Scanning
probe microscopies and spectroscopies enable investigation
of surfaces and even buried interfaces down to the scale of chemical-bonding
interactions, and this capability has been enhanced with the support
of computational algorithms for data acquisition and image processing
to explore physical, chemical, and biological phenomena. Here, we
describe how scanning probe techniques have been enhanced by some
of these recent algorithmic improvements. One improvement to the data
acquisition algorithm is to advance beyond a simple rastering framework
by using spirals at constant angular velocity and then switching to
constant linear velocity, which limits the piezo creep and hysteresis
issues seen in traditional acquisition methods. One can also use image-processing
techniques to model the distortions that appear from tip motion effects
and to make corrections to these images. Another image-processing
algorithm we discuss enables researchers to segment images by domains
and subdomains, thereby highlighting reactive and interesting disordered
sites at domain boundaries. Lastly, we discuss algorithms used to
examine the dipole direction of individual molecules and surface domains,
hydrogen-bonding interactions, and molecular tilt. The computational
algorithms used for scanning probe techniques are still improving
rapidly and are incorporating machine learning at the next level of
iteration. That said, the algorithms are not yet able to perform live
adjustments during data recording that could enhance the microscopy
and spectroscopic imaging methods significantly.