1996
DOI: 10.1002/pssb.2221970113
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Numerical solution to the general one‐dimensional diffusion equation in semiconductor heterostructures

Abstract: A method of solving numerically the one-dimensional diffusion equation for arbitrary profiles and arbitrary functional dependencies of the diffusion coefficient on the position, diffusant concentration and the time, is described. The technique is applied to a variety of diffusion problems in semiconductor quantum wells to illustrate its power and versatility. In particular solutions are shown for diffusion of graded interfaces, a concentration dependent diffusion coefficient, and the effect of a depth and time… Show more

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Cited by 7 publications
(16 citation statements)
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“…Figure 2 shows the behavior of error variation for the present method (SCM) as a function of N for different ∆ t used in the Runge-Kutta procedure. We have also included here the finite-difference based method [14] similar to the one used by Harrison [11]. In the case of the SCM, for all ∆t values error decreases sharply up to the point where either it approaches machine precision (~1 6 …”
Section: Examples and Discussionmentioning
confidence: 99%
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“…Figure 2 shows the behavior of error variation for the present method (SCM) as a function of N for different ∆ t used in the Runge-Kutta procedure. We have also included here the finite-difference based method [14] similar to the one used by Harrison [11]. In the case of the SCM, for all ∆t values error decreases sharply up to the point where either it approaches machine precision (~1 6 …”
Section: Examples and Discussionmentioning
confidence: 99%
“…For these computations we have used 2L = 80 nm and N = 400. In the second case [11], we consider diffusion of a graded gap QW, consisting of a 30 nm layer of A 0.9 B 0.1 C followed by a 10 nm layer of A 1-y B y C with graded profile and finally 30 nm of A 0.9 B 0.1 C. The initial condition for this case is: [11]. It can also be seen from Figs.…”
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confidence: 93%
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