Proteus MetroKit

Efficient Metrology Interfacing

Proteus MetroKit is a toolset designed to facilitate and automate the process of interfacing with metrology tools, thereby minimizing tool downtime and maximizing engineering efficiency. The toolset provides the ability to generate test patterns for modeling, automate the creation of metrology recipes for empirical data collection, reformat and analyze empirical data collected from the metrology tool for use with other Proteus applications, and create gauge files for model tuning. This product is offered as an upgrade option to IC WorkBench Plus (ICWB Plus) and Proteus WorkBench (PWB).

Metrology tool time and engineering time are far from a commodity. Synopsys is aware of this and has developed a toolset to make the most efficient use of each. The MetroKit Scanning Electron Microscope (SEM) Recipe Creator allows you to program the CD-SEM offline eliminating unnecessary down-time in the fab.

Avoid costly human errors and save time by automating the SEM data analysis and conversion process. A seamless link is provided between the SEM results database and the modeling tools. SEM data is screened for outliers and automatically converted to the format required for model generation prior to passing it to the OPC model calibration tools ProGen and ProGenPLUS, and/or the Synopsys Sentaurus Lithography simulator. The process results in increased data quality and reduced time to accurate model.

TPG key features:

  • Intuitive and flexible GUI environment for generating calibration structures and custom test chip templates
  • Extensive application programming interface or API provides a Tcl based interface to fully automate the tool with complete access to all functionality available within the GUI
  • Library Browser – Provides access to many standard test pattern structures as well as the ability to populate user defined test pattern structures
  • Link to Sentaurus Lithography – Any patterns created in TPG can be reused inside Sentaurus Lithography for rigorous simulation
Figure 1: Model generation flow

Figure 1: Model generation flow