Performance improvement of single-molecule sensors through deep learning-based decoding of tunneling signals enables sub-attomolar sensitivity
) with seconds-scale response time (26 s). Validated across diverse analytes, our strategy consistently enhances sensitivity, confirming its generalizability. This synergistic strategy establishes a paradigm for single-molecule chemical sensing both in methodological and performance dimensions. By transforming fleeting interactions into actionable detection, the approach could provide a robust and broadly applicable framework for environmental monitoring and molecular diagnostic.
Authors
- Chuancheng Jia (ORCID: https://orcid.org/0000-0002-1513-8497)
- B. X. Gao (ORCID: https://orcid.org/0009-0001-3064-9666)
- Xijuan Wang (ORCID: https://orcid.org/0000-0002-2409-115X)
- Sàisài Yuán (ORCID: https://orcid.org/0000-0001-9226-3753)
- Chuanxiang Chen (ORCID: https://orcid.org/0000-0001-9137-8356)
- Ping Duan (ORCID: https://orcid.org/0000-0003-0695-7498)
- Manqiu Ma
- Zhichao Pan (ORCID: https://orcid.org/0000-0002-2858-0348)
- Yuxiao Chen
- Ziyang Wang (ORCID: https://orcid.org/0009-0000-5811-6493)
- Xinhuan Zhang
- Yiming Chen
Institutions
- Nankai University (CN)
- Jiangsu University of Science and Technology (CN)
- Guilin University of Electronic Technology (CN)
Publication Details
- Journal
- Nature Communications
- Published
- 2026-04-21
- DOI
- https://doi.org/10.1038/s41467-026-72249-3
- Primary Topic
- Molecular Junctions and Nanostructures
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Fujian Institute of Research on the Structure of Matter
- Key Programme