Yifei Mo

Biography

Education  Ph.D., University of Wisconsin-Madison, 2010 Research Interests  Computational materials design, large-scale atomistic modeling, coupling between surfaces/interfaces/nanostructures and materials properties, and materials for energy storage and  conversion. Current Research Projects  My research group aims to advance the understanding, design, and discovery of engineering materials through cutting-edge computational techniques. We target critical materials problems that impede high-impact technologies, such as energy storage, conversion, and efficiency. In our research, the computational modeling provides enhanced fundamental scientific insights, and enables the ability to rationally design new materials. Accelerated design and discovery of novel materials through computation Computational techniques based on first principles are capable of predicting materials properties with little or no experimental input. In our research, we leverage an array of computational techniques to design new materials with enhancement in multiple properties. With the aid of supercomputers, computational methods can significantly speed up the innovation and development of new materials. Our current efforts focus on solid-state batteries, solid oxide fuel cell, and various membrane materials. Education  Ph.D., University of Wisconsin-Madison, 2010 Research Interests  Computational materials design, large-scale atomistic modeling, coupling between surfaces/interfaces/nanostructures and materials properties, and materials for energy storage and  conversion. Current Research Projects  My research group aims to advance the understanding, design, and discovery of engineering materials through cutting-edge computational techniques. We target critical materials problems that impede high-impact technologies, such as energy storage, conversion, and efficiency. In our research, the computational modeling provides enhanced fundamental scientific insights, and enables the ability to rationally design new materials. Accelerated design and discovery of novel materials through computation Computational techniques based on first principles are capable of predicting materials properties with little or no experimental input. In our research, we leverage an array of computational techniques to design new materials with enhancement in multiple properties. With the aid of supercomputers, computational methods can significantly speed up the innovation and development of new materials. Our current efforts focus on solid-state batteries, solid oxide fuel cell, and various membrane materials.

Research Interest

Computational materials design, large-scale atomistic modeling, coupling between surfaces/interfaces/nanostructures and materials properties, and materials for energy storage and  conversion.