Abstract :

Ravi Datta has been a Professor and Director of WPI Fuel Cell Center since 1998. He also served as Chemical Engineering Department Head at WPI from 1998 to 2005. Before this, he taught Chemical Engineering at the University of Iowa starting in 1981, when he received his PhD from University of California, Santa Barbara. Earlier, he got his B. Tech. from IIT, Kharagpur, and worked at L&T in Bombay for 4 years. His research interests are in reaction engineering of fuel cells, hydrogen catalysis, and renewable fuels. His recent work has focused on novel fuel cells, novel catalysts, fuel cell membranes, and reaction networks. He is a coauthor of 135 papers and 6 patents, and has been a mentor to 50 graduate students, including 25 doctoral students. Visualizing and Analyzing Reaction Networks  Complex reaction networks comprising of multiple steps and pathways are the norm in combustion, industrial catalysis, electrochemistry, and biology. While one can now predict kinetics of these molecular steps from first principles, a comprehensive and insightful framework for analyzing these reaction networks in their full complexity is not yet widely available. Toward this goal, we have developed in recent years a new approach called the “Reaction Route (RR) Graph” approach, which is described in this presentation. Unlike other graph-theoretical approaches, our RR Graphs are fully consistent with underlying stoichiometric analysis, pathway enumeration, mass balance, and Hess’s law. The last two requirements, labeled as Kirchhoff’s flux law (KFL) and Kirchhoff’s potential law (KPL), are directly analogous to the corresponding Kirchhoff’s laws in electrical networks. By further defining a reaction resistance, RR Graphs and electrical circuits become entirely analogous, rendering RR Graphs a powerful quantitative graph theoretical tool for pathway and kinetics analysis. In fact, it allows one to develop analytical QSS rate laws based on the LHHW approach that are exact for linear step kinetics, and approximate but precise for even nonlinear kinetics. Further, a comparison of pathway flux and step resistances allows a precise and transparent pruning of the network to whittle it down to its essence. Our RR Graph approach is explained first with the help of a simple 7-step nitrous oxide decomposition example, and then exemplified with the help of a 17-step water-gas shift catalysis example, which is used to draw the RR Graph, enumerate all 71 reaction pathways graphically as walks, and perform flux analysis to identify the dominant reaction pathways and the rate-limiting steps in a transparent manner, resulting in a highly reduced mechanism and rate expression that agrees well with the complete micro-kinetic model.