Robust Ion-Implantation Process Design through Statistical Analysis

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In this work, for the first time, we present a TCAD methodology to rigorously account for statistical variations due to these random process errors (inherent in all semiconductor processes), and thereby design a robust ion-implantation process. This paper demonstrates the importance of taking statistical process variations into account when designing semiconductor processes, and provides a methodology for doing so. An on-axis, high-energy ion-implant process is used as a vehicle to demonstrate the methodology. UT-MARLOWE is the well-calibrated (and hence predictive) simulation tool of choice. It is shown that crystal-cut errorsand implanter-tilt errors can result in a considerably off-axis implant for this nominally on-axis implant: instead of the intended tilt = 0?, the implant actually occurs at an average tiltof ~0.65?, with a significant probability of having tilt > 1?. Knowledge of the error-statistics is used to design a robust process (i.e. a process relatively immune to statistical process variations), thereby providing better control over device performance. This methodology can also account for deterministic errors arising from beam divergence and process-disk geometry in multi-wafer machines.

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Journal: TechConnect Briefs
Volume: Technical Proceedings of the 2000 International Conference on Modeling and Simulation of Microsystems
Published: March 27, 2000
Pages: 40 - 43
Industry sector: Sensors, MEMS, Electronics
Topic: Modeling & Simulation of Microsystems
ISBN: 0-9666135-7-0