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Search Publications by: Bryan Barnes (Fed)

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Displaying 76 - 100 of 137

Fourier Domain Optical Tool Normalization for Quantitative Parametric Image Reconstruction

September 5, 2013
Author(s)
Jing Qin, Richard M. Silver, Bryan M. Barnes, Hui Zhou, Francois R. Goasmat
There has been much recent work in developing advanced optical metrology methods that use imaging optics for critical dimension measurements and defect detection. Sensitivity to nanometer scale changes has been observed when measuring critical dimensions

Harnessing 3D Scattered Optical Fields for sub-20 nm Defect Detection

June 24, 2013
Author(s)
Bryan M. Barnes, Martin Y. Sohn, Francois R. Goasmat, Hui Zhou, Richard M. Silver, Abraham Arceo
Experimental imaging at =193 nm of sub-resolved defects performed at several focus positions yields a volume of spatial and intensity data. Defects are located in a differential volume, given a reference, with up to 5x increase in sensitivity.

3-D Optical Metrology of Finite sub-20 nm Dense Arrays using Fourier Domain Normalization

March 25, 2013
Author(s)
Jing Qin, Hui Zhou, Bryan M. Barnes, Ronald G. Dixson, Richard M. Silver
Reduced target dimensions requiring improved resolution and sensitivity have driven the need to use and analyze the phase and scattered frequency information available when using image-based scatterometry systems. One such system is scatterfield microscopy

Scatterfield Microscopy of 22 nm Node Patterned Defects using Visible and DUV Light

April 4, 2012
Author(s)
Bryan M. Barnes, Martin Y. Sohn, Francois R. Goasmat, Hui Zhou, Richard M. Silver, Abraham Arceo
Smaller patterning dimensions and novel architectures are fostering research into improved methods of defect detection in semiconductor device manufacturing. This initial experimental study, augmented with simulation, evaluates scatterfield microscopy to

Fundamental Limits of Optical Patterned Defect Metrology

November 14, 2011
Author(s)
Richard M. Silver, Bryan Barnes, Martin Sohn, Hui Zhou, Jing Qin
The semiconductor manufacturing industry is now facing serious challenges in achieving defect detection rates with acceptable throughput and accuracy. With conventional bright-field and dark-field inspection methods now at their limits, it has become

A Bayesian Statistical Model for Hybrid Metrology to Improve Measurement Accuracy

July 31, 2011
Author(s)
Richard M. Silver, Nien F. Zhang, Bryan M. Barnes, Jing Qin, Hui Zhou, Ronald G. Dixson
We present a method to combine measurements from different techniques that reduces uncertainties and can improve measurement throughput. The approach directly integrates the measurement analysis of multiple techniques that can include different