Lemmer, M;
Inkpen, MS;
Kornysheva, K;
Long, NJ;
Albrecht, T;
(2016)
Unsupervised vector-based classification of single-molecule charge transport data.
Nature Communications
, 7
, Article 12922. 10.1038/ncomms12922.
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Abstract
The stochastic nature of single-molecule charge transport measurements requires collection of large data sets to capture the full complexity of a molecular system. Data analysis is then guided by certain expectations, for example, a plateau feature in the tunnelling current distance trace, and the molecular conductance extracted from suitable histogram analysis. However, differences in molecular conformation or electrode contact geometry, the number of molecules in the junction or dynamic effects may lead to very different molecular signatures. Since their manifestation is a priori unknown, an unsupervised classification algorithm, making no prior assumptions regarding the data is clearly desirable. Here we present such an approach based on multivariate pattern analysis and apply it to simulated and experimental single-molecule charge transport data. We demonstrate how different event shapes are clearly separated using this algorithm and how statistics about different event classes can be extracted, when conventional methods of analysis fail.
| Type: | Article |
|---|---|
| Title: | Unsupervised vector-based classification of single-molecule charge transport data |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/ncomms12922 |
| Publisher version: | http://dx.doi.org/10.1038/ncomms12922 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Science & Technology, Multidisciplinary Sciences, Science & Technology - Other Topics, TRANSITION-METAL-COMPLEXES, CONDUCTANCE HISTOGRAMS, JUNCTION CONDUCTANCE, BREAK-JUNCTION, ELECTRON-TRANSPORT, WIRES, LEVEL, GOLD, GEOMETRIES, MECHANISM |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/1528205 |
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