Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

This Small Business Technology Transfer (STTR) program aims at development and demonstration of an integrated theoretically/experimentally combinatorial method for the accurate prediction of rheological behaviors of special polymer solutions. In-depth understandings of dynamic responses of the polymer solutions under external shear are essential for development of the “smart” polymer-based additive (SPA) flooding as advanced enhanced oil recovery (EOR) processes. However, conventional coarse-graining molecular dynamic simulations are not useful for Polymer Discovery because the materials are generally amorphous involving polymer chains of thousands to millions of atoms, usually composed of several monomers and generally cross-linked. Scientists from SGTC and Caltech will team up together to apply advanced multi-scale multi-paradigm simulation methods recently developed by the Caltech’s group to develop the robust molecular predictive methods and demonstrate the applicability for SPA-EOR applications. In particular, throughout this program, we will develop accurate molecular modeling methods to improve our fundamental understandings and the molecular in-silico screening to obtain best performance polymers. We proposed a strongly integrated theoretical/experimental project to develop and demonstrate scientific feasibility of the efficient yet accurate molecular predictive method to simulate high-molecular weight, water-soluble functionalized polymeric solution. Our theoretical programs include applications of state-of-the-art multi-scale, multi-paradigm molecular dynamic simulation methods that retains the accuracy of Quantum Mechanism methods for reactive systems, yet at the scale of millions of atoms and over time scale of milliseconds and longer. Our experimental programs include laboratorial synthesis, rheological property characterization, and unique multi-core flooding tests of the special polymer candidates. Special polymeric materials have extensive applications in building, coating, plastics, membranes, aerospace, automotive, electronics, packaging and medical devices, etc. Although this proposed project has been focused mainly on energy production applications, the success of our proposed robust molecular predictive methods for high throughput screening and molecular designs, could have much broad impacts in the Materials Discovery.