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Of critical importance in many manufacturing processes is the management of defects. Defects lead to lost production yield and poor reliability and failure of finished products. Defects can arise from an introduction of unwanted foreign material, incomplete removal of material (leaving behind a residue), unanticipated reaction of constituent materials or cleaning agents, or slowly occurring chemical processes triggered by external influences such as heat, moisture, and light. In all these instances, the chemical makeup of the defect is a key piece of information that could provide the manufacturing engineers with the potential source of the defect.
Most analytical laboratories are well equipped with techniques that yield elemental information of defects such as Energy Dispersive X-ray Spectroscopy (EDX), Total Reflection X-ray Fluorescence (TXRF), and Auger Spectroscopy with nanoscale spatial resolution that is regularly required in advanced manufacturing. While these techniques are useful in identifying metals and some inorganic materials, they are less useful with materials with same constituent elements as in many organic and inorganic materials since they do not reveal any chemical bonding information.
For molecular information, Fourier Transform Infrared Spectroscopy (FTIR) is by far the most widely used technique. However, since its spatial resolution is so poor (> 10 µm), other techniques such as Raman spectroscopy, Time-of-Flight Secondary Ion Mass Spectrometry (TOF-SIMS), and X-ray Photoemission Spectroscopy (XPS) are also utilized, sometimes in combination. The technique with the highest spatial resolution (with a nominal spatial resolution of about 200 nm) and low detection limits among these is TOF-SIMS. However, it is destructive, requires the sample to be vacuum compatible, and necessitates complex analysis.
Given the above state of the analytical instrumentation for defect analysis, it is not uncommon to encounter the use of many of these techniques in combination just to “guess” the molecular nature of the defects whenever their lateral sizes are less than about 1 micron; the situation worsens if the defect is very thin (< 100 nm) also since some of these techniques have poorer SNR at these thicknesses.
IR PiFM is well suited for the molecular analysis of nanoscale defects and residues due to its excellent spatial resolution and sensitivity. Unlike the guess work based on the results of multiple analytical techniques described above, PiFM in many instances will generate a definitive identity of the defect based on well-established FTIR spectra. Even though PiF-IR spectra are generated from ~ 10 nm regions, they match the bulk FTIR spectra remarkably well and thus can be used to identify defects as small as ~ 10 nm.
Figure 1 shows the PiF-IR spectra acquired on a 20nm polystyrene (PS) nanoparticle and the mica substrate along with the bulk FTIR spectra for both. The inset shows the topography and PiFM images at 1492 cm−1 and 1025 cm−1 to highlight the PS and mica substrate, respectively. The topography clearly shows that the particle is about 20 nm tall (note the contrast scale-bar shown above the image) and about 50 nm is lateral size arising from the convolution of the tip’s radius of curvature, which is typically about 30 nm due to the metallic coating. The additional spectral features between 1100 and 1360 cm−1 may be due to molecules from the liquid (eg., surfactant) that were deposited together with PS particles.
Figure 2 shows examples of identification of unknown defects found on silicon wafer based on their PiF-IR spectra. Figure 2a shows that the defect is about 100 nm in size and about 3 nm thick. The spectrum on the substrate clearly shows the signature of the native silicon oxide around 1090 cm−1. The spectrum of the defect matches the FTIR for Teflon well allowing us to identify the nano defect as a piece of Teflon-like material. Figure 2b shows a defect that is about 15 nm tall and about 50 nm in size. Given the tip’s radius of curvature, it is likely a spherical particle with a diameter of about 15 nm. Multiple spectra on the substrate and the particle show repeatable spectra. The silicon substrate can be identified by the broad peak centered about 1060 cm−1. The spectra for the particle match the FTIR spectrum for silica. These examples demonstrate the PiFM can identify both organic and inorganic nanoscale materials equally well.
Another common form of defect is residue. When the residue is ultra thin, its presence is extremely difficult to detect with existing microscopy or spectroscopy instrumentation. Figure 3 is an example of a residue on a bonding pad, which was not adhering properly to its mating part. PiF-IR spectra revealed a clear chemical signature of the residue that arose as a by-product of a processing step. Figure 3a shows the topography of the bonding pad while 3b shows the PiFM image at an absorption wavenumber associated with the residue defect.
In PiFM images, the signal strength is related to the absorption strength. Therefore, in image 3b, the regions that are colored gold are where the residue is present. The thickness of the residue is expected to be a couple of nanometers at most since the topography does not show feature that correlate with to the residue; rather it reveals the granular structure of the metal utilized in the bonding pad. In this example, the chemical nature of the metal pad or the residue defect is not specified intentionally.
In summary, IR PiFM is a powerful tool for molecular analysis of unknown defects and residue even when they are ~ 10 nm in size and ultra thin. When defect sizes too small or thin for the current analytical techniques such as TOF-SIMS, XPS, FTIR, Raman, and SEM/EDS, IR PiFM can step in to provide the critical information to understand the chemical nature of the defects.
|Lateral Resolution||~5 nm||> 0.5 µm||> 10 µm||> 0.2 µm||10 µm – 2 mm||~10 mm||1 nm * 0.5 µm EDS||0.2 nm||> 10 nm|
|Depth Probed||20 nm & bulk||> 500 nm||1 µm||1 nm||10 nm||10 nm||1 µm||~100 nm||10 nm|
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