Abstract
Flexible and transparent artificial synapses with extremely low energy consumption have potential for use in brain-like neuromorphic electronics. However, most of the transparent materials for flexible memristive artificial synapses were reported to show picojoule-scale high energy consumption with kiloohm-scale low resistance, which limits the scalability for parallel operation. Here, we report on a flexible memristive artificial synapse based on Cs3Cu2I5 with energy consumption as low as 10.48 aJ (= 10.48 × 10-18 J) μm-2 and resistance as high as 243 MΩ for writing pulses. Interface-type resistive switching at the Schottky junction between p-type Cu3Cs2I5 and Au is verified, where migration of iodide vacancies and asymmetric carrier transport owing to the effective hole mass is three times heavier than effective electron mass are found to play critical roles in controlling the conductance, leading to high resistance. There was little difference in synaptic weight updates with high linearity and 250 states before and after bending the flexible device. Moreover, the MNIST-based recognition rate of over 90% is maintained upon bending, indicative of a promising candidate for highly efficient flexible artificial synapses.
Original language | English |
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Pages (from-to) | 987-997 |
Number of pages | 11 |
Journal | Nanoscale Horizons |
Volume | 6 |
Issue number | 12 |
DOIs | |
Publication status | Published - 2021 Dec |
Bibliographical note
Funding Information:This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Ministry of Science, ICT Future Planning (MSIP) of Korea under contracts NRF-2016M3D1A1027663 and NRF-2016M3D1A1027664 (Future Materials Discovery Program). This work was also supported by Samsung Electronics Co., Ltd (IO201219-07994-01). Y. K. J. and A. W. are grateful to the UK Materials and Molecular Modelling Hub for computational resources, which is partially funded by EPSRC (EP/P020194/1).
Publisher Copyright:
© 2021 The Royal Society of Chemistry.
All Science Journal Classification (ASJC) codes
- Materials Science(all)