Journal of Computational Electronics

, Volume 14, Issue 3, pp 773–787 | Cite as

Existence of bounded discrete steady state solutions of the van Roosbroeck system with monotone Fermi–Dirac statistic functions

  • K. Gärtner


If in the classic van Roosbroeck system (Bell Syst Tech J 29:560–607, 1950) the statistic function is modified, the equations can be derived by a variational formulation or just using a generalized Einstein relation. In both cases a dissipative generalization of the Scharfetter–Gummel scheme (IEEE Trans Electr Dev 16, 64–77, 1969), understood as a one-dimensional constant current approximation, is derived for strictly monotone coefficient functions in the elliptic operator \(\nabla \cdot { {f}(v)} \nabla \), v chemical potential, while the hole density is defined by \(p={\mathcal {F}}(v)\le e^v.\) A closed form integration of the governing equation would simplify the practical use, but mean value theorem based results are sufficient to prove existence of bounded discrete steady state solutions on any boundary conforming Delaunay grid. These results hold for any piecewise, continuous, and monotone approximation of \({ {f}(v)}\) and \({\mathcal {F}}(v)\). Hence an implementation based on this discretization will inherit the same stability properties as the Boltzmann case based on the Scharfetter–Gummel scheme. Large chemical potentials and and related degeneracy effects in semiconductors can be approximated. A proven, stability focused blueprint for the discretization of a fairly general, steady state Fermi–Dirac like drift–diffusion setting for semiconductors using mainly new results to extend classic ideas is the main goal.


Generalized Scharfetter–Gummel scheme Fermi–Dirac statistics Generalized Einstein relation  Dissipativity  Bounded discrete steady state solutions Unique thermodynamic equilibrium Degenerate semiconductors 

Mathematics Subject Classification

65N08 65N12 35J55 



The author thanks A. Glitzky and J. A. Griepentrog for very helpful discussions, H. Doan for the close to rounding error Polylog data used for the approximations, and T. Koprucki for the pointer to [19]. The reviewer comments are acknowledged, too. Their more outside point of view was very helpful to improve the readability.


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© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Weierstrass Institute for Applied Analysis and StochasticsBerlinGermany
  2. 2.ICSUniversitá della Svizzera italianaLuganoSwitzerland

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