1998
DOI: 10.1116/1.589831
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Model database for determining dopant profiles from scanning capacitance microscope measurements

Abstract: To help correlate scanning capacitance microscope measurements of silicon with uniformly doped concentrations, model capacitance curves are calculated and stored in a database that depends on the probe-tip radius of curvature, the oxide thickness, and the dopant density. The oxide thicknesses range from 5 to 20 nm, the dopant concentrations range from 10 17 to 10 20 cm Ϫ3 , and the probe-tip radius of curvature is set to 10 nm. The cone-shaped probe is oriented normal to the sample surface, so that the finite-… Show more

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Cited by 39 publications
(13 citation statements)
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“…A fast algorithm has been developed by Kopanski et a1. [87] using interpolation on the stored solutions of the three-dimensional Poisson equation [88] for various tip-sample bias voltages, oxide thicknesses, dopant concentrations and tip radii. The probe is modeled in this case as a cone with a hemispherical shape which does include the effect of stray fields.…”
Section: Scanning Capacitance Microscopymentioning
confidence: 99%
“…A fast algorithm has been developed by Kopanski et a1. [87] using interpolation on the stored solutions of the three-dimensional Poisson equation [88] for various tip-sample bias voltages, oxide thicknesses, dopant concentrations and tip radii. The probe is modeled in this case as a cone with a hemispherical shape which does include the effect of stray fields.…”
Section: Scanning Capacitance Microscopymentioning
confidence: 99%
“…It can be used to arbitrary tip shapes as well as surface morphology. However, until now axially symmetric cases, sections of three-dimensional problems in Cartesian coordinates [31,32] and combination of both have been analysed [33][34][35][36].…”
Section: Analysed Probesmentioning
confidence: 99%
“…Most of the work related to samples containing pn-junctions was carried out in regards to junction delineation. Especially on small structures, a quantitative determination of the 2D doping distribution is obviously impossible without inverse modeling [14] or intensive simulations using empirical databases [15]. In addition, rather sophisticated calibration schemes had to be applied, which usually required intensive simulation [13].…”
Section: Introductionmentioning
confidence: 99%