We report on recent research on the development of data-driven ultrashort pulse laser processing to achieve higher productivity and quality. We are developing in-process monitoring, artificial intelligence (AI) optimization, and fast active control of the laser based on them. These key technologies are introduced for micro-drilling of metals and transparent materials and laser-induced periodic surface structure (LIPSS) formation on a silica glass. We demonstrate a fast pulse-to-pulse modulation of the fluences to control the ablation efficiency. A deep neural network was utilized to predict the 3-dimensional shapes of the ablation craters depending on the laser parameters (fluence and pulse duration). The scheme was extended to 10 sequential modulations of fluences. An in-process monitoring of the crack formation on glasses was implemented by optical transmission imaging with deep neural network. The optical reflection/transmission technique was also employed to probe the quality of the LIPSS formation on a silica glass.
Laser-induced periodic surface structure (LIPSS) in nanometer scale formed by femtosecond (fs) laser pulses depends strongly on laser parameters such as fluence and superimposed pulse number, as well as the surface condition of target materials. Process control based on in-process monitoring is one of the solutions to form the nanostructure stably and homogeneously. However, it is difficult to monitor the nanostructure in the process, because it is much smaller than the light wavelength. This paper reports on a new technique for in-process monitoring of the periodic nanostructure using its anti-reflection property. As a target, we used a synthetic quartz plate. The linear-polarized 1030-nm, 250-fs laser pulses from a Yb fiber laser amplification system operated at a repetition rate of 20 kHz were focused with an objective lens and scanned on the target surface. Microscopic images of the target surface with coaxial epi-illumination and transillumination were acquired with two CMOS cameras. From these images, the surface reflectivity and transmittance were evaluated. After the ablation experiment, the surface morphology was observed with a scanning electron microscope. The surface of which transmittance increased as reflectivity decreased, had a line-like periodic nanostructure with a period of ~200 nm and a depth of ~1 μm. On the other hand, the surface of which both transmittance and reflectivity decreased did not have the nanostructure. These results demonstrate that an observation technique using anti-reflection property is much more effective in monitoring fs-laser-induced nanostructure on glass in the process.
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