(640b) Computer-Aided Molecular Design for Chemical and Energy Applications

The energy efficiency and technical difficulties of an industrial chemical process are often determined by the physicochemical properties of materials.¹ It is desirable to design the right structure of chemicals to meet the targeted material properties, such as the adsorption or emission spectrum of light. However, the research and development (R&D) of functional chemicals has been based largely on researcher’s experiences and experimental trial-and-error. With the advances in computing power and algorithm, Computer-Aided Molecular Design (CAMD)^{2, 3} technique can now serve as an auxiliary methodology to improve the efficiency of R&D. There are two elements in CAMD: First is the methodology for the prediction of molecular properties, including thermodynamic models, quantum mechanical calculation (QM), and molecular simulation etc.; The second part of CAMD is the optimization algorithm that could automatically search molecules with given requirements of molecular properties, including genetic algorithm (GA), simulated annealing algorithm (SA) etc.⁴ We have developed a new molecular data structure (MDS)⁵ that allows for flexible creation of new chemical structures with GA. In this presentation, we will demonstrate the application of the MDS in three different applications: (1) Finding new organic solvents of specified value of octanol-water partition function (K_ow).^{2, 3} (2) Finding new organic solvents of specified value of LUMO-HOMO the LUMO-HOMO gap. (3) Finding new ionic liquids (ILs) for CO2 capture.⁶ We show that CAMD could provide new chemicals that have better or comparable performance with well-known/commercialized specialty chemicals.

References

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4. Austin, N. D. Tools for Computer-Aided Molecular and Mixture Design. Dissertation, Carnegie Mellon University, 2017.
5. Hsu, H.-H.; Huang, C.-H.; Lin, S.-T., New Data Structure for Computational Molecular Design with Atomic or Fragment Resolution. Journal of Chemical Information and Modeling 2019, 59, (9), 3703-3713.
6. Wang, J.; Song, Z.; Cheng, H.; Chen, L.; Deng, L.; Qi, Z., Computer-Aided Design of Ionic Liquids as Absorbent for Gas Separation Exemplified by CO2 Capture Cases. ACS Sustain. Chem. Eng. 2018, 6, (9), 12025-12035.