(166d) Computational Design of New Classes of Chemoresponsive Liquid Crystalline Systems | AIChE

(166d) Computational Design of New Classes of Chemoresponsive Liquid Crystalline Systems

Authors 

Szilvási, T. - Presenter, University of Wisconsin-Madison
Bao, N., University of Wisconsin-Madison
Nayani, K., University of Wisconsin-Madison
Yu, H., University of Wisconsin-Madison
Abbott, N. L., University of Wisconsin-Madison
Mavrikakis, M., University of Wisconsin - Madison
The interactions of nematic liquid crystals at interfaces can impact the overall orientation in the bulk phase. This surface-induced orientational behavior can be exploited to detect chemical analytes via competitive binding of the liquid crystal molecules and chemical analyte to a tailored surface.1-3 Very recently, we developed computational models,4,5 based on quantum mechanics, to capture the effects of important experimental parameters that influence orientational transitions exhibited by surface-anchored nematic liquid crystals. Our models have already helped to optimize the selectivity6 and sensitivity7 of existing chemoresponsive liquid crystalline systems. The models have also formed a central part of an integrated high throughput-like materials discovery approach that exploits the synergistic effects of fast theoretical prediction, synthesis of new liquid crystals, and their experimental evaluation.

In this presentation, we will show how experimentally validated computational models can lead to completely new interfacial designs of liquid crystalline systems that permit detection of analytes that bind very weakly to surfaces. We will demonstrate that our new approach based on computational chemistry-driven optimization of the chemoresponsive systems can selectively detect analytes in the parts-per-billion concentration range.

  1. Shah, R. R.; Abbott, N. L., Science 2001, 293, 1296.
  2. Hunter, J. T.; Abbott, N. L., Applied Materials and Interfaces, 2013, 6, 2362
  3. Yang, K. L.; Cadwell, K.; Abbott, N. L., Journal of Physical Chemistry B, 2004, 108, 20180.
  4. Roling L. T.; Scaranto, J.; Herron, J. A.; Yu, H.; Choi, S.; Abbott, N. L.; Mavrikakis, M., Nature Communication, 2016, 7, 13338.
  5. Szilvási, T.; Roling, L. T.; Yu, H.; Rai, P.; Choi, S.; Twieg, R. J.; Mavrikakis, M.; Abbott, N. L., Chemistry of Materials, 2017, 29, 3563.
  6. Yu, H.; Szilvási, T.; Rai, P.; Choi, S.; Twieg, R. J.; Mavrikakis, M.; Abbott, N. L., Advanced Functional Materials, 2018, 28, 1703581.
  7. Szilvási, T.; Bao, N.; Yu, H.; Twieg, R. J.; Mavrikakis, M.; Abbott, N. L., Soft Matter, 2018, 14, 797.