Intraparticle diffusion reaction networks

Effect of Intraparticle Diffusion for Reaction Networks For multiple reactions, intraparticle diffusion resistance can also affect the observed selectivity and yield. For example, for consecutive reactions intraparticle diffusion resistance reduces the yield of the intermediate (often desired) product if both reactions have the same order. For parallel reactions diffusion resistance reduces the selectivity to the higher-order reaction. For more details see, e.g., Carberry, Chemical and Catalytic Reaction Engineering, McGraw-Hill, 1976 and Fevenspiel, Chemical Reaction Engineering, 3d ed., Wiley, 1999. 

For more complex reactions, the effect of intraparticle diffusion resistance on rate, selectivity, and yield depends on the particulars of the network. Also, the use of the Thiele modulus-effectiveness factor relationships is not as easily applicable, and numerical solution of the diffusion-reaction equations may be required. 

Kinetic and reactor modeling will always be a fundamental step in the design of chemical processes. The main objective of this task is to construct a computational tool for predicting product distribution and reactor behavior at various operating conditions. In this sense, modeling of heavy oil hydroprocessing is of extreme complexity because there are so many parallel physical and chemical processes inside the reactor phase equilibrium, mass transfer of reactants and products between the three phases present in the reactor (gas, liqnid, and solid), intraparticle diffusion, a vast reaction network, and catalyst deactivation, to name a few. Ideally, the contribution of all these events must be accounted for in order to increase prediction capability however, the level of sophistication of the model will generally depend on the pursued objectives. 

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