| Autor: |
Beck, Megan E., Shylendra, Ahish, Sangwan, Vinod K., Guo, Silu, Gaviria Rojas, William A., Yoo, Hocheon, Bergeron, Hadallia, Su, Katherine, Trivedi, Amit R., Hersam, Mark C. |
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| Zdroj: |
Nature Communications; 3/26/2020, Vol. 11 Issue 1, p1-8, 8p |
| Abstrakt: |
Spiking neural networks exploit spatiotemporal processing, spiking sparsity, and high interneuron bandwidth to maximize the energy efficiency of neuromorphic computing. While conventional silicon-based technology can be used in this context, the resulting neuron-synapse circuits require multiple transistors and complicated layouts that limit integration density. Here, we demonstrate unprecedented electrostatic control of dual-gated Gaussian heterojunction transistors for simplified spiking neuron implementation. These devices employ wafer-scale mixed-dimensional van der Waals heterojunctions consisting of chemical vapor deposited monolayer molybdenum disulfide and solution-processed semiconducting single-walled carbon nanotubes to emulate the spike-generating ion channels in biological neurons. Circuits based on these dual-gated Gaussian devices enable a variety of biological spiking responses including phasic spiking, delayed spiking, and tonic bursting. In addition to neuromorphic computing, the tunable Gaussian response has significant implications for a range of other applications including telecommunications, computer vision, and natural language processing. Designing high performance, scalable, and energy efficient spiking neural networks remains a challenge. Here, the authors utilize mixed-dimensional dual-gated Gaussian heterojunction transistors from single-walled carbon nanotubes and monolayer MoS2 to realize simplified spiking neuron circuits. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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