A Simple Approach of Mass Transport On Gas-Liquid Interface by Statistical Rate Theory

Tuesday, October 18, 2011: 2:36 PM
102 C (Minneapolis Convention Center)
Xiaohua Lu, Rong An, Hanbing He, Yuanhui Ji, Yudan Zhu, Suoying Zhang and Gulou Shen, State Key Laboratory of Materials-oriented Chemical Engineering, Nanjing University of Technology, Nanjing, China

In many multi-phase chemical processes, mass transport at the interface is the rate-determining step, and the corresponding transport behavior can affect the system performance directly. Thus the effects of the interface on the material performance or the process have to be taken into account. The description for the transport behavior at solid-liquid interface has successfully provided theoretical guidance for chemical process. However, for the description of the mass transport at the gas(vapor)-Liquid interface, it is difficult to calculate the interfacial area accurately, which is a key factor for building accurate transport rate model. The interfacial area at gas(vapor)-liquid interface can be generally assumed as liquid cross-sectional area, which is different from the actual interfacial area. Therefore, it is necessary to introduce a nanobubble theory to predict the interfacial area at vapour-liquid interface.

With Statistical Rate Theory (SRT), the mass transport at gas(vapor)-liquid interface can be simplified as that of the two processes linking in gas(vapor)-phase, which is, mass transport from liquid into gas(vapor) phase and then that from gas(vapor)-liquid interface into bulk phase. It is necessary to utilize the nanobubble theory for predicting the interfacial transport area, as a key factor for mass transport at gas(vapor)-liquid interface. Afterwards, with the nanobubble theory and mass conservation, the transport area at the gas(vapor)-liquid interface can be determined by considering nanobubble diameter related to interfacial tension which is one of the main factors to control the transport rate. The nanobubble size distribution function can be also determined with the theory to further predict the transport rate with experimental kinetic data. Using the chemical potential gradient Δμ as driving force and then with parametric regression, the transport behavior at interface could be analyzed to determine the rate-controlling factor.

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See more of this Session: Fundamental Research In Transport Processes II
See more of this Group/Topical: Engineering Sciences and Fundamentals