(197h) A Study on Supercomputing Utilization and Molecular Structure Exploration Algorithm for Accelerating Material Inverse Design

Inverse design is a concept in which a desired set of properties is defined first, and then a material or molecule with those specific properties is designed through a systematic process. For the past 30 years, researchers have been actively studying Computer-Aided Molecular Design (CAMD) technology in the fields of bio-chemical materials and new drug development. Recently, with the application of big data and artificial intelligence technologies, the effectiveness of this technology has been realized. The primary goal of molecular design is to create new materials with improved physical properties compared to existing ones. To achieve this, an optimization process is used to propose a set of molecular structures for new materials or groups of similar materials that are expected to exhibit excellent physical properties. This process significantly reduces the number of materials that need to be synthesized or the range of physical properties that need to be measured through experiments. To maximize the efficiency of the optimization process based on supercomputing, algorithms that allow parallel searching are applied. Molecular dynamics and density functional theory are widely used to predict various properties of a substance based on its molecular structure through calculations, provided that the molecular structure is known through computation. To perform such calculations, a combination of databases and theoretical formulas are utilized. This study covers the basic composition for developing such software, as well as an example of a simple molecular design to test and develop the prototype program through a case study on the design of CO2 absorbent materials.