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Computational Modeling of two Dimensional Heterostructures for Optoelectronic and Catalytic Applications
Two-dimensional van der Waals (2D-vdW) materials have attracted significant attention for their unique and excellent properties. The properties of the 2D-vdW materials can be precisely engineered using various techniques ...
Accelerated Search of Catalysts Using Density Functional Theory and Machine Learning
The need for clean and renewable energy resources has propelled the interest in designing new catalysts producing energy from renewable resources and alternate cleaner fuels such as hydrogen, methane, ammonia, ethylene, ...
Electron Microscopy Investigations on Solution Grown Stannous Oxide Nanosheets
In this thesis, motivated by the possibility of studying rich scientific phenomena using morphology controlled single crystals, experimental observation of new features in the growth and structure of layered oxide materials ...
Machine learning and density functional theory assisted insights into the mechanical and oxidation properties of nickel-based superalloys
Due to global warming and increasing fuel costs, there is a constant thrust toward increasing fuel efficiency and reducing the emissions of gas-turbine engines, which are made out of superalloys. New superalloy materials, ...
Insights into Structure-Property Relationships via First Principles and Machine Learning Approaches
The increasing concerns about a sustainable future demand accelerated design and development of new materials with enhanced properties. The process of material development immensely depends on the structure-to-property ...