Prediction of etching results and etching stabilization by applying principal component regression to emission spectra during in-situ cleaning

Iwakoshi, Takehisa; Hirota, Kosa; Mori, Masahito; Tanaka, J.; Itabashi, Naoshi

doi:10.1016/j.tsf.2007.08.114

Cited by 6 publications

(2 citation statements)

References 5 publications

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“…To reduce these fluctuations, a prediction model using statistical analysis has been developed and introduced into mass production for many applications. [4][5][6][7][8] An equipment engineering system (EES) is a tool that uses all the signals accumulated from an etching system to collect data in real time and statistically analyze etching properties (see Fig. 2).…”

Section: Introductionmentioning

confidence: 99%

Prediction of Fluctuations in Plasma–Wall Interactions Using an Equipment Engineering System

Fukasawa¹,

Kawashima²,

Kuboi³

et al. 2009

Jpn. J. Appl. Phys.

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The fluctuations in etch rates caused by changes in chamber conditions were studied. Excess deposition of C-F polymer on the chamber wall increased CF x density while H was consumed by the polymer and/or was deactivated on the conductive surface of Si electrodes. The change in radical densities had a clear relationship with the SiN etch rate. The etch rate was accurately predicted by statistical analysis using equipment engineering system (EES) data and optical emission spectroscopy (OES) signals which were extracted by considering both the physical model and the results of statistical analysis.

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Section: Introductionmentioning

confidence: 99%

Prediction of Fluctuations in Plasma–Wall Interactions Using an Equipment Engineering System

Fukasawa¹,

Kawashima²,

Kuboi³

et al. 2009

Jpn. J. Appl. Phys.

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“…1) In mass fabrications, there are problems, such as fluctuations in plasma etching performance characteristics and film thicknesses of gate stacks. [2][3][4] These problems have resulted in in situ (real time) etching monitors being developed for Si-gate processes. For example, optical interference monitors 5) are employed to estimate film thicknesses in Si-based transistor processes.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Measurement of W, TiN, and TaSiN Thicknesses Comprising Full-Metal Gates during Plasma Etching by Optical Interference of Etching Plasma

Iwakoshi¹,

Ono²,

Aoyama³

et al. 2008

jjap

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Film thicknesses of W, TiN, and TaSiN in a full-metal gate stack with photoresist masks were measured in real time during plasma etching with an in situ thickness monitor. The accuracy of such measurement was approximately AE1 nm. The monitor functions on the basis of the interference of plasma optical emission, reflected from the surface and base of the film. Although W and TiN have large absorption indexes, their thicknesses were more accurately measured when they became thinner. In particular, W thickness was estimated more accurately when it was smaller than approximately 10 nm.

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Sodium alginate coupled with organosilane quaternary ammonium salt for the antibacterial application

Cui

Sun

et al. 2022

Cellulose

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Prediction of etching results and etching stabilization by applying principal component regression to emission spectra during in-situ cleaning

Cited by 6 publications

References 5 publications

Prediction of Fluctuations in Plasma–Wall Interactions Using an Equipment Engineering System

Prediction of Fluctuations in Plasma–Wall Interactions Using an Equipment Engineering System

Real-Time Measurement of W, TiN, and TaSiN Thicknesses Comprising Full-Metal Gates during Plasma Etching by Optical Interference of Etching Plasma

Sodium alginate coupled with organosilane quaternary ammonium salt for the antibacterial application

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