Wafer charging quantification using image distortion

Xiang Wang; Chan Luo; Stacey Reeves; Isael Soto

doi:10.1117/1.JMM.22.2.021003

23 December 2022 Wafer charging quantification using image distortion

Xiang Wang, Chan Luo, Stacey Reeves, Isael Soto

Author Affiliations +

Journal of Micro/Nanopatterning, Materials, and Metrology, Vol. 22, Issue 2, 021003 (December 2022). https://doi.org/10.1117/1.JMM.22.2.021003

Abstract

Background

Electron beam induced charging can introduce complications during defect inspection and metrology applications. Caution needs to be taken when choosing scanning electron microscope (SEM) condition during recipe set up.

Aim

To identify a reliable key performance indicator (KPI) based on SEM imaging that does not require repeated exposure. This KPI needs to be strongly correlated to charging and easily quantified. It is expected that the KPI can help simplify the recipe creation flow and increase the recipe robustness.

Approach

Hypothesized surface charging either impedes or facilitates the probe beam scanning, which would result in shrinking or expending field-of-view, respectively.

Results

Tested the hypothesis on after-development-inspection wafers and observed image distortion being modulated by landing energy. Confirmed distortion, once presented, would increase with exposure repeats, which can be reasonably explained based on charging.

Conclusions

Image distortion can be used as a reliable KPI to quantify wafer charging. This will greatly simplify recipe creation and improve recipe robustness. Also, the neutral condition in turn benefits the imaging and minimizes distortion.

Citation Download Citation

Xiang Wang, Chan Luo, Stacey Reeves, and Isael Soto "Wafer charging quantification using image distortion," Journal of Micro/Nanopatterning, Materials, and Metrology 22(2), 021003 (23 December 2022). https://doi.org/10.1117/1.JMM.22.2.021003

Received: 15 September 2022; Accepted: 5 December 2022; Published: 23 December 2022

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KEYWORDS

Distortion

Semiconducting wafers

Scanning electron microscopy

Calibration

Metrology

Electron microscopes

Image processing

Background

Aim

Approach

Results

Conclusions

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