Abstract
The scanning tunneling microscope-based break-junction (STM-BJ) technique is the most common method used to study the electronic properties of single-molecule junctions. It relies on repeatedly forming and rupturing a Au contact in an environment of the target molecules. The probability of junction formation is typically very high (∼70-95%), prompting questions relating to how the nanoscale structure of the Au electrode before the metal point contact ruptures alters junction formation. Here we analyze conductance traces measured with the STM-BJ setup by combining correlation analysis and multiple machine learning tools, including gradient-boosted trees and neural networks. We show that two key features describing the Au-Au contact prior to rupture determine the extent of contact relaxation (snapback) and the probability of junction formation. Importantly, our data strongly indicate that molecular junctions are formed prior to the rupture of the Au-Au contact, explaining the high probability of junction formation observed in room-temperature solution measurements.
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