Projects
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Solid state Li-ion conductors and all solid state battery materials․
The project aims to use computational methods, including data mining, machine learning, and evolutionary algorithms, to accelerate the search for novel solid state electrolytes for future energy storage systems, addressing current limitations in ion conductivity and material compatibility.
Design of organic solid-state materials for battery applications.
The project aims to address global environmental challenges by developing sustainable and clean battery technologies, focusing on organic electrode materials for their cost-effectiveness and recyclability, in combination with solid-state electrolytes to enhance battery performance and sustainability.
Post Li-ion (Na, K, Ca, Zn and so on) battery materials design and discovery.
The focus is on developing high-energy-density, climate-neutral solid-state batteries and alternative ion batteries (e.g., Sodium-ion) for sustainable energy storage, overcoming challenges in electrolyte and electrode material discovery through advanced computational methods like machine learning and evolutionary algorithms for material prediction.
Computational Investigation of 2D Materials for Catalytic Activity.
The research is focused on computationally discovering new 2D materials with unique properties for catalysis and other applications, utilizing the USPEX tool to predict materials that could lead to significant advancements in technology.
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Computational Search for Super-hard materials.
The research aims to identify new superhard materials, focusing on carbides, borides, and nitrides, to expand the range of compounds with exceptional hardness for use in industrial applications.