This improved SNR leads to a commensurate increase in the resolving power of the STM. However, if all the hundred images are averaged then we would expect a tenfold improvement in the signal to noise ratio (SNR) as the random noise diminishes with the square root of the number of averaged images.
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To date, this has not been viewed as a particularly significant advantage because operator practice is such that only the best one of these hundred images will be used and the others discarded. In effect, this means that for the time taken to acquire one nc-AFM image it is possible to acquire around a hundred STM images. The advantage, however, that the STM still has over nc-AFM is that the scan speed is typically around two orders of magnitude faster. Where AFM was initially the poor cousin to the atomic resolution STM, it is now possible to take non-contact AFM (nc-AFM) images with intramolecular resolution. These incremental gains stand in stark contrast to the advances made with the atomic force microscope (AFM). Only small advances have been achieved through low noise electronics, enhanced vibration damping, and low-temperature operation. The resolution of the scanning tunneling microscope (STM) has barely improved since its inception. Our new approach to STM imaging will allow a wealth of structural and electronic information from surfaces to be extracted that was previously buried in noise. Last, we demonstrate the automated classification of the two chiral variants of the surface unit cells of the (4 × 4) reconstructed SrTiO 3(111) surface. Next, we demonstrate that images with sub-picometre height precision can be routinely obtained and show this for a monolayer of Ti 2O 3 on Au(111). First, we show a sixfold enhancement of the SNR of the Si(111)-(7 × 7) reconstruction. Here, we demonstrate how a significant improvement in the resolving power of the STM can be achieved through automated distortion correction and multi-frame averaging (MFA) and we demonstrate the broad utility of this approach with three examples. However, for serial-acquired 2D STM images the nature and variety of image distortions can severely complicate accurate registration.
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Data averaging can be routinely performed for 1D spectra, where their alignment is straightforward.
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This is in contrast to most other disciplines where the signal to noise ratio (SNR) of a data set is improved by taking repeated measurements and averaging them. The usual way to present images from a scanning tunneling microscope (STM) is to take multiple images of the same area, to then manually select the one that appears to be of the highest quality, and then to discard the other almost identical images.