In modern
semiconductor industry, ion implantation is the most important
technique for adding dopants into semiconductor materials. The main
advantage of this technique is the precise control of the process
parameters, which is especially useful for the creation of very shallow
dopant distribution in a semiconductor device.
Because the electrical properties of a semiconductor device strongly
depend on the distribution of the dopants, very precise simulation
methods are needed in order to explain and simulate this process.
Thereby the behavior of the device can be predicted and parameters can
be optimized. As a result of the miniaturization of the devices in the
last decade, three-dimensional simulations are often necessary.
These precise simulation methods are one of the most critial steps
concerning the simulation time of a full three dimensional process
simulation. Due to the complicated structures and the small dimensions
of modern semiconductor devices, Monte Carlo simulation methods have
often been used to describe non-planarity effects, phenomena resulting
from ion channeling and large tilt angles, and to provide accurate
point-defect distributions for rapid thermal annealing processes. To
reach the expected accuracy, three-dimensional simulations have to be
performed with sophisticated models, especially for very shallow
implantation conditions. Meeting all these requirements demands
simulation times which exceed one day or even more on high-end
workstations.
Therefore the analytical simulation of ion implantation is desirable to
avoid a bottleneck in the process simulation flow. On this account an
analytical module for the multidimensional process simulation tool MCIMPL-II
has been developed to allow a fast, stable, and precise simulation of
inserting dopants into a three-dimensional structure. This module
calculates the distribution of dopants with analytical distribution
profiles, where the parameters are delivered from moment look-up tables.
Also some research is
being done in the field of multilayer models, specifically in the field
of
three-dimensional dose-conservation models.
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