A retrainable neuromorphic biosensor for on-chip learning and classification-Reference-Cited by-同舟云学术

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A retrainable neuromorphic biosensor for on-chip learning and classification

Published:2023-09-14 Issue:10 Volume:6 Page:765-770
ISSN:2520-1131
Container-title:Nature Electronics
language:en
Short-container-title:Nat Electron

Author:

van Doremaele E. R. W.^ORCID,Ji X.^ORCID,Rivnay J.^ORCID,van de Burgt Y.^ORCID

Funder

EC | Horizon 2020 Framework Programme

Alfred P. Sloan Foundation

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Instrumentation,Electronic, Optical and Magnetic Materials

Link

https://www.nature.com/articles/s41928-023-01020-z.pdf

Reference35 articles.

1. van de Burgt, Y., Melianas, A., Keene, S. T., Malliaras, G. & Salleo, A. Organic electronics for neuromorphic computing. Nat. Electron. 1, 386–397 (2018).

2. Gkoupidenis, P., Schaefer, N., Garlan, B. & Malliaras, G. G. Neuromorphic functions in PEDOT:PSS organic electrochemical transistors. Adv. Mater. 27, 7176–7180 (2015).

3. van de Burgt, Y. & Gkoupidenis, P. Organic materials and devices for brain-inspired computing: from artificial implementation to biophysical realism. MRS Bull. 45, 631–640 (2020).

4. Fuller, E. J. et al. Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing. Science 364, 570–574 (2019).

5. Xia, Q. & Yang, J. J. Memristive crossbar arrays for brain-inspired computing. Nat. Mater. 18, 309–323 (2019).

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