Abstract
This chapter shows how rate constants can either be calculated or be derived from experimental results. Calculating rate constants involves determining the initial and the transition state of a process, the energies of these states, and their partition functions. We show that the general expression for the partition functions can often be simplified when a degree of freedom is a vibration, a rotation, or a free translation. Recipes can be given for how to combine partition functions to get rate constants for processes like Langmuir–Hinshelwood and Eley–Rideal reactions, adsorption and desorption, and diffusion. The phenomenological or macroscopic equation is the essential equation to get rate constants from experiments. It is shown how to use it for simple desorption, simple and dissociative adsorption, uni- and bimolecular reactions, and diffusion. Lateral interactions can affect rate constants substantially, but because they are relatively weak, special attention needs to be given to the reliability of calculations of these interactions. Cross validation and Bayesian model selection are discussed in relation to the cluster expansion for these interactions.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
If one determines the activation energy E act by a linear regression of a set of rate constants at different temperatures, then this energy is not exactly equal to E bar+E zp. This is because the factors \((k_{\mathrm{B}}T/h)(\tilde{Q}^{\ddagger}/\tilde{Q})\) also give a small contribution to E act. See the discussion at the end of Sect. 4.2.2.
- 2.
- 3.
There are actually two more factors [7]. There is the partition function of the electronic states Q el and the partition function of the spins of the nuclei Q nucl. We will ignore both. The electronic ground state defines the potential energy of the system, so the partition function is defined only by the summation in Eq. (4.11). As the electronic excitation energies are, except for rare case, much larger than the thermal energy, we get Q el=1. The spin state of the nuclei generally does not change during a reaction. So its partition functions for the transition and initial state cancel in the expression for the rate constant, and can therefore be ignored.
- 4.
Note that below room temperature this expression should not be used for molecular hydrogen. The rotational excitations for this molecule are so high, that the high-temperature approximation only becomes valid at higher temperatures.
- 5.
It may be that there is a very low barrier for diffusion of the adsorbed molecule. In that case the partition function of the initial or transition state will have a 2D translational partition function for the center of mass motion as a factor. See the example of CO desorption in Sect. 4.4.6.
- 6.
Parts of Sect. 4.5.4 have been reprinted with permission from A.P.J. Jansen, C. Popa, Bayesian approach to the calculation of lateral interactions: NO/Rh(111), Phys. Rev. B 78, 085404 (2008). Copyright 2008, American Physical Society.
References
C.G.M. Hermse, F. Frechard, A.P. van Bavel, J.J. Lukkien, J.W. Niemantsverdriet, R.A. van Santen, A.P.J. Jansen, J. Chem. Phys. 118, 7081 (2003)
R.A. van Santen, J.W. Niemantsverdriet, Chemical Kinetics and Catalysis (Plenum, New York, 1995)
W.H. Press, B.P. Flannery, S.A. Teukolsky, W.T. Vetterling, Numerical Recipes. The Art of Scientific Computing (Cambridge University Press, Cambridge, 1989)
D.G. Truhlar, A.D. Isaacson, B.C. Garrett, in Theory of Chemical Reaction Dynamics, Part IV, ed. by M. Baer (CRC Press, Boca Raton, 1985), pp. 65–138
