Deep-learning-based simulator for femtosecond laser micro-machining

Shuntaro Tani; Yohei Kobayashi

doi:10.1117/12.2648050

18 April 2023 Deep-learning-based simulator for femtosecond laser micro-machining

Shuntaro Tani, Yohei Kobayashi

Proceedings Volume PC12408, Laser Applications in Microelectronic and Optoelectronic Manufacturing (LAMOM) XXVIII; PC1240802 (2023) https://doi.org/10.1117/12.2648050
Event: SPIE LASE, 2023, San Francisco, California, United States

Abstract

Femtosecond lasers are a powerful tool for micro-machining, while various parameters such as irradiation paths and pulse energies must be optimized. We have developed a method to simulate three-dimensional shapes after femtosecond pulse irradiation at arbitrary locations with arbitrary pulse energies using a difference equation for laser ablation based on deep learning. The deep-neural-network-based simulator successfully predicted the processing results for various materials such as semiconductors, glass, and polymers.

Conference Presentation

Citation Download Citation

Shuntaro Tani and Yohei Kobayashi "Deep-learning-based simulator for femtosecond laser micro-machining", Proc. SPIE PC12408, Laser Applications in Microelectronic and Optoelectronic Manufacturing (LAMOM) XXVIII, PC1240802 (18 April 2023); https://doi.org/10.1117/12.2648050

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