Laser doping mechanism of 4H-SiC by KrF excimer laser irradiation using SiNx thin films

Yasunami, Takuma; Nakamura, Daisuke; Katayama, Keita; Kakimoto, Yoshiaki; Kikuchi, Toru; Ikenoue, Hiroshi

doi:10.35848/1347-4065/acb0d8

Cited by 3 publications

(1 citation statement)

References 30 publications

(28 reference statements)

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“…Notably, in [116], the laser doping method was employed, with the application of an ultraviolet nanosecond laser, to co-dope with fluorine and induce an N-type transition in phosphorus-doped germanium. Similarly, in [117], laser doping was used for nitrogen doping in 4H-silicon carbide. A KrF excimer laser with a wavelength of 248 nm was utilized in the experimental study.…”

Section: Harnessing Photothermal Reactions and Functional Additive In...mentioning

confidence: 99%

Fabrication of Smart Materials Using Laser Processing: Analysis and Prospects

Murzin,

Stiglbrunner

2023

Applied Sciences

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Laser processing is a versatile tool that enhances smart materials for diverse industries, allowing precise changes in material properties and customization of surface characteristics. It drives the development of smart materials with adaptive properties through laser modification, utilizing photothermal reactions and functional additives for meticulous control. These laser-processed smart materials form the foundation of 4D printing that enables dynamic shape changes depending on external influences, with significant potential in the aerospace, robotics, health care, electronics, and automotive sectors, thus fostering innovation. Laser processing also advances photonics and optoelectronics, facilitating precise control over optical properties and promoting responsive device development for various applications. The application of computer-generated diffractive optical elements (DOEs) enhances laser precision, allowing for predetermined temperature distribution and showcasing substantial promise in enhancing smart material properties. This comprehensive overview explores the applications of laser technology and nanotechnology involving DOEs, underscoring their transformative potential in the realms of photonics and optoelectronics. The growing potential for further research and practical applications in this field suggests promising prospects in the near future.

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Section: Harnessing Photothermal Reactions and Functional Additive In...mentioning

confidence: 99%

Fabrication of Smart Materials Using Laser Processing: Analysis and Prospects

Murzin,

Stiglbrunner

2023

Applied Sciences

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Prediction of Contact Resistance of 4H–SiC by Machine Learning Using Optical Microscope Images after Laser Doping

Iwaizumi,

Yasunami,

Katayama

et al. 2024

SSP

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In this study, machine learning (ML) was employed to predict the electrical properties of finished devices, specifically focusing on the state of the contacts at the electrodes. The predictions are based on optical microscope images of the surface conditions, which were captured immediately following the laser doping of nitrogen atoms into 4H-SiC. The laser doping process involved varying the laser fluence from 0.4 to 4.0 J/cm2 and using number of laser irradiation to 5, 10, 20, and 100 shots. The ML prediction was carried out in two steps. In STEP1, we classified the contact status into three types.: 1) Schottky junctions (insufficient doping), 2) Ohmic contact (good contact), and 3) Not ohmic (damage caused by laser irradiation). In STEP2, contact resistance prediction (numerical regression) was performed using the dataset predicted as an ohmic contact. As a result, we found that the three classifications in STEP1 could be predicted with a high accuracy of over 88%. Furthermore, the contact resistance prediction in STEP2 could be made with an accuracy (RMSPE: root mean square percent error) of 27.2%. Visualizing the prediction basis of numerical regression using modulus-reweighted grad-regression activation mapping (MoRAM) revealed that the ML model focused on the inside of the laser-irradiated area in the optical microscope image. The results of the scanning electron microscopy observation of the laser-irradiated area showed that ablation and residuals were generated during laser doping in that area. Consequently, it was concluded that our ML model predicted the contact resistance of the finished device taking into consideration these surface conditions. Even highly-skilled laser doping technicians have difficulty predicting the resistance values arising from the ablation and residue conditions. Based on above results, we conclude that our ML model is capable of predicting the electrical characteristics of a finished device, a task that is often considered challenging for humans.

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Effect of Substrate Heating on Low Contact-Resistance Formation by Excimer Laser Doping for 4H-SiC

Kakimoto,

Yasunami,

Katayama

et al. 2024

SSP

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N atoms were doped into SiNx/4H-SiC substrates by KrF laser irradiation while the substrates were heated. The diffusion depth of nitrogen increased above the solubility limit when the sample heated to 600°C was irradiated by the laser compared to the sample at room temperature. In addition, a clear 4H-SiC pattern was observed in the cross-sectional TEM diffraction image, thereby suggesting that sufficient crystal recovery was achieved even under melt-solidification conditions owing to the effect of substrate heating.

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Laser doping mechanism of 4H-SiC by KrF excimer laser irradiation using SiNx thin films

Cited by 3 publications

References 30 publications

Fabrication of Smart Materials Using Laser Processing: Analysis and Prospects

Fabrication of Smart Materials Using Laser Processing: Analysis and Prospects

Prediction of Contact Resistance of 4H–SiC by Machine Learning Using Optical Microscope Images after Laser Doping

Effect of Substrate Heating on Low Contact-Resistance Formation by Excimer Laser Doping for 4H-SiC

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