2019
DOI: 10.1016/j.cnsns.2018.09.028
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Numerical simulation of porous silicon morphology using a monotone iterative method

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Cited by 3 publications
(1 citation statement)
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“…As for the continuous case, the numerical monotone iterative methods require the knowledge of upper and lower solutions in order to generate two monotone sequences that converge to the solution of the problems under investigation. Numerical techniques of this nature have been employed to solve the multidimensional semiconductor Poisson equation [8], to simulate quantumcorrected energy transport models [9], to study numerically the solutions of parabolic problems with time delays [10], to investigate two-dimensional simulation of submicron MOSFETs [11], to provide numerical analysis of coupled systems of nonlinear parabolic equations [12], and to simulate porous silicon morphologies [13]. In various of these reports and many other articles which employ discrete monotone iterative approaches, this methodology has been used to prove the existence and uniqueness of solutions, as well as to investigate the numerical efficiency of the computational algorithms.…”
Section: Introductionmentioning
confidence: 99%
“…As for the continuous case, the numerical monotone iterative methods require the knowledge of upper and lower solutions in order to generate two monotone sequences that converge to the solution of the problems under investigation. Numerical techniques of this nature have been employed to solve the multidimensional semiconductor Poisson equation [8], to simulate quantumcorrected energy transport models [9], to study numerically the solutions of parabolic problems with time delays [10], to investigate two-dimensional simulation of submicron MOSFETs [11], to provide numerical analysis of coupled systems of nonlinear parabolic equations [12], and to simulate porous silicon morphologies [13]. In various of these reports and many other articles which employ discrete monotone iterative approaches, this methodology has been used to prove the existence and uniqueness of solutions, as well as to investigate the numerical efficiency of the computational algorithms.…”
Section: Introductionmentioning
confidence: 99%