| AVS 66th International Symposium & Exhibition | |
| New Challenges to Reproducible Data and Analysis Focus Topic | Wednesday Sessions |
| Session RA+AS+BI-WeA |
| Session: | Addressing Reproducibility Challenges using Multi-Technique Approaches |
| Presenter: | Thierry Conard, IMEC, Belgium |
| Authors: | T. Conard, IMEC, Belgium P.A.W. van der Heide, IMEC, Belgium A. Vanleenhove, IMEC, Belgium C. Zborowski, IMEC, Belgium W. Vandervorst, IMEC, Belgium |
| Correspondent: | Click to Email |
Repeatability and reproducibility in surface analysis in the semiconductor industry are key to for supporting efficient process development as well as High Volume Manufacturing (HVM). As two examples, long term repeatability is critically important when comparing to historical data, while reproducibility is required to support technology transfers when HVM of specific devices is to be carried out at multiple sites. This however introduced a number of unique challenges for running a characterization facility.
In this presentation we will present a number of examples that can result in reproducibility issues. Particular focus will be in the areas of X-ray Photoelectron Spectroscopy (XPS) Secondary Ion Mass Spectrometry (SIMS). The first and foremost causes of repeatability and reproducibility arise from instrumental variation. A second important source arises from samples variability. We will show that assessing long-term instrumental stability is potentially hindered by long term variation of samples characteristics. We will also show that an understanding of the characterization techniques is paramount to understanding such issues.
Next to the “pure” technical causes of repeatability and reproducibility, is the human factor. This involve for instance decision making in data treatment during for example, fitting procedures, statistical treatments, etc. This will be illustrated using practical examples. And with present day characterization depending more heavily on computational support/ commercial software, potential detriments to characterization repeatability will again be made evident. Finally, we will show through round-robin results, that combining all the above factors, widely varying results can be obtained on the same samples.