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Organic based nano-contaminants are a common defect type found in micro-electronics manufacturing processes, including semiconductor, data storage, and LED. These types of organic contaminants are a serious defectivity issue for manufacturers as they cause yield issues, process delays and can lead to scrap product.
The contaminants arise from a variety of sources, including chemical processing, cleaning techniques, airborne molecular contamination, wafer transfer and handling, as well as the degree of human interaction with the processes.
Significant efforts are expended in the prevention and detection of defects; however, for many of these defects, there is still a significant class, including organic nanocontaminants, where unambiguous identification is difficult to obtain using existing instrumentation, due to insufficient resolution or even damage to the sample during measurement.
AFM-IR not only enables precise chemical identification of contaminants, but can also provide mutliple property analyses with nanoscale resolution.
To demonstrate nanoscale chemical characterization capabilities on the nanoIR2-FS, contaminated silicon wafers were prepared using known materials typical of those found in semiconductor fabriation environments and analyzed. For each sample, pping AFM-IR imaging was used to locate the contaminants, followed by subsequent AFM-IR measurements.
The AFM height image (Fig. 1a) illustrates the thickness variation (20-100nm) of the contaminant reside (human skin tissue) on the wafer. AFM-IR spectra were then collected at sites with variable sample thickness (Fig. 1b). As expected, the observed IR intensities differed with sample thickness; however, the overall signal to noise ratio is sufficient to accurately identify the material, even at 20nm thickness, reflecting the excellent sensitivity in detection of thin samples.
New FASTspectra™ capabilities on the nanoIR2-FS enable faster acquisition of spectra over the full IR tuning range, allowing for a reduction in spectral acquisition time by a factor of 10. This achievement, illustrated in figure 2, still enables accurate FTIR spectra to be collected. The AFM-IR spectra from the sample were compared against a common FTIR database (KnowItAll, Bio-Rad Inc.). The ~30 nm tall contamination residue was positively identified as polyethylene terephthalate (PET), a polymer typically used in polyester fabrics.
In this note, the nanoIR2-FS was used to successfully identify nanoscale organic contaminants in manufacturing of semiconductors. These study results show that nanoscale IR spectroscopy is a powerful tool to accurately characterize defects in semiconductors and other electronic devices.