Process Recipe Optimization using Calibrated Simulation Engine SFR Workshop November 8, 1999 Junwei Bao, Nickhil Jakatdar, Costas Spanos Berkeley, CA The goal of this work is to calibrate the lithography simulation engine by accurately extracting the model parameters, and optimize process recipe to obtain a maximum yield. 2/28/2019

Motivation Current lithography simulators are parameter limited as opposed to model limited. Importance of predictive capabilities is increasing with increasing development costs and time-to-market pressures. Process recipe needs to be optimized considering the effect of parameter variations. 2/28/2019

Moving the Process Development from Real World to Virtual World (Lithography Equipment) Process Inputs (temp.,time,dose) Process Output Process Inputs Virtual World (Process Models) Model Coefficients Simulated Output 2/28/2019

Parameter Extraction and Recipe Optimization Framework Experiment Data Spatial variation filter Param. & op. point variance Param. mean values Calibrated Sim. Eng. Target Specs. of features Recipe of max. yield In-line sensor measurement Maximization of overlapping area 2/28/2019

Parameter Extraction -- Unpatterned Experiments 1 .5 Deprotection 140C 135C 120C 110C Exposure + PEB Parameters 0 1 2 3 4 5 6 7 Exposure Dose (mJ/cm2) 3000 2000 Develop Parameters Develop Rate in A/sec 1000 0 0.5 1 Normalized concentration of unreacted sites 2/28/2019

Parameter Extraction -- Patterned Experiments Mask 1 Mask 2 Mask 3 Mask 4 Mask 5 Mask 6 Mask 7 Mask 8 Mask 9 Mask 10 Masks 1-10 differ in the line-space ratios 0.25 micron process technology OPC assisted masks -1 Focus +1 -1 Focus +1 AFM vs Simulation 2/28/2019

Recipe Optimization Framework Process Inputs Calibrated Lithography Simulator Simulated Output Target Profile + - RECIPE OPTIMIZER 2/28/2019

Recipe Optimization 2/28/2019 Resist Th : 655 nm Exposure : 18.3 mJ/cm2 Focus : +0.39 mm PEB temp : 126oC PEB time : 80 secs Develop time : 80 secs 2/28/2019

Future Work -- Recipe Optimization with Variations Parameter distributions In-die spatial variation Simulated Output distributions Profiles within spec. Calibrated Lithography Simulator Operating Point distributions + - Overlapping to get yield RECIPE OPTIMIZER 2/28/2019