Separation of organic vapors and gases with tailored membranes

Metal/covalent organic frameworks, as well as functionalized nanostructure materials with ionic liquids, are advancing the separation capabilities of polymer membranes for gas and organic vapor separations. Such functionalization of membranes also suppresses negative phenomena, such as plasticization and aging, which limit the use of a new generation of polymeric materials with excellent separation properties. This work aims to investigate the effect of the type and amount of functionalization on the transport-separation parameters and the structure of membranes. The study of the transport and separation properties will be carried out using automated systems to measure the permeation of gas and organic vapor mixtures. Also, the possibilities of predicting transport parameters using physical models and machine learning methods will be explored.

Required education and skills:

• Master’s degree in Chemical Engineering, Physical Chemistry, or any relevant field;
• interest in science, willingness for experimental work, and to learn new things; teamwork ability.

Sholl D., Lively R. Seven chemical separations to change the world. Nature 532, 435 (2016)

Yang J., et al. Machine learning enables interpretable discovery of innovative polymers for gas separation membranes. Sci. Adv. 8, eabn9545 (2022).

Co-supervisors: doc. Ing. Pavel Izák Ph.D. DSc., Ing. Zuzana Petrusová Ph.D.