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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments

In-situ (scanning) transmission electron microscopy (S/TEM) is being developed for numerous applications in the study of nucleation and growth under electrochemical driving forces. For this type of experiment, one of the key parameters is to identify when nucleation initiates. Typically the process of identifying the moment that crystals begin to form is a manual process requiring the user to perform an observation and respond accordingly (adjust focus, magnification, translate the stage etc.). However, as the speed of the cameras being used to perform these observations increases, the ability of a user to “catch” the important initial stage of nucleation decreases (there is more information that is available in the first few milliseconds of the process). Here we show that video shot boundary detection (SBD) can automatically detect frames where a change in the image occurs. We show that this method can be applied to quickly and accurately identify points of change during crystal growth. This technique allows for automated segmentation of a digital stream for further analysis and the assignment of arbitrary time stamps for the initiation of processes that are independent of the user’s ability to observe and react.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Redefining the Practice of Peer Review Through Intelligent Automation—Part 3: Automated Report Analysis and Data Reconciliation

One method for addressing existing peer review limitations is the assignment of peer review cases on a completely blinded basis, in which the peer reviewer would create an independent report which can then be cross-referenced with the primary reader report of record. By leveraging existing computerized data mining techniques, one could in theory automate and objectify the process of report data extraction, classification, and analysis, while reducing time and resource requirements intrinsic to manual peer review report analysis. Once inter-report analysis has been performed, resulting inter-report discrepancies can be presented to the radiologist of record for review, along with the option to directly communicate with the peer reviewer through an electronic data reconciliation tool aimed at collaboratively resolving inter-report discrepancies and improving report accuracy. All associated report and reconciled data could in turn be recorded in a referenceable peer review database, which provides opportunity for context and user-specific education and decision support.

42 ENGINEERING↗
DOE OSTI2018

Hydroxamate column-based purification of zirconium-89 (89Zr) using an automated fluidic platform

Zirconium-89 (89Zr) is a long-lived (t1/2 = 78.4 h) positron-emitting isotope that is useful for positron emission tomography (PET) based diagnostic imaging using radiolabeled antibodies. Hydroxamate resin columns are predominantly used for the purification of 89Zr from cyclotron bombarded natY targets dissolved in strong HCl. 89Zr is conventionally eluted from the resin in 1 M oxalic acid (H2C2O4), a complexant that is conducive to follow-on binding of 89Zr through a transchelation process to the deferoxamine siderophore. In the present study, we determined that a lower concentration of H2C2O4 eluent (0.8 M) is adequate to efficiently remove 89Zr from a column containing 100 mg hydroxamate resin. As a result, less buffering agents are needed to be added to the 89Zr product fraction prior to labeling. A simple automated fluidic system prototype has been developed to perform the steps required for 89Zr purification using a hydroxamate resin column (column conditioning in HCl, Y target dissolution, dissolved target solution load onto column, column washes using HCl and water, and 89Zr elution). The system performance was evaluated using several cyclotron bombarded Y targets; 89Zr product fractions demonstrated excellent chemical recoveries from these targets, with 1.0 mL product volumes yielding 89±2% of the column elution peak activity and 84±2% of 89Zr recovered from the target (at EOB). These results compare favorably with previously published 89Zr product volumes and yields, despite the lower concentration of H2C2O4 eluent employed. Transchelation of resulting 89Zr product fractions was performed to assess product quality. The effective specific activity (ESA) ranged between 44(7) and 109(22) TBq·mmole-1, while the bindable metals concentration, a metric introduced for assessing and comparing product purity, ranged between 43(7) and 115(27) nmole·g-1.

zirconium-89, 89Zr, ImmunoPET, medical isotope, au↗
DOE OSTI2018

Automated Algorithms for Band Gap Analysis from Optical Absorption Spectra

As high-throughput combinatorial experimental methods become more common, the technical challenge is shifting from producing materials to dealing with increasingly large datasets. One of the most important metrics to determine suitability of semiconductor materials for various applications is the band gap. This paper discusses automated algorithms for determining band gaps from optical absorption spectra. The algorithms are applied to a database of 34,313 optical absorption spectra, and selected results are compared to published theoretical and experimental band gap data from 16 materials sets. The best algorithm determines the band gaps with an accuracy of 0.37 eV for direct- and 0.93 eV for indirect band gaps for >20,000 spectra.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Predicting Reaction Products and Automating Reactive Trajectory Characterization in Molecular Simulations with Support Vector Machines

A machine learning-based methodology for the prediction of chemical reaction products, along with automated elucidation of mechanistic details via phase space analysis of reactive trajectories, is introduced using low-dimensional heuristic models and then applied to ab initio computer simulations of the photodissociation of acetaldehyde, an important chemical system in atmospheric chemistry. Our method is centered around training Support Vector Machines (SVMs) to identify optimal separatrices that delineate the regions of phase space that lead to different chemical reaction products. In contrast to the more common “black box” type machine learning methodologies for analyzing chemical simulation data, this SVM-based methodology allows for mechanistic insight to be gleaned from further analysis of the positioning of the phase space points used to train the SVM with respect to the separatrices. For example, a pair of phase space points that are in close proximity to each other but on opposite sides of a separatrix may be situated on opposite sides of a transition state, while phase space points occurring early in a simulation that are distant from a separatrix are likely to belong to trajectories that are highly biased toward the product state associated with the basin of attraction to which they belong. In addition to inferring mechanistic details about multiple-pathway chemical reactions, our method can also be used to increase reactive trajectory sampling efficiency in molecular simulations via rejection sampling, with trajectories leading to undesired product states being identified and terminated early in the simulation rather than being carried to completion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

1366 Project Automate: Enabling Automation for <$0.10/W High-Efficiency Kerfless Wafers Manufactured in the US

For photovoltaic (PV) manufacturing to thrive in the U.S., there must be an innovative core to the technology. Project Automate builds on 1366’s proprietary Direct Wafer® kerfless wafer technology and aims to unlock the cost and efficiency advantages of thin kerfless wafers. Direct Wafer is an innovative, U.S.-friendly (efficient, low-labor content) manufacturing process that addresses the main cost barrier limiting silicon PV cost-reductions – the 35-year-old grand challenge of manufacturing quality wafers (40% of the cost of modules) without the cost and waste of sawing. This simple, scalable process will allow 1366 to manufacture “drop-in” replacement wafers for the $10 billion silicon PV wafer market at 50% of the cost, 60% of the capital, and 30% of the electricity of conventional casting and sawing manufacturing processes. This SolarMat project developed the Direct Wafer processes’ unique capability to tailor the shape of wafers to simultaneously make thinner AND stronger wafers (with lower silicon usage) that enable high-efficiency cell architectures. By producing wafers with a unique target geometry including a thick border (which determines handling characteristics) and thin interior regions (which control light capture and electron transport and therefore determine efficiency), 1366 can simultaneously improve quality and lower cost (using less silicon).

14 SOLAR ENERGY↗