Calibre Siemens publications at SPIE Advanced Lithography Conference 2024.

01_An artificial intelligence machine leaning (AI/ML) approach with cross-technology node learning for multi-layer process defect predictions

02_Machine learning (ML) based SEM contour extraction accelerated by GPU for etch modeling application

03_OPC and modeling solution towards 0.55na EUV stitching

04_Low landing energy as an enabler for optimal contour based OPC modeling in the EUV era

05_Improving OPC model accuracy of dry resist for low k1 EUV patterning 

06_Cloud flight plan for post-tapeout flow jobs 

07_Advanced process control by machine learning based virtual metrology for high product mix manufacturing 

08_Using machine learning method to improve design sampling efficiency for fab applications 

09_Towards efficient and accurate cost functions for EUVL stochastic-aware OPC correction and verification: via failure probability versus image and process variation band metrics 

10_The effect of edge placement error on deformity and roughness calculation 

11_Fast and accurate automatic wafer defect detection and classification using machine learning based SEM image analysis 

12_Contour metrology for process matching and OPC qualification with machine learning-based site selection 

13_Layout simulation for directed self-assembly with chemo-epitaxy methodology 

14_Principal components and optimal feature vectors of EUVL stochastic variability: applications of Karhunen-Loève Expansion to efficient estimation of stochastic failure probabilities and stochastic metrics 

15_A new era DFM solution for yield enhancement using machine learning 

16_An integrated verification flow for curvilinear mask 

17_Fast full chip curvilinear MRC for advanced manufacturing nodes 

18_Model-based OPC using the MEEF matrix III