Kumar, Vinod

Marin, Guy

Thybaut, Joris

English

Ghent University Academic Bibliography

International Symposium on Chemical Reaction Engineering (ISCRE 22),  Maastricht , September 2-5, 2012 MicroKinetic Engine (µKE): A tool for (micro)kinetic modelling Vinod Kumar, Joris W. Thybaut, Guy B. Marin http://www.lct.UGent.be                                                                                     E-mail: Vinod.Kumar@Ugent.be  Laboratory for Chemical Technology, Krijgslaan 281 (S5), 9000 Ghent, Belgium European Research Institute of Catalysis ITNMUL TIMODObjective Development of a generic tool “MicroKinetic Engine”1 for (micro)kinetic modelling of chemical reactions High throughput Experimentations Microkinetic Modeling (includes all elementary steps) 1. Optimize catalyst properties (pore radius, site density, etc.) 2. Predict behavior for reactions / compounds of the same family Justification  Performs microkinetic modeling adopting complex networks of heterogeneous systems  No programming required by the end user  Incorporates differential and algebraic solvers + deterministic & stochastic optimization routines  Able to provide information about quasi-equillibruim steps. Reaction orders can also be estimated  No rate determining step.   Provides parity and residual plots along with the statistical analysis of results, e.g. 95% confidence interval, t-value, F value etc. µKE Features 1. Metaxas, K., J. Thybaut, G. Morra, D. Farrusseng, C. Mirodatos and G. Marin (2010). Topics in Catalysis 53(1-2): 64-76. 2. Heynderickx, P., J. Thybaut, H. Poelman, D. Poelman and G. Marin (2010). Applied Catalysis B-Environmental 95(1-2): 26-38. 00.10.20.30.40.50.60.70.80 200 400 600XC3H8 Wcat F-1C3H8   595 K621 K648 K𝐶3𝐻8  +  5𝑂2  → 3𝐶𝑂2 + 4𝐻2𝑂 Power law reaction kinetics Reaction orders estimated Data taken from the work performed at the lab by Heynderickx et al2 Power law 00.10.20.30.40.50.60.70.80 200 400 600XC3H8 Wcat F-1C3H8 595 K621 K648 K𝐶3𝐻8  + ∗ ⇌ 𝐶3𝐻8 ∗ 𝐶3𝐻8 ∗  +5𝑂2  → 3𝐶𝑂2 + 4𝐻2𝑂 +∗ C3H8 adsorbs on the catalyst surface and then reacts with 𝑂2(𝑔) forming products in gas phase  Underlying chemistry is reflected in the performance curves Reaction mechanism elucidation 00.10.20.30.40.50.60.70.80 200 400 600XC3H8 Wcat F-1C3H8 595 K621 K648 K𝐶3𝐻8  + ∗ ⇌ 𝐶3𝐻8 ∗ 𝑂2  + ∗ ⇌ 2𝑂 ∗ 𝐶3𝐻8 ∗  + 10𝑂 ∗ → 3𝐶𝑂2 ∗ +4𝐻2𝑂 ∗ +4 ∗ 𝐶𝑂2 ∗ ⇌ 𝐶𝑂2 +∗ 𝐻2𝑂 ∗⇌ 𝐻2𝑂 +∗ Reactants adsorption is followed by the surface reaction and the finally the products are desorbed Surface reaction is the slowest non-equilibrated step. Hence rate determining step. Trends are in agreement with the published data2 Case study  Kinetic modelling based on user defined reaction network  Top-down methodology proved to be helpful in using the Microkinetic engine (μKE)  A priori knowledge can  be used to reduce number of parameters to be estimated.  