We have developed an imaging spectroscopic reflectometry (ISR) method based on hyperspectral imaging and deep learning to detect defects in the bottom region of high-aspect-ratio nanostructures. ISR enables fast and non-destructive imaging of the bottom critical dimension (BCD) of channel holes (CHH) on a chip die of vertical NAND (V-NAND). A supervised learning model is built to predict the BCD by associating a pre-measured hyperspectral cube with scanning electron microscopy images after decapsulation of the top of the sample. The BCD predicted by ISR shows a high correlation of R2=0.72 with the actual BCD, and the distribution of CHH not open (NOP) defects on the chip die identified by bright field inspection after decapsulation is consistent with the BCD image obtained by ISR. In addition, ISR can detect defects that occur at arbitrary positions relative to the optical critical dimension (OCD) of the die. On fully integrated V-NAND chips, the ISR result showed a high correlation (R2=0.82) with the failure rate caused by CHH NOP, while the conventional spot OCD showed only R2=0.41. Thus, ISR can be used to optimize the etch process for weak wafer edge regions and to detect defective etch equipment.
We developed imaging spectroscopic reflectometry (ISR) based on hyperspectral imaging and deep learning and built it as an in-line facility. After obtaining the reflectance as a hyperspectral cube of the 350 – 1100 nm wavelength region throughout the whole device wafer, dimension of the nanometer-sized structure can be imaged through the supervised learning model. In particular, by including near-IR region in the spectrum, the bottom critical dimension (BCD) of the high-aspect ratio structure such as channel hole (CHH) of the 3D NAND evaluated in this study can be imaged non-destructively and rapidly. After removing the top through decapsulation, the actual BCD was measured by SEM and was linked to the hyperspectral cube to construct a supervised learning model. The BCD predicted through ISR showed a correlation of R2=0.72 with the actual BCD. In addition, the shape of the defect on device chip caused by insufficient etch at the bottom of CHH, obtained by ISR was identical to the inspection image taken after decapsulation. Compared to spot measurement, ISR shows the advantage of being able to capture defects that occur at random locations in the device wafer. From our high volume sample of 3D NAND, ISR result showed a high correlation (R2 = 0.82) with the rate of failure caused by channel hole while the conventional spot measurement showed only R2 = 0.41. By using ISR, we could optimize the etching process for the wafer edge area where CHH formation is particularly weak.
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