SPIE Advanced Lithography Symposium 2018 – day 4

My hat is off to the speakers who brave the 8am time slot on the last day of the conference.  They are often talking to a sparse crowd as the stragglers slowly trickle in.  The exception was William Miller of Qualcomm, whose excellent talk at 8am was very well attended.  For us semiconductor types, it was very enlightening to hear the customer’s perspective on what goes wrong in manufacturing.

Since my papers were all done for the week, I spent the day just listening.  Bruno Azeredo (ASU) gave a fascinating talk on electrochemical nanoimprinting of silicon in the newly revamped Novel Patterning Technologies conference.  I also enjoyed watching my former student Meghali Chopra present results on etch optimization with software from her new company Sandbox Semiconductor.  My coauthor from imec Vito Rutigliani gave a great talk, showing how different underlayers (below the resist) affect the image contrast of SEM images, changing the noise and bias in roughness measurements so that biased roughness measurements are essentially useless.

There were several talks aimed at using defect review SEMs as fast metrology tools, allowing for a dramatic increase in the amount of data that can be practically collected.  This is great for looking for stochastic defects, especially defective contact holes that occur at or below the ppm level (one bad contact hole in a million).  We still need to see calibration results comparing these larger pixel size/larger spot size tools to traditional CD-SEMs.

The stochastics theme continued on Thursday with afternoon talks by Peter de Schepper of Inpria and Eric Hendrickx (standing in for Peter de Bisschop) of imec looking for defects at the million-feature level.  Another talk in the EUV Resist Roughness session set me off on mini-diatribe, which I will repeat here for those who didn’t watch me coopt an author’s Q&A time to give it the first time. 

In trying to understand how low we might be able to push line-edge roughness, we often want to understand the separate contributions of photon shot noise and resist noise (both of which are translated by the image log-slope into the observed edge errors).  Suppose the total 3-sigma roughness for our features is 3nm, and we estimate that this same resist exposed with an image that has no photon shot noise would produce 1.8 nm of roughness.  Would it be appropriate to say that the resist contributes 60% of the total roughness?  No, and making such a statement is quite misleading.  Why?  If the photon shot noise and the resist contributions to roughness are independent, then their contributions would add in quadrature, so that variance (not standard deviation) is divided up between the two sources.  If we took out the 1.8 nm resist contribution, what would the roughness be?  2.4 nm, only a 20% reduction from the original 3nm, not a 60% reduction.   If we insist on assigning a percent contribution to photon and resist noise, we must do it on the variance scale.  In this case, photon shot noise would contribute 64% to the total variance, and the resist would contribute the other 36%.  When it comes to noise, we should always focus on the biggest contributor since the quadrature addition will amplify its importance.

I stayed till the bitter end, closing out another great week at the SPIE Advanced Lithography Symposium.  We didn’t get much of an update from ASML or the semiconductor companies on the recent progress of EUV lithography.  Multibeam electron lithography and directed self-assembly continue to make slower than expected progress in wafer patterning.  But multi-beam mask writing is doing great, enabling very good progress in nanoimprint lithography.  The hot topics wax and wane from year to year, but progress is always made, thanks to the innovative work of the people at this conference.  See you next year!

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