an important technological challenge. A mechanistic understanding of interactions involved in the capture process is necessary not only for technological development but also for efficient conversion of captured CO 2 into value-added materials. Herein, we present a novel contained secondary electrospray ionization platform for studying the interactions of gaseous amines and CO 2 gas under microdroplet reaction conditions, which enables mass spectrometry (MS) characterization of CO 2 capture products and intermediates in real time. We detected [2 M + CO 2 + H] + species, which corresponds to a six-membered intermediate. DFT calculations confirmed the high stability of the protonated six-membered ring intermediate. This finding provides a plausible concerted mechanism in the microdroplet environment that excludes the involvement of thermodynamically disfavored ionic species. The carbamic acid counterpart of the final product/salt was readily characterized by tandem MS. The carbamic acid/amine salt was also isolated and characterized by Fourier transform infrared spectroscopy. By virtue of the fact that headspace vapors of amines are sampled, we were able to establish a high-throughput platform that enabled the CO 2 capture capacity of five different amines to be studied in under 2 min. The same device also enabled the absolute quantification of capture capacity.

Amines↗
DOE OSTI2023

Small molecule inhibitors for treatment of alpha viruses

An in vitro assay was designed to measure the activity of the alphavirus non-structural protein 2 (nsP2), which is the viral protease and is required for viral replication. By taking advantage of fluorescence-resonance energy transfer between two proteins, a protease cleavage assay was generated. This was utilized for high-throughput screening of 40,000 small molecules. Inhibitors were validated using cell-based assays to measure alphavirus infection and cytotoxicity. Certain compounds were then characterized for anti-viral efficacy in various cell lines in numerous assays. Compounds were tested against Chikungunya virus, Venezuelan Equine Encephalitis virus, Rift Valley Fever virus, and Zika virus. Three compounds (compounds I, II, and III) showed pan-alphavirus anti-viral efficacy at concentrations that did not result in cell toxicity. An additional compound, structure IV, showed broad spectrum inhibition of all viruses tested. Pharmaceutical preparations and methods of treatment including these compounds are provided herein.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Static characterization of a highly optimized streak tube design incorporating a steering slot anode and an aberration-corrected Einzel lens

The BHx streak tube, under development at the Laboratory for Laser Energetics, incorporates a series of novel electron-optics elements to enable high fidelity measurements for high-energy-density physics experiments. The system is engineered to support a 25-mm active photocathode region compatible with sub-picosecond temporal resolution and with 70% internal photoelectron throughput. It exhibits negligible geometric distortion on a flat output screen, making it well suited for variety of measurements, such as ultrafast x-ray spectroscopy. Here, this paper presents characterization data from a prototype unit tested with an ultraviolet laser in a static deflection (non-swept) mode and shows good agreement with the predictions from numerical modeling, including focusing performance and geometric distortion measurements. Key design elements have been demonstrated and de-risked, laying the foundation for dynamic deflection testing. The anticipated improvements in data fidelity are expected to impact the fields as diverse as inertial confinement fusion, laboratory astrophysics, and materials science.

High energy density physics↗
DOE OSTI2022

Dimensional Control over Metal Halide Perovskite Crystallization Guided by Active Learning

Metal halide perovskite (MHP) derivatives, a promising class of optoelectronic materials, have been synthesized with a range of dimensionalities that govern their optoelectronic properties and determine their applications. We demonstrate a data-driven approach combining active learning and high-throughput experimentation to discover, control, and understand the formation of phases with different dimensionalities in the morpholinium (morph) lead iodide system. Using a robot-assisted workflow, we synthesized and characterized two novel MHP derivatives that have distinct optical properties: a one-dimensional (1D) morphPbI 3 phase ([C 4 H 10 NO][PbI 3 ]) and a two-dimensional (2D) (morph) 2 PbI 4 phase ([C 4 H 10 NO] 2 [PbI 4 ]). To efficiently acquire the data needed to construct a machine learning (ML) model of the reaction conditions where the 1D and 2D phases are formed, data acquisition was guided by a diverse-mini-batch-sampling active learning algorithm, using prediction confidence as a stopping criterion. Querying the ML model uncovered the reaction parameters that have the most significant effects on dimensionality control. Based on these insights, we discuss possible reaction schemes that may selectively promote the formation of morph-Pb-I phases with different dimensionalities. The data-driven approach presented here, including the use of additives to manipulate dimensionality, will be valuable for controlling the crystallization of a range of materials over large reaction-composition spaces.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Investigation of Reactive Silver Ink Formula for Reduced Silver Consumption in Silicon Heterojunction Metallization