Significant estimation + physical meaning for the kinetic parameters of the microkinetic model Conclusion Authors acknowledge the funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement N° 238013 Acknowledgement References o Initial conditions for all experiments • Inlet flow rates • Temperature • Pressure • Catalyst weight  regression routine (ODRPACK) • Initial parameter values • Parameter limits • Fixing parameters •  parameter estimates and confidence intervals •  statistical significance of the regression •  parity diagrams •  … o Experimental results for all experiments • Outlet flow rates perform simulation for all experiments compare calculated and experimental outlet flow rates adjust parameter values fit ok? yes no µKE work flow Reactor model Kinetic model Non-isothermal parameter estimation using Arrhenius equation  _, 1...( ), 1...n ms response intermediate tot elem stepsj paramet rs esskr p C s Nf j Nk  𝒌𝒔 = 𝒌𝒂𝒗𝒈 ∙ 𝒆𝒙𝒑 −𝑬𝒂𝒄𝒕𝑹𝟏𝑻−𝟏𝑻𝒂𝒗𝒈 Mass balance for the catalyst’s active sites  Intermediates are more reactive than reactants and products, i.e. net rate of formation equals zero Mathematical model 𝑆 𝛽𝑗 =  𝑤𝑖  𝐹𝑖𝑙𝑐𝑎𝑙𝑐 − 𝐹𝑖𝑙exp 2         𝛽𝑗       𝑚𝑖𝑛𝑖𝑚𝑢𝑚𝑁𝑒𝑥𝑝𝑙=1𝑁𝑟𝑒𝑠𝑖=1 Objective function  𝑑(𝑉 ∙ 𝐶𝑖)𝑑𝑡= 𝐹 𝐶𝑖𝑖𝑛 − 𝐶𝑖 + 𝑅𝑖 ,   SBR 0in outi i i catF F Rw   CSTR d, 1...dii responsesFR i NW   PFR Batch Graphical user interface k(avg) Estimated values Activation energies Estimated values (kJ/mol) 𝑘𝐶3𝐻8𝑓𝑤𝑑 4.24±2.29 kPa-1s-1 𝐸𝐶3𝐻8𝑓𝑤𝑑 1.26±0.51 𝑘𝐶3𝐻8𝑟𝑒𝑣 (1.11±0.46)x10+08 s-1 𝐸𝐶3𝐻8𝑟𝑒𝑣  23.3±15.0 𝑘𝑂2𝑓𝑤𝑑  4.22±1.73 kPa-1s-1 𝐸𝑂2𝑓𝑤𝑑 0.399±0.11 𝑘𝑂2𝑟𝑒𝑣 (7.87±4.41)x10+07 s-1 𝐸𝑂2𝑟𝑒𝑣 13.7±5.3 𝑘𝑠 (5.61±2.23)x10+11 𝑘𝑔𝑐𝑎𝑡mol-1s-1 𝐸𝑠 124.0±21.0 𝑘𝐶𝑂2𝑟𝑒𝑣 (2.27±1.49)x10+01 s-1 𝐸𝐶𝑂2𝑟𝑒𝑣  74.9±51.4 𝑘𝐶𝑂2𝑓𝑤𝑑 (2.00±0.88)x10+01kPa-1s-1 𝐸𝐶𝑂2𝑓𝑤𝑑 1.37±0.66 𝑘𝐻2𝑂𝑟𝑒𝑣 (2.05±1.15)x10+01 s-1 𝐸𝐻2𝑂𝑟𝑒𝑣  (79.5±28.6 𝑘𝐻2𝑂𝑓𝑤𝑑 (3.09±1.10)x10+01 kPa-1s-1 𝐸𝐻2𝑂𝑓𝑤𝑑 0.70±0.55 Other case studies Toluene hydrogenation Oxidative coupling of methane Methane aromatization n-hexane hydrocracking  Total active site concentration : 1.204421 ± 0.00846 mol/𝑘𝑔𝑐𝑎𝑡 

Microkinetic engine (μKE): a software tool for (micro)kinetic modeling

https://biblio.ugent.be/publication/3158984/file/3159018

Microkinetic engine (μKE): a software tool for (micro)kinetic modeling

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