Estimation of the mobility of low temperature polycrystalline silicon thin film transistors through deep learning

Akira Mizutani, Fuminobu Hamano, Keita Katayama, Daisuke Nakamura, Tetsuya Goto, Hiroshi Ikenoue

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The crystallization of a-Si leads to alterations in the morphology of Si film such as surface color and surface roughness as a result of excimer laser annealing (ELA). These surface changes correlate with the characteristics of polysilicon films. The quality of crystallized poly Si has been evaluated by Non-destructive optical inspection methods. This study aims to use deep learning to estimate the quantitative relationship between the microscope images of a low-temperature polycrystalline silicon (LTPS) film and the mobility of an LTPS thin film transistor (TFT). This method would make it possible to measure the mobility from the images captured after annealing and improve the crystallization by in situ feedback. An a-Si substrate with a film thickness of 100 nm was polycrystallized by employing a KrF (wavelength of 248 nm) excimer laser, after which an optical microscope image of the substrate was captured. By changing the laser fluence and the number of shots (44 conditions N=10), LTPS films of various surface morphology were fabricated. We fabricated 440 transistors using these LTPS channels (channel size L = 20 μm, W = 30 μm) and measured their mobilities. Then, we performed deep learning with these sets of annealed optical microscope images and the corresponding mobilities. The mobility was estimated with an accuracy of ±12.8 cm2V-1s-1. Further improvement of the prediction accuracy (<±5 %) is needed for in-situ feedback. We plan to increase the number of images and use transfer learning to improve prediction accuracy.

Original languageEnglish
Title of host publicationLaser Applications in Microelectronic and Optoelectronic Manufacturing (LAMOM) XXVI
EditorsCarlos Molpeceres, Jie Qiao, Aiko Narazaki
PublisherSPIE
ISBN (Electronic)9781510641815
DOIs
Publication statusPublished - 2021
EventLaser Applications in Microelectronic and Optoelectronic Manufacturing (LAMOM) XXVI 2021 - Virtual, Online, United States
Duration: 2021 Mar 62021 Mar 11

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11673
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceLaser Applications in Microelectronic and Optoelectronic Manufacturing (LAMOM) XXVI 2021
Country/TerritoryUnited States
CityVirtual, Online
Period21/3/621/3/11

Keywords

  • Deep learning
  • Excimer laser annealing
  • Low-temperature poly-Si
  • Thin-film transistor

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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