Neural network approach to rapid thin film characterization

Nickhil H. Jakatdar; Xinhui Niu; Costas J. Spanos

doi:10.1117/12.304402

1 April 1998 Neural network approach to rapid thin film characterization

Nickhil H. Jakatdar, Xinhui Niu, Costas J. Spanos

Proceedings Volume 3275, Flatness, Roughness, and Discrete Defects Characterization for Computer Disks, Wafers, and Flat Panel Displays II; (1998) https://doi.org/10.1117/12.304402
Event: Optoelectronics and High-Power Lasers and Applications, 1998, San Jose, CA, United States

Abstract

A novel approach for thin film thickness and optical constant extraction from spectral reflectance data is presented here. This methodology combines the global minimization abilities of Adaptive Simulated Annealing with the high computational efficiency of Neural Networks to solve complex characterization problems in real time. The optical constants of many thin films such as Polysilicon are a function of the processing conditions and hence the real time measurement of these parameters could possibly be used in real time or run to run process control applications.

Citation Download Citation

Nickhil H. Jakatdar, Xinhui Niu, and Costas J. Spanos "Neural network approach to rapid thin film characterization", Proc. SPIE 3275, Flatness, Roughness, and Discrete Defects Characterization for Computer Disks, Wafers, and Flat Panel Displays II, (1 April 1998); https://doi.org/10.1117/12.304402

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