Mote2-based low energy consumption artificial synapse for neuromorphic behavior and decimal arithmetic
Two-dimensional material-based memristors have shown attractive research prospects as brain-like devices for neuromorphic computing. Among them, transition metal dichalcogenides–based memristors have proved to be one of the most promising competitors. In this work, a two-dimensional memristor based...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/108904/1/MoTe2-based%20low%20energy.pdf http://psasir.upm.edu.my/id/eprint/108904/ https://linkinghub.elsevier.com/retrieve/pii/S2468519422004979 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Two-dimensional material-based memristors have shown attractive research prospects as brain-like devices for neuromorphic computing. Among them, transition metal dichalcogenides–based memristors have proved to be one of the most promising competitors. In this work, a two-dimensional memristor based on MoTe2 nanosheets was fabricated and demonstrated. The experimental results illustrate that the two-terminal synaptic based on the Ag/MoTe2/ITO structure exhibits stable bipolar and non-volatile resistive switching characteristics attributed to the controllable formation and rupturing of silver conductive filaments. The device can be successively modulated by a pulse train with a minimum pulse width of 40 ns. More interestingly, the energy consumption of the device to complete one write event is only 74.2 pJ. In addition, biological synaptic behaviors, such as excitatory postsynaptic current gain properties, long-term potentiation (LTP)/long-term depression, spike-timing-dependent- plasticity, short-term plasticity, long-term potentiation (LTP), paired-pulse facilitation, post-tetanic potentiation, and learning-experimental behaviors were mimicked faithfully. Finally, the decimal arithmetic application was introduced to the device, and it is confirmed that addition and multiplication functions can be performed. Therefore, the artificial synapse based on MoTe2 nanosheets not only exhibits the stable non-volatile resistive switching behavior but also facilitates the development of low-energy consumption neuromorphic computing chips based on transition metal dichalcogenides. |
|---|