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Description:

Molecule-based reservoir computing (RC) is promising for achieving low power consumption neuromorphic computing, although information-processing capability of small numbers of molecules is not clear. Here, we report a few- and single-molecule RC that employs the molecular vibration dynamics in the para-mercaptobenzoic acid (pMBA) detected by surface enhanced Raman scattering (SERS) with tungsten oxide nanorod/silver nanoparticles. The Raman signals of the pMBA molecules, adsorbed at the SERS active site of the nanorod, were reversibly perturbated by the application of voltage-induced local pH changes near the molecules, and then used to perform time-series analysis tasks. Despite the small number of molecules employed, our system achieved good performance, including >95% accuracy in various nonlinear waveform transformations, 94.3% accuracy in solving a second-order nonlinear dynamic system, and a prediction error of 25.0 mg/dl in a 15-minute ahead blood glucose level prediction. Our work provides a concept of few-molecular computing with practical computation capabilities.

Rights:

• Creative Commons BY-NC Attribution-NonCommercial 4.0 International
  

Keyword: Reservoir computing, Neuromorphic computing, Surface enhanced Raman scattering, Single-molecule reservoir computing

Date published: 2024-02-28

Publisher: American Association for the Advancement of Science (AAAS)

Journal:

• Science Advances (ISSN: 23752548) vol. 10 issue. 9 eadk6438

Funding:

Manuscript type: Publisher's version (Version of record)

MDR DOI:

First published URL: https://doi.org/10.1126/sciadv.adk6438

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Updated at: 2024-08-05 12:30:19 +0900

Published on MDR: 2024-08-05 12:30:19 +0900