Stochastic Modeling of Separation Mechanism in Confined Membrane

In many industries, chemical separation is the most expensive part of the manufacturing process. A new method of separation using nanometere channels inspired by biological systems promises a greater efficiency in comparison with common separation methods. However, the cell membranes mechanism is super complicated and in order to mimic biological cells in real world to separate chemical mixtures, we need to understand how they behave and operate. Understanding the mechanism of them when very efficient, fast, and robust separations helps scientist to build industrial separation systems that behave the same. In this work, applying interdisciplinary knowledge to a common technique of process transport resulted in the creation of a novel model that increases selectivity. The utilization of this scalable model can lead to improved development of future separation technology based on nanochannels. More specifically, this work proposes a theory, and pioneers a model to discover the reason that super efficient separation happens in biological membranes to be translated into industrial separation systems using nanochannels. We used stochastic models that take into account all relevant transport probabilities in binary mixture separation. The effects of the symmetry and the strength of the molecular-pore interactions are examined. The most efficient separation is predicted when the interaction site is located near the entrance to the nanopore. The origin of the results is discussed as well.