Fast data sorting with modified principal component analysis to distinguish unique single molecular break junction trajectories

Abstract

A simple and fast analysis method to sort large data sets into groups with shared distinguishing characteristics is described, and applied to single molecular break junction conductance versus electrode displacement data. The method, based on principal component analysis, successfully sorted data sets based on the projection of the data onto the first or second principal component of the correlation matrix without the need to assert any specific hypothesis about the expected features within the data. This was an improvement on the current correlation matrix analysis approach because it sorted data automatically, making it more objective and less time consuming, and our method is applicable to a wide range of multivariate data sets. Here the method was demonstrated on two systems. First, it was demonstrated on mixtures of two molecules with identical anchor groups, similar lengths, but either a $\pi$ (high conductance) or $\sigma$ (low conductance) bridge. The mixed data was automatically sorted into two groups containing one molecule or the other. Second, it was demonstrated on break junction data measured with the $\pi$ bridged molecule alone. Again the method distinguished between two groups. These groups were tentatively assigned to different geometries of the molecule in the junction.

Maths in SM; NMR in SM

References in corpus (3)

• Formation and Evolution of Single Molecule Junctions
• Regular atomic narrowing of Ni, Fe and V nanowires resolved by 2D correlation analysis
• Temporal correlations and structural memory effects in break junction measurements

Cited by in corpus (7)

• Benchmark and application of unsupervised classification approaches for univariate data
• Unsupervised Segmentation-Based Machine Learning as an Advanced Analysis Tool for Single Molecule Break Junction Data
• Unsupervised feature recognition in single molecule break junction data
• Principal Component Analysis of collective flow in Relativistic Heavy-Ion Collisions
• Redox-controlled conductance of polyoxometalate molecular junctions
• Grid-Based Correlation Analysis to Identify Rare Quantum Transport Behaviors
• A multivariate approach to single-molecule thermopower and electric conductance measurements