“Twisting” the data: a universal machine-learning approach to classify single-molecule curves and beyond
We present a new automated supervised procedure to classify conductance-voltage ( G ( V )) curves and conductance-distance ( G ( z )) traces from single-molecule junctions with high confidence. It is based on representing the data as a spiral image.
Authors
- Edmund Leary (ORCID: https://orcid.org/0000-0001-7541-5997)
- Mauricio González (ORCID: https://orcid.org/0000-0001-9021-451X)
- Pablo M. Olmos (ORCID: https://orcid.org/0000-0003-4276-5178)
- Linda A. Zotti (ORCID: https://orcid.org/0000-0002-5292-6759)
- Carlos Roldán-Piñero (ORCID: https://orcid.org/0009-0009-7491-4634)
Institutions
- Madrid Institute for Advanced Studies (ES)
- Universidad Carlos III de Madrid (ES)
- Universidad Autónoma de Madrid (ES)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5dd00207a
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- University of Oxford
- Agencia Estatal de Investigación