An Ultralow Power Li x TiO 2 ‐Based Synaptic Transistor for Scalable Neuromorphic Computing

Artificial synapses based on electrochemical synaptic transistors (SynTs) have attracted tremendous attention toward massive parallel computing operations. However, most SynTs still suffer from downscaling limitations and high energy consumption. To overcome such drawbacks, a complementary metal–oxi...

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Veröffentlicht in:Advanced electronic materials 2022-12, Vol.8 (12)
Hauptverfasser: Nguyen, Ngoc‐Anh, Schneegans, Olivier, Salot, Raphaël, Lamy, Yann, Giapintzakis, John, Mai, Van Huy, Oukassi, Sami
Format: Artikel
Sprache:eng
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Zusammenfassung:Artificial synapses based on electrochemical synaptic transistors (SynTs) have attracted tremendous attention toward massive parallel computing operations. However, most SynTs still suffer from downscaling limitations and high energy consumption. To overcome such drawbacks, a complementary metal–oxide–semiconductor (CMOS) back‐end‐of‐line compatible solid‐state SynT is presented, which includes an ultrathin (10 nm thick) quasiamorphous Li x TiO 2 channel. A nonvolatile conductance modulation (10 5 weight updates) and recognition accuracy (>95% on the MNIST data test using crossbar simulations). Furthermore, a comprehensive electrochemical study allows deeper insight into the specific pseudocapacitive mechanism at the origin of conductance modulation. These results underline the high potential of Li x TiO 2 ‐based SynTs for energy‐efficient neuromorphic applications.
ISSN:2199-160X
2199-160X
DOI:10.1002/aelm.202200607