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Roy, Lindsay E.

Publications and source records attributed to Roy, Lindsay E..

Machine Learning Prediction of Fracture Toughness in Hydrogen-charged Stainless Steels

Austenitic stainless steels are structural materials utilized in tritium gas pressure boundaries since they are resistant to hydrogen isotope embrittlement [1-3]. However, exposure to tritium over long periods of time leads to tritium uptake which decays to result in helium ingrowth. This helium ingrowth results in further embrittlement effects which are synergistic with that from the hydrogen isotope [4]. Therefore, it is important for tritium facilities to understand the material limitations of stainless steel in this environment. The Savannah River National Laboratory (SRNL) has available a large experimental data set of austenitic stainless steels which have been exposed to tritium environments for various lengths of time. With the availability of this data set, machine learning (ML) algorithms provide an opportunity to model the embrittlement of stainless steel due to the algorithm’s ability to identify patterns in data sets that are difficult and costly to identify in other manners [5]. Ultimately, the amount and quality of the available data is one defining force in the ability of a ML model to accurately predict the desired outputs. The models developed herein will illustrate the ability for the various algorithms to predict the change in fracture toughness in stainless steels due to hydrogen-isotope embrittlement.

Hoar, Eric T.↗

The electronic Raman scattering spectrum of PuO 2

Here the Raman spectrum of PuO 2 was measured up to 13,000 cm –1 with three different laser excitation wavelengths spanning the resonance (405 nm), near-resonance (457 nm), and preresonance (514 nm) energy range. Approximately 26 never-before-seen bands were observed between 3500 and 13,000 cm –1 . Given the very high energy of the Raman shifts of these bands and the relative insensitivity of their spectral position to the interrogating laser wavelength, they are believed to arise from an electronic origin. These bands are present in both freshly calcined and radiolytically aged PuO 2 , although a broad luminescence is observed in the aged material, which obscures many of the high frequency features. In situ laser annealing of the material attenuated this luminescence and allowed for clear observation of these never-before-seen spectral features. Discovery of these high-energy bands presents a new way of identifying PuO 2 for nuclear nonproliferation and forensics purposes.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Impact of Precipitation Parameters on the Specific Surface Area of PuO 2

Controlling the properties of PuO 2 through processing is of vital importance to environmental transport and fate, production of nuclear fuels, nuclear forensic analyses, stockpile stewardship, and storage of nuclear wastes applications. A number of processing conditions have been identified to control final product properties, including specific surface area (SSA), residual carbon content, adsorption of volatile species, morphology, and particle size. In this paper, a novel approach is developed for the prediction of PuO 2 SSA via the synthetic route of Pu(IV) oxalate precipitation followed by calcination. The proposed model utilizes multivariate regression methodology and leave one out formalism to link Savannah River Site (SRS) precipitation and calcination production data to the SSA of the final product. A comparison among the models provides insight into the accuracy and ability to identify variations amongst the processing data. Additionally, the models may also be used to fit new data outside of the parameters explored in a production facility. Finally, the trained model was compared to a similarly trained conventional model form to illustrate the influence of precipitation parameters on the prediction of the final SSA. The models presented here attempt to provide new methods for more accurate prediction of the PuO 2 product properties in a production scale environment for key environmental and nuclear applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Solid State Ionics: Materials Development by Multiscale Modeling and Advanced Manufacturing Techniques

Solid-state ionic materials are an important enabling technology for energy conversion and storage. Solid-state batteries would be a safer and higher energy density alternative to commercially available lithium ion batteries (LIB), however their implementation requires ion conduction in solids at room temperature to occur on the same level as the current generation of liquid electrolytes. Microstructural modifications have been demonstrated to play a major role on ion transport through the control of grain boundary interfaces, which traditionally serve as “blocking” layers. Ultimately, these materials will be fabricated in thin films form as electrolytes in order to minimize ohmic losses in electrochemical devices. This work uses advanced manufacturing techniques in combination with theoretical modeling to implement a science-based approach in the deposition of thin films ion conductors with controlled microstructures used in ceramic energy conversion and storage devices.

25 ENERGY STORAGE↗