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The Computation-Guided Energy Materials Discovery (C-GEM) research group, led by Poulumi Dey, focuses on the computation-guided design of materials for sustainable renewable energy applications. The group aims to pave the way for a sustainable future by designing materials for sustainable energy applications through a multi-scale simulation approach combined with machine learning. The research encompasses three main areas: (i) facilitating efficient large-scale hydrogen storage and production through the identification and optimization of materials, (ii) accelerating the deployment of safe, flexible, and efficient hydrogen grids by repurposing existing gas networks and identifying new pipeline materials that are immune to hydrogen embrittlement, and (iii) tailoring the properties of materials such as high entropy alloys for energy-related applications, including improvements in energy conversion efficiency for thermoelectric applications and the optimization of catalysts for fuel cell applications.
Requirements apply generally across engineering and science master programs. Specific tracks like Architecture require a digital portfolio.