Surface plasmon resonance (SPR) is a very important metrology in biology detection. Phase modulation is one of the
SPR detection technologies and the sample changes can be recognized from the phase variation. It is able to detect very
tiny bio sample variation due to its high sensitivity. In this study, the optical system design based on a paraboloidal
lens-based surface plasmon resonance instrument will be used to control the SPR critical angle. The charge coupled
device camera (CCD camera) will be used to record the images of the bio-reaction and (5,1) phase-shifting algorithm
will be adopted to retrieve the phase fringes of the whole spot from the intensity maps. The combination of the angle
control SPR system and the (5,1) phase-shifting algorithm will expand the whole spot detection ability from the intensity
to phase modulation because the intensity maps are going to be recorded for the (5,1) phase-shifting algorithm
calculation. The difference between (5,1) phase-shifting algorithm and Five-Step Algorithm1 is that (5,1)
phase-shifting algorithm only needs one image map at one time during the bio reaction and Five-Step Algorithm requires
five image maps. Therefore, (5,1) phase-shifting algorithm will reduce the process of experiment and the requirement
of the memory. The different concentration alcohols were measured by the optical system to verify the (5,1)
phase-shifting algorithm applied in SPR phase modulation measurement and to prove the idea is workable and
successful.
We will present a complete example that demonstrates daily CD monitor for good CDSEM control, including sampling plan, monitoring procedure, and monitoring and matching data for multiple CDSEM. In addition, we also investigate two methods to address the carbon contamination problem. In the first method, carryover trends on three different film stacks, poly, metal, and multi-layer metal, before and after plasma clean are compared in search of ways to minimize carryover. The second method applies statistical treatment to remove the effect of carryover while maintaining sensitivity over small fluctuations in line CD monitor results. Both linear regression and exponentially weighed moving average calculated from daily monitor data are used to model the baseline carryover trend for the purpose of isolating tru tool variability. Using this method, we can easily quantify the long-term stability of each CDSEM, and with that, we are able to calculate the true long-term process variation Cp by subtracting the CDSEM variation component from the observed total Cp.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.