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Proceedings Paper

Automated lamellar block copolymer process characterization
Author(s): G. Bernard; X. Chevalier; A. Dervilllé; J. Foucher
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Paper Abstract

Lamellar CD-SEM image analysis is one of the key step for the development of new polymer formulations. We present in this paper a new approach for the analysis of lamellar CD-SEM that can be extended to any type of other pattern (contact…) with a machine learning approach. We will also focus on the roughness analysis and specifically the Line Edge Roughness (LER) and Power Spectral Density (PSD) with a robust estimation that takes into account curvature of the line. The last part is dedicated to the introduction of a process optimisation technique using machine learning to optimize process parameters from a first design of experiment.

Paper Details

Date Published: 19 March 2018
PDF: 6 pages
Proc. SPIE 10586, Advances in Patterning Materials and Processes XXXV, 105860Z (19 March 2018); doi: 10.1117/12.2297347
Show Author Affiliations
G. Bernard, POLLEN Metrology (France)
X. Chevalier, Arkema S.A. (France)
A. Dervilllé, POLLEN Metrology (France)
Lab. Jean Kuntzmann Grenoble (France)
J. Foucher, POLLEN Metrology (France)


Published in SPIE Proceedings Vol. 10586:
Advances in Patterning Materials and Processes XXXV
Christoph K. Hohle, Editor(s)

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