Sparse-coding denoising applied to reversible conformational switching of a porphyrin self-assembled monolayer induced by scanning tunnelling microscopy.

Scanning tunnelling microscopy (STM) was used to induce conformational molecular switching on a self-assembled monolayer of zinc-octaethylporphyrin on a graphite/tetradecane interface at room temperature. A reversible conformational change controlled by applying a tip voltage was observed. Consecutive STM images acquired at alternating tip voltages showed that at 0.4 V the porphyrin monolayer presents a molecular arrangement formed by alternate rows with two different types of structural conformations and when the potential is increased to 0.7 V the monolayer presents only one type of conformation. In this paper, we characterize these porphyrin conformational dynamics by analyzing the STM images, which were improved for better quality and interpretation by means of a denoising algorithm, adapted to process STM images from state of the art image processing and analysis methods. STM remains the best technique to 'see' and to manipulate the matter at atomic scale. A very sharp tip a few angstroms of the surface can provide images of molecules and atoms with a powerful resolution. However, these images are strongly affected by noise which is necessary to correct and eliminate. This paper is about new computational tools specifically developed to denoise the images acquired with STM. The new algorithms were tested in STM images, obtained at room temperature, of porphyrin monolayer which presents reversible conformational change in function of the tip bias voltage. Images with high resolution, acquired in real time, show that the porphyrins have different molecular arrangements whether the tip voltage is 0.4 V or 0.7 V.