(192al) Computational Discovery of New Materials and Processes for Industrial Separations
- Conference: AIChE Annual Meeting
- Year: 2017
- Proceeding: 2017 Annual Meeting
- Group: Computational Molecular Science and Engineering Forum
Monday, October 30, 2017 - 3:15pm-4:45pm
We use Monte Carlo (MC) simulations for predicting phase and adsorption equilibria. Accurate force fields are at the heart of any reliable computational prediction. These molecular models comprise of several parameters, that may be system-specific for matching to experimental data. However, this work takes a different approach, in that, a large amount of effort is first invested in a multi-dimensional, parallel, and physically guided parameter optimization for capturing a wide range of properties for the molecules of interest. The expense involved in parametrizing transferable force fields is recouped by allowing the use of these models for diverse systems, without the need for reoptimization each time a new system is investigated. This also provides truly predictive and reliable answers to problems where experimental data may not be available.
MC simulations are used to probe adsorption in zeolites â nanoporous materials with highly specific pore sizes and shapes. Using tailored simulation protocols, a large database of zeolite structures is screened for adsorption performance and promising structures for efficient separations are discovered. Some of these zeolite frameworks are currently synthesized and assessed experimentally to validate the predictions. The new separation technologies that we are developing have the potential for far-reaching impacts on the global energy and chemical industries.