(222e) Cold Plasma Enhanced Dry Methane Reforming Reactor and Process Design to Maximize the Overall Process Sustainability | AIChE

(222e) Cold Plasma Enhanced Dry Methane Reforming Reactor and Process Design to Maximize the Overall Process Sustainability

Authors 

Rangarajan, S. - Presenter, Lehigh University - Dept of Chem & Biomolecular
Baltrusaitis, J., Lehigh University
Gonzalez, D., Lehigh University
Qin, T., Lehigh University
Huang, W. M., Lehigh University
Room temperature plasma is an attractive method to produce syngas via electrification of the endothermal methane dry reforming reactors. Electricity can be obtained from green sources thus lowering the CO2 burden of the reactor that normally utilizes fixed heat flux generates by burning natural gas. The optimization of such reactor operating conditions, however, becomes more complex and laboratory experiments need to be performed in conjunction with the experiment optimization to account for the multitude of external variables (chiefly thermal heat vs electricity to generate plasma), the resulting performance parameters, such as generated H2 amount, as well as sustainability constrains, such as the source of electricity used.

In this presentation, we show a comprehensive plasma-enhanced catalytic dry methane reforming reactor analysis of experiments to obtain the optimal operating conditions with the objective to maximize H2 production while minimizing the associated environmental impacts. In particular, variables explored included CO2/CH4 ratio, gas flow, reactor temperature, plasma intensity and water vapor content. The response parameters included reactant conversion, H2 produced, rate of reaction and carbon balance. Importantly, environmental impact calculations were also performed using Life Cycle Analysis to calculate environmental burden, in kg CO2 equivalent using the laboratory data obtained during the experiments. These calculations resulted in a set of solutions that allowed to maximize H2 production while minimizing their environmental impacts. Practical process design parameters that utilized these data will also be discussed.