An atomic force microscopy (AFM) image of a surface is a convolution of the tip geometry and sample features. It is important to develop tip characterisers and estimate the tip shape for a more accurate AFM image. With the traditional characterisers with special microstructures it is difficult to accurately determine tip shape because of their dimensional uncertainty. Combined with tip blind reconstruction algorithms, some nanomaterials with arrayed nanostructures are often used to estimate the AFM tip morphology. However, the blind reconstruction algorithms are sensitive to image noise. To solve such problems, the porous anodic alumina (PAA) film with well-ordered porous nanostructures was fabricated and used as a new tip characteriser. By setting the appropriate scanning routine and scanning mode, the two-dimensional and three-dimensional tip morphology was accurately calculated. PAA film as the AFM tip characteriser can effectively reduce the influence of AFM image noise and sample-dimensional uncertainty of tip blind estimation results, especially avoiding tip wear and damage.
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