Designing exceptional gas-separation polymer membranes using machine learning

Plasticization of gas separation membranes*

For the investigation of the plasticizing effect of carbon dioxide on polymers used for gas separation membranes new experimental methods have been developed that measure the sorption kinetics as well as the dilation kinetics. Comparing dilation and sorption kinetics at low and elevated pressures gives information about different types of swelling behaviour depending on the pressure level. Volu...

Polymeric Gas Separation Membranes: What Makes them Industrially more Attractive?

Designing social choice mechanisms using machine learning

Social choice studies ordinal preference and information aggregation with applications in high-stakes political elections as well as low-stakes movie rating websites. Recently, computational aspects of classical social choice mechanisms have been extensively investigated, yet not much has been done in designing new mechanisms with the help of computational techniques. In this paper, we outline ...

Modeling of Chloride Ion Separation by Nanofiltration Using Machine Learning Techniques

In this work, several machine learning techniques are presented for nanofiltration modeling. According to the results, specific errors are defined. The rejection due to Nanofiltration increases with pressure but decreases with increasing the concentration of chloride ion. Methods of machine learning represent the rejection of nanofiltration as a function of concentration, pH, pressure and also ...

Novel inorganic membranes for gas separation

A literature survey was performed to evaluate the state-of-the-art membrane systems for CO2/CH4 separation which is critical in the natural gas industry. The systems that were reviewed included zeolite, carbon, polymeric, mixed matrix, amorphous silica, and supported ionic liquid membranes. Supported ionic liquid CO2/CH4 selective membranes were synthesized in our laboratory by applying room te...