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.
Original languageEnglish
Pages (from-to)89-97
Number of pages9
JournalACS Nano
Issue number1
Early online date22 Nov 2021
Publication statusPublished - 25 Jan 2022
MoE publication typeA1 Journal article-refereed


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