According to the design rule shrinkage, more precise control of mask CD, including mean to target and uniformity, is
required in lithography process. Since dry etching is one of the most critical processes to determine CD qualities in
photomask, optical emission spectroscopy (OES) to monitor plasma status during dry etching process could be useful.
However, it is not possible to obtain distributional information of plasma with a conventional OES tool because the OES
acquires totally integrated signals of light from the chamber. To overcome the limit of OES, we set up a spatially
resolved (SR)-OES tool and measure the distribution of radicals in plasma during dry etch process. The SR-OES consists
of a series of lenses, apertures, and a pinhole as a spatial filter which enable us to focus on certain area in the chamber, to
extract the emitted light from plasma, and to perform the spectroscopic analysis. The Argon based actinometry combined
with SR-OES shows spatially distinguished peaks related to the etch rate of Chromium on photomask. In this paper, we
present experimental results of SR-OES installed on a commercial photomask dry etcher and discuss its practical
effectiveness by correlation of the results with chamber etch rate.
A mid-IR optical emission spectrometer (mid-IR OES) was designed and constructed to detect the absolute spectral
radiant exitance of IR signatures. A 256-array PbSe detector was adopted to analyze the mid-IR emission spectrum from
countermeasure flares. The spectral response of the optical emission spectrometer was obtained using a directly heated
graphite blackbody. The absolute emissions of their IR signatures were inferred by applying spectral response to the
spectrum intensity data. Also, we devised a post processing method for compensating diffraction order overlap in a mid-
IR grating spectrometer using an array detector. We confirmed the validity of the compensation method by comparing
the signal intensities acquired using the different methods.
Maskless lithography (ML) systems have been researched as an alternative technologies of the conventional
photolithography systems. Digital micromirror devices (DMD) can be used in ML systems as a role of photomask in the
conventional photolithography systems. For high-throughput manufacturing processes DMDs in ML systems must be
driven to their operational limits, often in harsh conditions. We propose an optical system and detection methodologies
to detect DMD malfunctions to ensure perfect mask image transfer to the photoresist in ML systems. We categorize
DMD malfunctions into two types. One is bad DMD pixel caused from mechanical defect and the other is data transfer
error. We detect bad DMD pixels with 20×20 pixels using white and black image tests. We confirm data transfer errors
at high frame rate operation of DMD by monitoring changes in the frame rate of a target DMD pixel driven by the input
data with a set frame rate of up to 28,000 frames per second (fps).
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