Silver is the most expensive non-silicon component in photovoltaic cells. This is particularly salient for silicon heterojunction (SHJ) cells, which rely on large quantities of low-temperature silver pastes (LT-SP). SHJ cells would benefit greatly from an industrially scalable metallization process that simultaneously offers low silver consumption, low finger resistivities (<20 μΩ·cm), and low processing temperatures. Printed reactive silver inks (RSI) are an innovative candidate to this end. Furthermore, this work furthers the research on RSI metallization by investigating the impact of ink formula on properties pertinent to SHJ cells, including electrical properties, line width, ink splatter, silver consumption, cell performance, and adhesion. We introduce a scalable, high-throughput flexible needle contact printing approach for metallization that solves many of the issues associated with drop-on-demand printing. The printed silver fingers are characterized using electrical measurements and top-down and cross-sectional microscopy. The best performing ink, consisting of silver acetate, ethylamine, and formic acid, achieved silver fingers with total resistivities of 3.1 μΩ·cm and contact resistivities of 3.2 mΩ·cm 2 when printed at 61 °C. This ink metallized a full-sized 156 mm × 156 mm SHJ cell. This is the first reported data for RSI metallization of a full-sized SHJ cell and shows how an optimized RSI can achieve similar performances to LT-SP while consuming 80–90% less silver.

14 SOLAR ENERGY↗
DOE OSTI2021

Machine-learning-accelerated multimodal characterization and multiobjective design optimization of natural porous materials

Natural porous materials such as nanoporous clays are used as green and low-cost adsorbents and catalysts. The key factors determining their performance in these applications are the pore morphology and surface activity, which are typically represented by properties such as specific surface area, pore volume, micropore content and pH. The latter may be modified and tuned to specific applications through material processing and/or chemical treatment. Characterization of the material, raw or processed, is typically performed experimentally, which can become costly especially in the context of tuning of the properties towards specific application requirements and needing numerous experiments. In this work, we present an application of tree-based machine learning methods trained on experimental datasets to accelerate the characterization of natural porous materials. The resulting models allow reliable prediction of the outcomes of experimental characterization of processed materials (R2 from 0.78 to 0.99) as well as identification of key factors contributing to those properties through feature importance analysis. Furthermore, the high throughput of the models enables exploration of processing parameter–property correlations and multiobjective optimization of prototype materials towards specific applications. We have applied these methodologies to pinpoint and rationalize optimal processing conditions for clays exploitable in acid catalysis. One of such identified materials was synthesized and tested revealing appreciable acid character improvement with respect to the pristine material. Specifically, it achieved 79% removal of chlorophyll-a in acid catalyzed degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Supported-Single Nickel Atom Catalysts for the Methanation of Carbon Dioxide

