Process Simulation

Process simulation provides a better understanding of individual process steps, saves time and cost in the design and optimization of new technologies, and helps solve problems in manufacturing. Our focus of interest are ion beam related processes such as ion implantation and sputtering, and post-implant thermal processes. We are interested both in the numerical algorithms and in modeling of the process physics and chemistry. Over the years, two simulation programs have evolved which are available to external users (see below).

If you are a student and are interested in the simulation methods and their application on the nanoscale, you can learn more in the course Materialien, Prozesse und Technologien der Mikroelektronik, opens an external URL in a new window. A simplified version of PyTopSim is developed in the seminar Wissenschaftliches Programmieren in Python, opens an external URL in a new window.

If you want to join our team, check our topics offered for diploma theses and dissertations, or contact Gerhard Hobler.

Simulation tools:

IMSIL (Implant and Sputter sImuLator) is a Monte Carlo simulator of ion irradiation effects based on the binary collision approximation. It can handle static 1D, 2D, and rotational symmetric 3D target geometries composed of an arbitrary number of amorphous materials and optionally one crystalline material. In addition, dynamic changes to geometry and composition of 1D targets can be simulated. The ability to simulate ion channeling and crystal-orientation dependent sputtering distinguishes IMSIL from other widely used Monte Carlo programs. Models for ion implantation in silicon are well calibrated. It is our plan to develop IMSIL into a full 3D static/dynamic binary collision simulator. More information on the most recent version of IMSIL is found in the manual, opens a file in a new window. IMSIL is usually given to non-commericial users free of charge. To obtain a license, contact Gerhard Hobler.

PyTopSim is a 2D/3D continuum simulator for focused ion beam milling based on the string method. It works best for surfaces that can be described by height functions. PyTopSim is calibrated for some ion species/energy combinations and Si or W targets. For other ion-target combinations, the physical input has to be provided, e.g., by running IMSIL. PyTopSim is completely written in Python and is open source. It can be downloaded from here, opens an external URL in a new window. Note, while PyTopSim is functional for many applications as demonstrated by test examples, it does not come up to the same standards as IMSIL. If you are interested in this kind of simulation, you are welcome to contact Gerhard Hobler.


FIB milling of a sidewall

Focused beams of Ga ions are routinely used to thin samples for transmission electron microscopy (TEM). This is best done at grazing incidence, i.e.,  the ion beam almost parallel to the surface to be eroded, see the gray area in vertical direction in the figure on the right. The original geometry is indicated by the dashed line. Under the beam the surface recedes to the right. By scanning (moving) the beam to the right at an appropriate speed the side wall can be eroded to a desired position. The W layer screens the Si substrate from the beam tails.

The image quality of TEM is affected by the contamination with Ga ions and the damage generated by the ion bombardement. The figure on the right shows the Ga concentration calculated self-consistently with surface evolution using the binary collision Monte Carlo simulator FIBSIM, a predecessor of IMSIL.


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