Dr. Mihir Khadilkar

– Developed a novel optimization method for targeted inverse design of block-copolymer morphologies for industrial applications that worked up to 10 times faster than existing methods. – Proposed method involved combining computer simulations with data-driven global optimization in parameter space to reduce experimental effort. – Worked in a team of academic and industrial researchers, communicating progress in monthly meetings and planning long-term research outline with quarterly reports.

– Explored structure and ordering of polyhedral nanoparticles (generally used in chemical, biotechnolgy, and electronics industries) using molecular modeling (Monte Carlo simulations). – Discovered previously unknown guiding rules on nanoparticle mixture self-assembly in 2-D and 3-D, for novel material discovery applications. – Used computational and data analysis tools to understand colloidal self-assembly.

Statistical Thermodynamics