Synthesis of twenty-seven bimetallic catalysts consisting of nickel and one of nine different dopants (B, Co, Cu, Fe, Mg, Mn, Sn, V, and Zn) supported on three different metal oxides (Al 2 O 3 , CeO 2 , and SiO 2 ) is carried out via organometallic grafting. The catalysts are evaluated for their activity and selectivity for the CO 2 methanation reaction at a feed ratio of H 2 /CO 2 of 4 at 300 °C in a high-throughput flow reactor system. After in situ pre-activation (500 °C in H 2 ), Ni/Co/CeO 2 exhibited high conversion (84.3%) and selectivity for methane (99.6%). Ni/Co/CeO 2 was characterized by high-resolution transmission electron microscopy (HRTEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction, H 2 -temperature-programmed reduction (H 2 -TPR), and CO 2 -temperature-programmed desorption (CO 2 -TPD). HRTEM showed the presence of single Ni and Co atoms on ceria after pre-reduction at 500 °C and after the methanation reaction at 300 °C for 15 h. XPS determined that the strong interaction between Ni, Co, and ceria increased after the reduction, leading to a charge transfer between Ni and Ce that created oxygen vacancies in ceria. Nickel was found to be Ni 2+ in the as-prepared material and was partially reduced in the presence of cobalt and after the activation in H 2 at 500 °C. The DFT results show that both nickel and cerium exhibit lower Bader charges in the Ni/Co/CeO 2 system, confirming that the presence of cobalt enhances the reduction of both Ni and Ce through electronic interactions. This indicates that single cationic Ni atoms are highly effective for the methanation reaction. In conclusion, the organometallic grafting technique is found to be efficient for synthesizing catalysts with highly homogeneous dispersed species at low metal loadings (0.16 wt % Ni–0.15 wt % Co), which leads to high turnover frequency (up to 248.7 h –1 ) and durability for methanation.

CO2 conversion↗
DOE OSTI2025

A high-throughput approach for statistical process optimization in Laser Powder Bed Fusion

Process variability is inherent in metal additive manufacturing (AM). However, it is often overlooked in process optimization frameworks, constraining the understanding of process uncertainties and their influence on parameter selection. To address this, we present an integrated framework that combines high-throughput single-track experiments, GAN-based melt pool geometry extraction, robust statistical and machine learning modeling, and uncertainty-quantified process mapping. Process variability is characterized through single-track melt pool behaviors, and its influence on defect formation is systematically quantified to enable statistically guided process parameter optimization. This approach is demonstrated on Laser Powder Bed Fusion (L-PBF) of stainless steel 316L, effectively capturing the interplay between process parameters, melt pool variability, and defect probability. By integrating uncertainty quantification into process optimization, this study provides a structured methodology for addressing variability challenges in AM quality control, ultimately contributing to enhanced manufacturing reliability.

Laser Powder Bed Fusion↗
DOE OSTI2023

Metagenomics harvested genus-specific single-stranded DNA-annealing proteins improve and expand recombineering in Pseudomonas species

The widespread Pseudomonas genus comprises a collection of related species with remarkable abilities to degrade plastics and polluted wastes and to produce a broad set of valuable compounds, ranging from bulk chemicals to pharmaceuticals. Pseudomonas possess characteristics of tolerance and stress resistance making them valuable hosts for industrial and environmental biotechnology. However, efficient and high-throughput genetic engineering tools have limited metabolic engineering efforts and applications. To improve their genome editing capabilities, we first employed a computational biology workflow to generate a genus-specific library of potential single-stranded DNA-annealing proteins (SSAPs). Assessment of the library was performed in different Pseudomonas using a high-throughput pooled recombinase screen followed by Oxford Nanopore NGS analysis. Among different active variants with variable levels of allelic replacement frequency (ARF), efficient SSAPs were found and characterized for mediating recombineering in the four tested species. New variants yielded higher ARFs than existing ones in Pseudomonas putida and Pseudomonas aeruginosa, and expanded the field of recombineering in Pseudomonas taiwanensisand Pseudomonas fluorescens. These findings will enhance the mutagenesis capabilities of these members of the Pseudomonas genus, increasing the possibilities for biotransformation and enhancing their potential for synthetic biology applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Scalable Parallel Measurement of Individual Nitrogen-Vacancy Centers

The nitrogen-vacancy (NV) center in diamond is a solid-state spin defect that has been widely adopted for quantum sensing and quantum information processing applications. Typically, experiments are performed either with a single isolated NV center or with an unresolved ensemble of many NV centers, resulting in a trade-off between measurement speed and spatial resolution or control over individual defects. In this work, we introduce an experimental platform that bypasses this trade-off by addressing multiple optically resolved NV centers in parallel. We perform charge- and spin-state manipulations selectively on multiple NV centers from within a larger set, and we manipulate and measure the electronic spin states of over 100 NV centers in parallel. We show that the high signal-to-noise ratio of the measurements enables the detection of shot-to-shot pairwise correlations between the spin states of 108 NV centers, corresponding to the simultaneous measurement of 5778 unique correlation coefficients. We discuss how our platform can be scaled to parallel experiments with thousands of individually resolved NV centers. These results enable parallelized high-throughput sensing experiments that retain the spatial resolution of single defects and will, thereby, help to unlock advances in applications such as single-molecule NMR and characterization of integrated circuits. In addition, our approach to multiplexing provides a natural platform for the application of recently developed correlated sensing techniques.

