My postdoctoral research focuses on studying the performance of tritium barrier coatings (TBC) used in fusion reactors using Xolotl, an open source, spatially dependent cluster dynamics simulation code.
With a background in nuclear and electrical engineering, I earned my doctorate from École Centrale de Lille, France in computational material science. During my Ph.D., I investigated radiation induced damage mechanisms in reactor structural materials using molecular dynamics and computational modeling. This work included developing automated simulation workflows and data driven models to characterize the effects of empirical potentials and alloy composition on material behavior under irradiation.
As postdoctoral research at the Institute of Research for Ceramics (IRCER) in Limoges, France, I applied machine learning techniques, including convolutional neural network models built with TensorFlow, to predict strain profiles from X-ray diffraction (XRD) experimental data.
My broader research goal is to develop a materials informatics driven approach, combining neural networks, statistical learning, and data driven modeling, to enable predictive understanding of materials performance in radiation environments.
Email: aachutha@utk.edu