Electrolyte-gated transistors with good retention for neuromorphic computing
Electrolyte-gated transistors (EGTs) provide prominent analog switching performance for neuromorphic computing. However, suffering from self-discharging nature, the retention performance greatly hampers their practical applications. In this Letter, we realize a significant improvement in EGT retenti...
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Veröffentlicht in: | Applied physics letters 2022-01, Vol.120 (2) |
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Sprache: | eng |
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Zusammenfassung: | Electrolyte-gated transistors (EGTs) provide prominent analog switching performance for neuromorphic computing. However, suffering from self-discharging nature, the retention performance greatly hampers their practical applications. In this Letter, we realize a significant improvement in EGT retention by inserting a SiO2 layer between the gate electrode and electrolyte. The dynamic process behind the improvement is interpreted by an assumptive leakage-assisted electrochemical mechanism. In addition to improved retention, analog switching with a large dynamic range, superior linearity and symmetry, and low variation has been achieved using identical voltage pulses. Based on the experimental data, a nearly ideal recognition accuracy of 98% has been demonstrated by simulations using the handwritten digit data sets. The obtained results pave a way for employing EGT in future neuromorphic computing. |
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ISSN: | 0003-6951 1077-3118 |
DOI: | 10.1063/5.0082061 |