Discrete Modeling of Lattice Systems: The Concept of Shannon Entropy Applied to Strongly Interacting Systems

Thomas Wallek, Martin Pfleger, Andreas Pfennig

Research output: Contribution to journalArticlepeer-review


Discrete modeling is a novel approach that uses the concept of Shannon entropy to develop thermodynamic
models that can describe fluid-phase behavior. While previous papers have focused on reviewing its theoretical background and
application to the ideal-gas model as one limiting case for fluid phases, this paper addresses its application to lattice models for
strongly interacting condensed phase systems, which constitute the other limiting case for fluids. The discrete modeling approach
is based on the discrete energy classes of a lattice system of finite size, represented by a distribution of discrete local
compositions. In this way, the model uses the same level of discretization as classical statistical thermodynamics in terms of its
partition functions, yet avoids (1) a priori averaging of local compositions by utilizing a distribution, and (2) confinement to
systems of infinite size. The subsequent formulation of the probabilities of discrete energy classes serves as the basis for
introducing the concept of Shannon information, equivalent to thermodynamic entropy, and for deriving the equilibrium
distribution of probabilities by constrained maximation of entropy. The results of the discrete model are compared to those
derived from Monte Carlo simulations and by applying the Guggenheim model of chemical theory. We point out that this
applicability of discrete modeling to systems of finite size suggests new possibilities for model development.
Original languageEnglish
Pages (from-to)2483-2492
JournalIndustrial & Engineering Chemistry Research
Issue number8
Publication statusPublished - 2 Feb 2016


  • Shannon entropy
  • discrete modeling
  • thermodynamic modeling
  • maximum entropy principle
  • lattice model
  • local compositions

Fields of Expertise

  • Mobility & Production

Treatment code (Nähere Zuordnung)

  • Basic - Fundamental (Grundlagenforschung)


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