Structural stability and electrochemical response of 3D printed and reactively sintered Ga-doped Li7La3Zr2O12 electrolytes
Not Available
Dandeneau, Christopher S.↗
Engineering topics
Garcia-Diaz, Brenda L.
Publications and source records attributed to Garcia-Diaz, Brenda L..
Deep Eutectic Solvents as Candidates for Lithium Isotope Enrichment
Nuclear fusion is a phenomenon that is well known within the nuclear physics community as a viable option for alternative energy as many natural gases and fossil fuels are phased out of commercial use. Deuterium and tritium fusion reactions are currently the leading candidates for nuclear fusion, with a major limiting factor being a means to produce tritium on an industrial scale. Lithium-6 is a well-known isotope that can produce tritium and helium following a fission reaction with a neutron. Unfortunately, the lithium-6 enrichment methods are limited to the COLEX process, which leaves behind an alarming amount of mercury waste as a potential environmental contaminant. Deep eutectic solvents are believed to be a potential alternative to lithium isotope separations due to the ease of generation, in addition to the minimum environmental waste generated when these solvents are employed. Previous studies have suggested that deep eutectic solvents are capable of separating lithium isotopes by utilizing a 2-thenoyltrifluoroacetone and trioctylphosphine oxide system that can biphasically react with a buffered solution containing lithium chloride. This system displays a separation factor of 1.068, which when compared to the 1.054 separation within the COLEX process, makes it a potential candidate for lithium-6/7 separation. Within this study, we investigate this system in comparison to two newly synthesized deep eutectic solvents and find that within these acetylacetone-based systems, little isotopic separation is observed. We investigate these systems both experimentally and computationally, showing the different lithium cation affinities, in addition to proposing how the electron-donating or -withdrawing nature can influence these systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Full loop thermodynamic corrosion inhibition and sensing in molten chloride systems. Final report
The objective of this project is to increase the lifetime of Concentrated Solar Power (CSP) systems by identifying corrosion mitigation methods for heat transfer loops in the temperature range of 500 - 800 °C. Coupling of experimental data with CFD modeling has provided greater insight into corrosion mitigation methods and how they will be applied in molten salt systems with convective flows. The overall goal of the program is to demonstrate techniques that control corrosion while having limited impact on system alloys.
14 SOLAR ENERGY↗
Process Image Analysis using Big Data, Machine Learning, and Computer Vision
The development of algorithms for machine learning and data analysis for the 3013 MIS corrosion surveillance program is a collaborative effort by SRNL, USC and GT. For corrosion detection, LCM image data is extracted from large binary files, with software written to convert the data to physical attributes (i.e. height, color and grayscale values; all as functions of a location in a plane projection). The user interface for the software permits selective downloading of binary data and interrogation of attributes. User input thresholds are used to flag attributes of interest. Machine learning algorithms, developed for this application, are used to determine whether the features are the result of corrosion. To address the fundamental mechanisms of corrosion, machine learning algorithms are being developed to derive interatomic potential force-fields from ab-initio DFT calculations. The goal is to apply molecular modeling on a large enough scale to guide the design of resistant materials.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking (FY2020 Progress Report)
The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g. height, color and grayscale values; all as functions of a location in a plane projection). It is the objective of this project to produce a user-friendly interface that incorporated all operations needed to perform surface examination. For this reason, a Matlab-based Graphical User Interface (GUI) was created to integrate data input with software developed for processing and evaluation. In summary, the GUI permits selective downloading of binary data, interrogation of attributes, data labeling, flagging of significant features, execution of Machine Learning (ML) algorithms, output of parameters for trained ML algorithms, reports of ML model accuracy with respect to labeled data, and generation of graphical representations of various analyses.
3013 corrosion↗
MAX phase materials and MXenes as hydrogen barrier coatings
Hydrogen and its isotopes play an important role in nuclear applications, but their permeation and radioactivity lead to degradation of materials. Therefore, hydrogen isotope permeation barriers are an important supporting technology. Unfortunately, most permeation barriers that perform well in the laboratory fail when placed in radiation environments. The goal of this work is to begin the development of next generation permeation barriers with materials known to have good stability under neutron irradiation, and then tailor their composition and structure to maximize their barrier properties. In particular MAX phase materials and their two-dimensional analogues (MXenes) have been chosen due their excellent stability under neutron irradiation.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