FLOOPS: Understand Its History and a Calibrated Process-Simulation Workflow — working record
Yenra | October 4, 2026
https://yenra.com/floops-florida-object-oriented-process-simulator/

Purpose: Explain the simulator's documented historical role and assess what recipe, mesh, model and calibration evidence a process simulation needs.

Instructions: Make a working copy. Fill the fields below with actual evidence and units. Record unavailable information as unknown, give it an owner, and resolve it before using the record for acceptance. Keep raw evidence by reference. Use the approved method, equipment limits and acceptance rules for your application. This blank record does not establish qualification.

1. Software/product name, exact version, model documentation and study purpose
   Response / evidence reference: ______________________________

2. Initial geometry/materials, units and process input evidence
   Response / evidence reference: ______________________________

3. Implant species, dose, energy, orientation and full thermal history
   Response / evidence reference: ______________________________

4. Model choices, parameter sources, calibrated changes and fixed parameters
   Response / evidence reference: ______________________________

5. Mesh, boundaries, solver/time controls and sensitivity results
   Response / evidence reference: ______________________________

6. Calibration datasets, measurement methods, uncertainty and fitting outputs
   Response / evidence reference: ______________________________

7. Withheld validation cases, common output definitions and error denominator
   Response / evidence reference: ______________________________

8. Supported process range, extrapolations, unresolved discrepancies and reviewer
   Response / evidence reference: ______________________________

Teaching example (fictional; not acceptance criteria):
Fictional junction-depth comparison A calibration case measures a junction depth of 100 nm and the fitted model predicts 104 nm: a 4% difference relative to measurement. With the parameters fixed, a separate case measures 150 nm and the model predicts 165 nm: a 10% difference. The second case is a more demanding check of prediction. Define junction depth consistently, include measurement uncertainty and use application-specific acceptance criteria.

Primary source context (consult for applicable method and scope):
Mark E. Law and Stephen M. Cea's 1998 paper
https://swamp.mse.ufl.edu/wp-content/uploads/sites/286/2020/06/Law_1998_CMS_12_289.pdf
University of Florida's 2013 account of Law's work
https://www.eng.ufl.edu/news/honors-awards/semiconductor-industry-association-honors-uf-professor-mark-law/
Synopsys records its acquisition of ISE in 2004
https://www.synopsys.com/company/acquisitions.html
Synopsys' process-simulation overview
https://www.synopsys.com/manufacturing/tcad/process-simulation.html

Review outcome: accepted / held / further evidence needed
Reviewer and date: __________________
Open actions, owner and due date: __________________