PhD student
My research focuses on enhancing the calibration of Crystal Plasticity Finite Element (CPFE) models, which are powerful tools for simulating the grain-level mechanical behavior of polycrystalline materials. Given the complexity and computational cost of calibrating CPFE parameters, I’m using Deep Reinforcement Learning (specifically, the Deep Deterministic Policy Gradient algorithm) to optimize this process. I've developed a Python-based environment to automate calibration and compared it with traditional methods like Particle Swarm Optimization, showing improved accuracy. My work demonstrates the potential of AI-driven optimization in complex material modeling scenarios, such as simulating the cyclic behavior of stainless steel under different conditions.
Email: fe22312@bristol.ac.uk

PhD student
My research interest lies in understanding deformation behavior across different material systems. My work focuses on computational materials science, utilizing molecular dynamics simulations and high-performance computing to study mechanical responses at the atomic scale. I have experience in experimental techniques such as SEM, EBSD, and digital image correlation, complementing my computational insights. My research spans gradient nanoglass structures, additively manufactured alloys, and phase transformations under thermomechanical processing. Through my studies, I aim to bridge experimental and computational approaches to advance the design and performance of next-generation materials.
Email: prashiljoshi@iisc.ac.in

Masters student
My research focuses on enhancing our CPFE simulation toolbox for FeCr alloys that have been irradiated with Fe ions under a controlled thermal gradient. By integrating experimental data from Laue diffraction, nanoindentation, and AFM, I aim to refine the CPFE model by incorporating temperature as a critical parameter in irradiation damage evolution. This work will bridge the gap between experimental limitations and engineering-scale predictions, ultimately improving the model’s adaptability and its ability to forecast material behavior for reactor component design.
Email: sandeshdhage@iisc.ac.in

PhD student
My research focuses on understanding how Fe-Cr alloys perform under irradiation damage at different temperatures. I'm exploring these materials to find the best alloy composition that could be used as a Plasma-Facing Component (PFC) in fusion reactors. To do this, I'm using cutting-edge techniques like ion-implantation, synchrotron Laue diffraction, Atomic Force Microscopy (AFM), and nanoindentation. My goal is to uncover how these materials behave under extreme fusion conditions and help design alloys that are ready for the future of energy!
Email: chandrabhusan.yadav@bristol.ac.uk

Masters Student
My research focuses on understanding how strain rate affects the deformation behavior of irradiated tungsten, a material crucial for high-performance applications. To explore this, I’ve combined nanoindentation, Atomic Force Microscopy (AFM), and crystal plasticity modeling to capture the nuances of how tungsten behaves under different conditions. This project opens the door to deeper insights into how we can tailor the mechanical properties of tungsten for demanding environments, with the ultimate goal of improving its performance in applications like fusion reactors."

Masters Student
My research is focused on enhancing the CPFE model for irradiated tungsten. I aim to capture how strain rate varies with slip systems, indentation size, and the source of irradiation. By refining these models, I hope to deepen our understanding of tungsten’s deformation behavior, ultimately paving the way for improved performance in high-demand applications like fusion reactor.
Email: layatmikas@iisc.ac.in

UKAEA

Henry Royce Institute