journal article·2022-08-23

High-Throughput Preparation of Supramolecular Nanostructures on Metal Surfaces

Jiayi Lu, Hao Jiang, Yuyi Yan, Zhiwen Zhu, Fengru Zheng, Qiang Sun

ACS Nano· Volume 16· Issue 8
Publisher page

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, low-dimensional nanostructures not limited to supramolecular interactions.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Surface Chemistry and Catalysis · Machine Learning in Materials Science · Surface and Thin Film Phenomena

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Materials Genome Institute, Shanghai University, 200444 Shanghai, China

Funding

National Natural Science Foundation of China

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