High-Throughput Preparation of Supramolecular Nanostructures on Metal Surfaces

Abstract

One of the contemporary challenges in materials science lies in the rapid materials screening and discovery. Experimental sample libraries can be generated by high-throughput parallel synthesis to map the composition space for rapid material discoveries. Molecular self-assembly on surfaces has proved a useful way to construct nanostructures with interesting topologies or properties. Despite the strong dependence of molecular stoichiometry on the structures, high-throughput preparations of supramolecular surface nanostructures have been far less explored. Here, by integrating a physical mask into the standard ultra-high-vacuum (UHV) molecular preparation system we show a high-throughput approach for preparing supramolecular nanostructures of continuous composition spreads on metal surfaces. The spatially addressable sample libraries of supramolecular self-assemblies are characterized by high-resolution scanning probe microscopy. We could explore different binary nanostructures of varying molecular ratios on one single substrate. Moreover, we use the minimum spanning tree approach to qualitatively and quantitatively study the structural properties of the formed nanostructures. This high-throughput approach may accelerate the screening and exploration of surface-supported, lowdimensional nanostructures not limited to supramolecular interactions.

Heteroatom-Doped [4]Triangulene: Facile Synthesis and Two-Dimensional On-Surface Self-Assemblies

“…27 We then performed the minimum spanning tree (MST) analysis of the STM image of 1a on Ag(111) surface to quantify the degrees of disorder of the 2D self-assembled structures (Figure 5a). [48][49][50] Based on the MST image, a Voronoi tessellation can be constructed, representing molecules with various highly ordered hexagonal cells (Figure 5b). Besides, the mean normalized distance (μ) of MST image edges (green lines) is calculated as ~1.045 with a standard deviation (σ) of ~0.021 (Figure 5c).…”

Coronene guest molecule selectivity in host templates formed by hydrogen bonding and van der Waals forces at liquid/solid interfaces

“…Surface supramolecular chemistry has been widely studied recently. 1,2 Molecules self-assemble on a surface to form longrange, ordered, and reversible assembly structures through non-covalent interactions, [3][4][5] which is conducive to building nanostructures with clear physical and chemical properties through a ''bottom-up'' method. 6,7 These structures have been widely used in organic solar cells, 8 superconducting materials, 9 fluorescent materials, 10 and other fields.…”

Predicting Molecular Self-Assembly on Metal Surfaces Using Graph Neural Networks Based on Experimental Data Sets

“…Due to its widespread importance, molecular self-assembly has received vast attention in the past decades. Molecular self-assemblies at solid surfaces could produce large-scale surface nanostructures. − And properties of molecular thin films, such as the optical absorbance and electrical conductivity, are dependent on the structures of molecules upon adsorption on a substrate. − Generally speaking, the self-assembled patterns are decided by the intrinsic properties of the molecules and environments, i.e., the balance of the adsorbate–adsorbate and adsorbate–surface interactions for molecular self-assemblies on surfaces. − Due to the complexity that arises from different aspects including the different functional groups of molecules, the size/shape of the molecular backbone, their adsorption geometries, as well as the different metal substrates, predicting the self-assembled structures remains an enormous challenge. − Meanwhile, constructing surface-supported supramolecular nanostructures through traditional trial-and-error methods relies on repeated preparations and experimental characterizations with advanced characterization tools, such as scanning probe microscopy (SPM), − which are typically time-consuming and costly.…”