C.S. Tautermann, D.C. Clary, J. Chem. Phys. 122, 134702 (2005)
C.S. Tautermann, D.C. Clary, Phys. Chem. Chem. Phys. 8, 1437 (2006)
D.A. McQuarrie, Statistical Mechanics (Harper, New York, 1976)
A. Messiah, Quantum Mechanics (North-Holland, Amsterdam, 1961)
H. Goldstein, Classical Mechanics (Addison-Wesley, Amsterdam, 1981)
M.J. Frisch, G.W. Trucks, H.B. Schlegel, G.E. Scuseria, M.A. Robb, J.R. Cheeseman, J.A. Montgomery Jr., T. Vreven, K.N. Kudin, J.C. Burant, J.M. Millam, S.S. Iyengar, J. Tomasi, V. Barone, B. Mennucci, M. Cossi, G. Scalmani, N. Rega, G.A. Petersson, H. Nakatsuji, M. Hada, M. Ehara, K. Toyota, R. Fukuda, J. Hasegawa, M. Ishida, T. Nakajima, Y. Honda, O. Kitao, H. Nakai, M. Klene, X. Li, J.E. Knox, H.P. Hratchian, J.B. Cross, C. Adamo, J. Jaramillo, R. Gomperts, R.E. Stratmann, O. Yazyev, A.J. Austin, R. Cammi, C. Pomelli, J.W. Ochterski, P.Y. Ayala, K. Morokuma, G.A. Voth, P. Salvador, J.J. Dannenberg, V.G. Zakrzewski, S. Dapprich, A.D. Daniels, M.C. Strain, O. Farkas, D.K. Malick, A.D. Rabuck, K. Raghavachari, J.B. Foresman, J.V. Ortiz, Q. Cui, A.G. Baboul, S. Clifford, J. Cioslowski, B.B. Stefanov, G. Liu, A. Liashenko, P. Piskorz, I. Komaromi, R.L. Martin, D.J. Fox, T. Keith, M.A. Al-Laham, C.Y. Peng, A. Nanayakkara, M. Challacombe, P.M.W. Gill, B. Johnson, W. Chen, M.W. Wong, C. Gonzalez, J.A. Pople, Gaussian 03, revision b.04. Gaussian, Inc., Pittsburgh, PA (2003)
M. Abramowitz, I.A. Stegun, Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables (Dover, New York, 1965)
A. Szabo, N.S. Ostlund, Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory (McGraw-Hill, New York, 1982)
D. Frenkel, B. Smit, Understanding Molecular Simulation: From Algorithms to Applications (Academic Press, London, 2001)
A.R. Leach, Molecular Modelling. Principles and Applications (Longman, Singapore, 1996)
W. Koch, M.C. Holthausen, A Chemist’s Guide to Density Functional Theory (Wiley-VCH, New York, 2000)
C.J. Cramer, Essentials of Computational Chemistry (Wiley, Chichester, 2004)
R.A. van Santen, M. Neurock, Molecular Heterogeneous Catalysis (Wiley-VCH, Weinheim, 2006)
O. Trushin, A. Karim, A. Kara, T.S. Rahman, Phys. Rev. B 72, 115401 (2005)
K. Sastry, D.D. Johnson, D.E. Goldberg, P. Bellon, Phys. Rev. B 72, 085438 (2005)
N. Castin, L. Malerba, Nucl. Instrum. Methods Phys. Res., Sect. B, Beam Interact. Mater. Atoms 267, 3148 (2009)
G. Henkelman, H. Jónsson, J. Chem. Phys. 111, 7010 (1999)
G. Henkelman, G. Jóhannesson, H. Jónsson, in Progress in Theoretical Chemistry and Physics, ed. by S.D. Schwarts (Kluwer Academic, London, 2000)
G. Mills, H. Jónsson, G.K. Schenter, Surf. Sci. 324, 305 (1995)
C. Popa, W.K. Offermans, R.A. van Santen, A.P.J. Jansen, Phys. Rev. B 74, 155428 (2006)
C. Popa, R.A. van Santen, A.P.J. Jansen, J. Phys. Chem. C 111, 9839 (2007)
D. Curulla, A.P. van Bavel, J.W. Niemantsverdriet, ChemPhysChem 6, 473 (2005)
A.P. van Bavel, Understanding and quantifying interactions between adsorbates: CO, NO, and N- and O-atoms on Rh(100). Ph.D. thesis, Eindhoven University of Technology, Eindhoven (2005)
C. Popa, A.P. van Bavel, R.A. van Santen, C.F.J. Flipse, A.P.J. Jansen, Surf. Sci. 602, 2189 (2008)
D.H. Wei, D.C. Skelton, S.D. Kevan, Surf. Sci. 381, 49 (1997)
J.N. Murrell, S. Carter, P. Huxley, S.C. Farantos, A.J.C. Varandas, Molecular Potential Energy Functions (Wiley-Interscience, Chichester, 1984)
A. van der Walle, G. Ceder, J. Phase Equilibria 23, 348 (2002)
V. Blum, A. Zunger, Phys. Rev. B 69, 020103(R) (2004)
A.P.J. Jansen, W.K. Offermans, in Computational Science and Its Applications—ICCSA-2005. LNCS, vol. 3480, ed. by O. Gervasi (Springer, Berlin, 2005)
