Mathematical Modeling in Electrochemistry

  • Mordechay Schlesinger
Part of the Modern Aspects of Electrochemistry book series (MAOE, volume 43)


The specific intended theme of the present volume is modeling and numerical simulation in electrochemistry. In general, theoretical analysis and simulation may be performed for a particular phenomenon or a collection of phenomena that occur in a specific system. The objective of the analysis may be to understand and elucidate the phenomena and their impact on system performance and how to design the various components of a system to harvest or to avoid a detrimental influence. Thus, the ultimate objective is to carry out either performance evaluation of an existing system and/or attempt performance prediction of a new design. The aim of this chapter is to introduce and review the nature of mathematical modeling in general and in the context of modern electrochemistry in particular. This chapter attempts to describe how current and emerging trends in hardware and software computer applications and system development are intended to assist practitioners. One rather modern trend is toward the merger of these two disciplines as computer-aided mathematical modeling.


Laplace Equation Boundary Potential Primitive Component Schlesinger System Unknown Potential 
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  1. 1.
    1. Davis ME (1984) Numerical methods and modeling for chemical engineers, Wiley, New York.Google Scholar
  2. 2.
    2. Press WH, Teukolsky SA, Vetterling WT, and Flannery BP (1992) Numerical recipes in C: the art of scientific computing, 2nd edn. Cambridge University Press, Cambridge.Google Scholar
  3. 3.
    3. Foley JD, van Dam A, Feiner SK, and Hughes JF (1994) Computer graphics: principles and practice, 2nd edn. Addison-Wesley, Reading, MA.Google Scholar
  4. 4.
    4. Abell ML and Braselton JP (1994) Differential equations with maple V, Academic Press, San Diego, CA.Google Scholar
  5. 5.
    5. Pressman RS (1987) Software engineering: a practitioner's approach, McGraw-Hill, New York.Google Scholar
  6. 6.
    6. Flanagan D (1996) Java in a nutshell, O'Reilly, Cambridge, MA.Google Scholar
  7. 7.
    Cidambi I (1996) M.Sc. thesis. University of Windsor, Windsor, Ontario, Canada.Google Scholar
  8. 8.
    8. Martincic F (1997) Honours Bachelor of Computer Science thesis. University of Windsor, Windsor, Ontario, Canada.Google Scholar
  9. 9.
    Marcuzzi E (1997) M.Sc. thesis. University of Windsor, Windsor, Ontario, Canada.Google Scholar
  10. 10.
    10. Webb JP (1995) Reports Prog. Phys. 58: 1673–1712.CrossRefGoogle Scholar
  11. 11.
    11. Guyer JE, Boettinger WJ, Warren JA, and McFadden GB (2004) Phys. Rev. Rev. E 69: 021603.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Mordechay Schlesinger
    • 1
  1. 1.Department of PhysicsUniversity of WindsorON Windsor

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