Executive Summary : | The development of 'click' hydrogels, which are high selectivity, product homogeneity, and bio-orthogonality, is hindered by a lack of understanding of structural information and dominant atomistic interactions. Molecular dynamics (MD) simulation is a viable approach to reveal time-resolved atomic trajectories and statistical analysis of the system's structural, thermal, mechanical, and transport properties. However, building a chemically crosslinked 'click' hydrogel macromolecule is a challenge, and stationary phases due to structural complexity lead to inaccurate sampling and poor trajectories. umbrella sampling is an effective way to sample rare events in MD simulation. The proposal aims to provide an effective solution to these knowledge gaps in the 'click' hydrogel field by developing an open-source macromolecule building toolkit that allows users to build crosslinked functionalized polymers with desired chain length and degree of crosslinking. Artificial Intelligence (AI) algorithms will be integrated with MD simulation for enhanced sampling and statistics. The database will encode the structural, mechanical, thermal, and transport properties of 'click' hydrogels in varying environments of pH, temperature, and pressure, generating an enormous volume of data for discovering unexplored hydrogels. Non-traditional global optimization programs, such as 'chimp optimization algorithm' and 'grey wolf optimization', will be integrated with the AI framework to create a robust predictive framework that reveals the complex relationship between structural properties and physico-chemical properties. This will enable in silico design of unexplored 'click' hydrogels with a novel functionalized monomer and cross-linker, leading to the foundation of accelerated discovery of smart hydrogels. |