Electrostatic Discovery Atomic Force Microscopy

While offering high resolution atomic and electronic structure, scanning probe microscopy techniques have found greater challenges in providing reliable electrostatic characterization on the same scale. In this work, we offer electrostatic discovery atomic force microscopy, a machine learning based method which provides immediate maps of the electrostatic potential directly from atomic force microscopy images with functionalized tips. We apply this to characterize the electrostatic properties of a variety of molecular systems and compare directly to reference simulations, demonstrating good agreement. This approach offers reliable atomic scale electrostatic maps on any system with minimal computational overhead.

Automated summary

In this study, a machine learning based atomic force microscopy method is proposed to provide immediate maps of electrostatic potential directly from images, offering reliable atomic scale electrostatic characterization with minimal computational overhead.