NV centers↗
DOE OSTI2023

Summary of Methodology for Mitigating Risks Associated with Licensing and Qualifying AM Nuclear Materials

The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program focuses on accelerating the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. Laser powder bed fusion (LPBF) is one of the most popular additive manufacturing (AM) processes for fabricating components with intrinsically complex geometries. LPBF was extensively explored for nuclear applications under the previous Transformational Challenge Reactor program. Additionally, Oak Ridge National Laboratory developed and licensed the Peregrine software and larger digital platform that couples machine learning and in situ data collection during AM to detect anomalies and any evolved defects. The digital platform will be critical to (1) the qualification of AM components for nuclear applications that link location-specific data to macroscopic properties and (2) predict final component performance. Current in situ process monitoring tools are valuable for observing the formation of stochastic flaws, but additional data are needed to predict the resulting microstructures and associated material performance. Rapid cooling rates and large thermal gradients have caused large heterogeneities in the microstructure, which cause anisotropy in mechanical performance. The AMMT program is evaluating the best approaches for addressing these heterogeneities and their effect on component performance using a combination of multiscale modeling, enhanced in situ process monitoring, and high throughput experimental testing. This report summarizes strategies for mitigating the risks associated with qualifying AM components, including developing new sensing capabilities for in situ process monitoring and characterizing melt pool solidification and residual stresses to inform multiscale modeling efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Laser Ablation-Capillary Absorption Spectroscopy: A novel approach for high throughput and increased spatial resolution measurements of δ 13 C in plant-soil systems

Spatial and temporal heterogeneity of nutrient exchange within the rhizosphere is a topic of increasing interest, although challenging to study due to limits in existing analytical capabilities. Here, we developed and demonstrated a new approach applying laser ablation sample introduction to capillary absorption spectroscopy (LA-CAS) to characterize carbon isotopic distribution within plant tissues, rhizosphere, and soil. We exposed switchgrass plants to 13 CO 2 to allow tracing of 13 C-labelled photosynthates within plant biomass and into the associated soil. The LA-CAS methods we describe leverage continuous measurements of a sample stream derived from laser ablation line scans (10-25 µm in width) over a sample surface which enables the user to produce an isotope map with a) higher data density or b) over larger spatial areas versus previously existing techniques. This versatility of LA-CAS is assessed through testing of a range of laser parameters (spot size, scan rates) on various materials (soil, plant biomass/tissues, and rhizosphere). Here, we demonstrate the ability of LA-CAS to provide near instantaneous $δ$ 13 C measurements over isotopically distinct surfaces to enable high spatially resolved mapping of 13 C-labelled material within the rhizosphere. Applying LA-CAS analysis to plant biomass, we observed higher $δ$ 13 C values concentrated within phloem structures, consistent with localized photosynthate transport. When mapping across the rhizosphere, 13 C-enriched soil was typically present within 5-10µm of root boundaries with a steep spatial increase in $δ$ 13 C when the scan approached the middle of the root. As with all LA approaches, care is required to ensure accurate results as phenomena linked to ablation, combustion, and isotopic measurement can impart artifacts if not carefully controlled. Still, taken as a whole, our demonstrations highlight the increased sample throughput, improved data density, and enhanced $δ$ 13 C capability of LA-CAS versus other LA techniques and emphasize the role this method can play in future plant and rhizosphere related studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Compositional screening of Ce-doped (Gd,Lu,Y) 3 (Al,Ga) 5 O 12 ceramics prepared by quenching from melt and their luminescence properties

