RESUMEN
Enantiospecific effects play an uprising role in chemistry and technical applications. Chiral molecular networks formed by self-assembly processes at surfaces can be imaged by scanning probe microscopy (SPM). Low contrast and high noise in the topography map often interfere with the automatic image analysis using classical methods. The long SPM image acquisition times restrain Artificial Intelligence-based methods requiring large training sets, leaving only tedious manual work, inducing human-dependent errors and biased labeling. By generating realistic looking synthetic images, the acquisition of real datasets is avoided. Two state-of-the-art object detection architectures are trained to localize and classify chiral unit-cells in a regular molecular chiral network formed by self-assembly of linear molecular bricks. The comparison of different architectures and datasets demonstrates that the training on purely synthetic data outperforms models trained using augmented datasets. A Faster R-CNN model trained solely on synthetic data achieved an excellent mean average precision of 99% on real data. Hence this approach and the transfer to real data show high success, also highlighting the high robustness against experimental noise and different zoom levels across the full experimentally reasonable parameter range. The generalizability of this idea is demonstrated by achieving equally high performance on a different structure, too.
RESUMEN
DNA origami is a flexible platform for the precise organization of nano-objects, enabling numerous applications from biomedicine to nano-photonics. Its huge potential stems from its high flexibility that allows customized structures to meet specific requirements. The ability to generate diverse final structures from a common base by folding significantly enhances design variety and is regularly occurring in liquid. This study describes a novel approach that combines top-down lithography with bottom-up DNA origami techniques to control folding of the DNA origami with the adsorption on pre-patterned surfaces. Using this approach, tunable plasmonic dimer nano-arrays are fabricated on a silicon surface. This involves employing electron beam lithography to create adsorption sites on the surface and utilizing self-organized adsorption of DNA origami functionalized with two gold nanoparticles (AuNPs). The desired folding of the DNA origami helices can be controlled by the size and shape of the adsorption sites. This approach can for example be used to tune the center-to-center distance of the AuNPs dimers on the origami template. To demonstrate this technique's efficiency, the Raman signal of dye molecules (carboxy tetramethylrhodamine, TAMRA) coated on the AuNPs surface are investigated. These findings highlight the potential of tunable DNA origami-based plasmonic nanostructures for many applications.