Cucurbituril mediated single molecule detection and identification via recognition tunneling
Creators
- 1. The State Key laboratory of Refractories and Metallurgy, Wuhan University of Science and Technology, Wuhan 430081 (China)
- 2. School of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan 430081 (China)
- 3. Biodesign Institute, Arizona State University, Tempe, AZ 85287 (United States)
- 4. Department of Physics and Biomolecular Science Institute, Florida International University, Miami, FL 33199 (United States)
Description
Recognition tunneling (RT) is an emerging technique for investigating single molecules in a tunnel junction. We have previously demonstrated its capability of single molecule detection and identification, as well as probing the dynamics of intermolecular bonding at the single molecule level. Here by introducing cucurbituril as a new class of recognition molecule, we demonstrate a powerful platform for electronically investigating the host–guest chemistry at single molecule level. In this report, we first investigated the single molecule electrical properties of cucurbituril in a tunnel junction. Then we studied two model guest molecules, aminoferrocene and amantadine, which were encapsulated by cucurbituril. Small differences in conductance and lifetime can be recognized between the host–guest complexes with the inclusion of different guest molecules. By using a machine learning algorithm to classify the RT signals in a hyper dimensional space, the accuracy of guest molecule recognition can be significantly improved, suggesting the possibility of using cucurbituril molecule for single molecule identification. This work enables a new class of recognition molecule for RT technique and opens the door for detecting a vast variety of small molecules by electrical measurements. (paper)
Availability note (English)
Available from http://dx.doi.org/10.1088/1361-6528/aacb63Additional details
Identifiers
Publishing Information
- Journal Title
- Nanotechnology (Print)
- Journal Volume
- 29
- Journal Issue
- 36
- Journal Page Range
- [10 p.]
- ISSN
- 0957-4484
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 51040906
- Subject category
- S75: CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; S37: INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY;
- Descriptors DEI
- ALGORITHMS; CHEMICAL BONDS; CHEMISTRY; E-LEARNING; ELECTRICAL PROPERTIES; MOLECULES; PROBES; SIGNALS; TUNNEL EFFECT; TUNNEL JUNCTIONS
- Descriptors DEC
- EDUCATION; LEARNING; MATHEMATICAL LOGIC; PHYSICAL PROPERTIES; TRAINING