Quenching from the melt using an Optical Floating Zone furnace was investigated as a possible high-throughput preparation method in order to screen novel scintillating materials. To validate this method, polycrystalline rare-earth aluminum garnets and yttrium gallium aluminum garnets were synthesized and characterized by X-ray diffraction, photoluminescence and radioluminescence emission spectra as well as radioluminescence imaging and compared to the previously reported properties of those materials. In order to achieve rapid, but quantitative comparison of the materials, pellets fabricated from the synthesized powders were sintered; two different sintering conditions were investigated and compared. Therefore, a simplistic energy deposition and light absorption model for brightness of opaque samples under X-ray irradiation was developed to estimate the relative scintillation efficiency of the materials. Based on the results, Y 3 Al 5 O 12 , LuY 2 Al 5 O 12 and GdY 2 Al 5 O 12 seem to have the highest scintillation efficiency among the prepared samples.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Fast-Pass, Desorption Electrospray Ionization Mass Spectrometry Strategy for Untargeted Metabolic Phenotyping

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) provides direct analytical readouts of small molecules that can be used to characterize the metabolic phenotypes of genetically engineered bacteria. In an effort to accelerate the time frame associated with the screening of mutant libraries, we have developed a high-throughput DESI-MSI analytical workflow implementing a single raster line-scan strategy that facilitates the collection of location-resolved molecular information from engineered strains on a subminute time scale. Evaluation of this “Fast-Pass” DESI-MSI phenotyping workflow on analytical standards demonstrated the capability of acquiring full metabolic profiling information with a throughput of ~40 s per sample. This Fast-Pass strategy was implemented in the analysis of genetically edited Escherichia coli strains that have been engineered to produce various free-fatty acids (FFAs) for applications relevant to biofuels. Due to the untargeted nature of DESI-MSI, the investigation of these strains yielded molecular information for both global metabolites and targeted detection of accumulated bioproducts, allowing simultaneous readouts of strain-specific chemical profiles and comparative measurements of FFA production levels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2016

Hall Thruster Thermal Modeling and Test Data Correlation

HERMeS - Hall Effect Rocket with Magnetic Shielding. Developed through a joint effort by NASA/GRC and the Jet Propulsion Laboratory (JPL). Design goals: High power (12.5 kW) high Isp (3000 sec), high efficiency (> 60%), high throughput (10,000 kg), reduced plasma erosion and increased life (5 yrs) to support Asteroid Redirect Robotic Mission (ARRM). Further details see "Performance, Facility Pressure Effects and Stability Characterization Tests of NASAs HERMeS Thruster" by H. Kamhawi and team. Hall Thrusters (HT) inherently operate at elevated temperatures approx. 600 C (or more). Due to electric magnetic (E x B) fields used to ionize and accelerate propellant gas particles (i.e., plasma). Cooling is largely limited to radiation in vacuum environment.Thus the hardware components must withstand large start-up delta-T's. HT's are constructed of multiple materials; assorted metals, non-metals and ceramics for their required electrical and magnetic properties. To mitigate thermal stresses HT design must accommodate the differential thermal growth from a wide range of material Coef. of Thermal Expansion (CTEs). Prohibiting the use of some bolted/torqued interfaces.Commonly use spring loaded interfaces, particularly at the metal-to-ceramic interfaces to allow for slippage.However most component interfaces must also effectively conduct heat to the external surfaces for dissipation by radiation.Thus contact pressure and area are important.

Model↗
DOE OSTI2023

The Materials Provenance Store

Abstract We present a database resulting from high throughput experimentation, primarily on metal oxide solid state materials. The central relational database, the Materials Provenance Store (MPS), manages the metadata and experimental provenance from acquisition of raw materials, through synthesis, to a broad range of materials characterization techniques. Given the primary research goal of materials discovery of solar fuels materials, many of the characterization experiments involve electrochemistry, along with optical, structural, and compositional characterizations. The MPS is populated with all information required for executing common data queries, which typically do not involve direct query of raw data. The result is a database file that can be distributed to users so that they can independently execute queries and subsequently download the data of interest. We propose this strategy as an approach to manage the highly heterogeneous and distributed data that arises from materials science experiments, as demonstrated by the management of over 30 million experiments run on over 12 million samples in the present MPS release.

36 MATERIALS SCIENCE↗