C.G.M. Hermse, A.P.J. Jansen, in Catalysis, vol. 19, ed. by J.J. Spivey, K.M. Dooley (Royal Society of Chemistry, London, 2006)
Y. Zhang, V. Blum, K. Reuter, Phys. Rev. B 75, 235406 (2007)
D.M. Hawkins, J. Chem. Inf. Comput. Sci. 44, 1 (2004)
A.P.J. Jansen, C. Popa, Phys. Rev. B 78, 085404 (2008)
N.A. Zarkevich, D.D. Johnson, Phys. Rev. Lett. 92, 255702 (2004)
R. Drautz, A. Díaz-Ortiz, Phys. Rev. B 73, 224207 (2006)
D.E. Nanu, Y. Deng, A.J. Böttger, Phys. Rev. B 74, 014113 (2006)
T. Mueller, G. Ceder, Phys. Rev. B 80, 024103 (2009)
E.T. Jaynes, G.L. Bretthorst, Probability Theory: The Logic of Science (Cambridge University Press, Cambridge, 2003)
A. Gelman, J.B. Carlin, H.S. Stern, D.B. Rubin, Bayesian Data Analysis (Chapman & Hall/CRC, Boca Raton, 2003)
D. Sivia, J. Skilling, Data Analysis: A Bayesian Tutorial (Oxford University Press, Oxford, 2006)
B. Hammer, Phys. Rev. B 63, 205423 (2001)
J.N. Brønsted, Chem. Rev. 5, 231 (1928)
M.G. Evans, M. Polanyi, Trans. Faraday Soc. 34, 11 (1938)
P. Hohenberg, W. Kohn, Phys. Rev. 136, B864 (1964)
W. Kohn, L.S. Sham, Phys. Rev. 140, A1133 (1965)
R.G. Parr, W. Yang, Density-Functional Theory of Atoms and Molecules (Oxford University Press, New York, 1989)
N.G. van Kampen, Stochastic Processes in Physics and Chemistry (North-Holland, Amsterdam, 1981)
A.P.J. Jansen, Comput. Phys. Commun. 86, 1 (1995)
A.M. de Jong, J.W. Niemantsverdriet, Surf. Sci. 233, 355 (1990)
J.M. Thomas, W.J. Thomas, Principles and Practice of Heterogeneous Catalysis (VCH, Weinheim, 1997)
G.A. Somorjai, Introduction to Surface Chemistry and Catalysis (Wiley, Chichester, 1993)
R. Becker, Theorie der Wärme (Springer, Berlin, 1985)
A. Cassuto, D.A. King, Surf. Sci. 102, 388 (1981)
V.P. Zhdanov, Elementary Physicochemical Processes on Solid Surfaces (Plenum, London, 1991)
J. Mai, V.N. Kuzovkov, W. von Niessen, Phys. Rev. E 48, 1700 (1993)
J. Mai, V.N. Kuzovkov, W. von Niessen, Physica A 203, 298 (1994)
J. Mai, V.N. Kuzovkov, W. von Niessen, J. Chem. Phys. 100, 6073 (1994)
E.A. Kotomin, V.N. Kuzovkov, Modern Aspects of Diffusion-Controlled Reactions: Cooperative Phenomena in Bimolecular Processes (Elsevier, Amsterdam, 1996)
O. Kortlüke, V.N. Kuzovkov, W. von Niessen, Chem. Phys. Lett. 275, 85 (1997)
S. Kirkpatric, C.D. Gelatt Jr., M.P. Vecchi, Science 220, 671 (1983)
D.A. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning (Addison-Wesley, Reading, 1989)
H.P. Schwefel, Evolution and Optimum Seeking (Wiley, Chichester, 1995)
Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs (Springer, Berlin, 1999)
W. Banzhaf, P. Nordin, R.E. Keller, F.D. Francone, Genetic Programming: An Introduction (Morgan Kaufmann, San Francisco, 1998)
D. Corne, M. Dorigo, F. Glover, New Ideas in Optimization (McGraw-Hill, London, 1999)
E. Bonabeau, M. Doriga, G. Theraulaz, Swarm Intelligence: From Natural to Artificial Systems (Oxford University Press, New York, 1999)
A.P.J. Jansen, Phys. Rev. B 69, 035414 (2004)
M.M.M. Jansen, C.G.M. Hermse, A.P.J. Jansen, Phys. Chem. Chem. Phys. 12, 8053 (2010)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Jansen, A.P.J. (2012). How to Get Kinetic Parameters. In: An Introduction to Kinetic Monte Carlo Simulations of Surface Reactions. Lecture Notes in Physics, vol 856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29488-4_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-29488-4_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29487-7
Online ISBN: 978-3-642-29488-4
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)