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.

Two-Dimensional Metal-Organic Framework on Superconducting NbSe2.

The combination of two-dimensional (2D) materials into vertical heterostructures has emerged as a promising path to designer quantum materials with exotic properties. Here, we extend this concept from inorganic 2D materials to 2D metal-organic frameworks (MOFs) that offer additional flexibility in realizing designer heterostructures. We successfully fabricate a monolayer 2D Cu-dicyanoanthracene MOF on a 2D van der Waals NbSe2 superconducting substrate. The structural and electronic properties of two different phases of the 2D MOF are characterized by low-temperature scanning tunneling microscopy (STM) and spectroscopy (STS), complemented by density-functional theory (DFT) calculations. These experiments allow us to follow the formation of the kagome band structure from Star of David-shaped building blocks. This work extends the synthesis and electronic tunability of 2D MOFs beyond the electronically less relevant metal and semiconducting surfaces to superconducting substrates, which are needed for the development of emerging quantum materials such as topological superconductors.

Automated structure discovery in atomic force microscopy.

Atomic force microscopy (AFM) with molecule-functionalized tips has emerged as the primary experimental technique for probing the atomic structure of organic molecules on surfaces. Most experiments have been limited to nearly planar aromatic molecules due to difficulties with interpretation of highly distorted AFM images originating from nonplanar molecules. Here, we develop a deep learning infrastructure that matches a set of AFM images with a unique descriptor characterizing the molecular configuration, allowing us to predict the molecular structure directly. We apply this methodology to resolve several distinct adsorption configurations of 1S-camphor on Cu(111) based on low-temperature AFM measurements. This approach will open the door to applying high-resolution AFM to a large variety of systems, for which routine atomic and chemical structural resolution on the level of individual objects/molecules would be a major breakthrough.

On-Surface Assembly of Au-Dicyanoanthracene Coordination Structures on Au(111).

On-surface metal-organic coordination provides a promising way for synthesizing different two-dimensional lattice structures that have been predicted to possess exotic electronic properties. Using scanning tunneling microscopy (STM) and spectroscopy (STS), we studied the supramolecular self-assembly of 9,10-dicyanoanthracene (DCA) molecules on the Au(111) surface. Close-packed islands of DCA molecules and Au-DCA metal-organic coordination structures coexist on the Au(111) surface. Ordered DCA3 Au2 metal-organic networks have a structure combining a honeycomb lattice of Au atoms with a kagome lattice of DCA molecules. Low-temperature STS experiments demonstrate the presence of a delocalized electronic state containing contributions from both the gold atom states and the lowest unoccupied molecular orbital of the DCA molecules. These findings are important for the future search of topological phases in metal-organic networks combining honeycomb and kagome lattices with strong spin-orbit coupling in heavy metal atoms.