Abstract
Two-dimensional materials are emerging as potential solutions for high-density nonvolatile memory and efficient neuromorphic computing. However, integrating multidimensional memory and an ideal linear weight updating synapse in a simple device configuration to achieve versatile biomimetic neuromorphic systems remains challenging. Here, we introduce a wrinkled rhenium disulfide (ReS2) transistor, where the wrinkled structure facilitates the carrier trapping/detrapping at the dielectric interface, thus enabling the fusion of nonvolatile memory and both electronic and optoelectronic synaptic functionalities. As a nonvolatile memory, anisotropic wrinkled ReS2 can yield three distinct sets of data across three crystal orientations under identical programming operations. Each set demonstrates exceptional retention and endurance properties. As a neuromorphic synapse, it realizes the linear and symmetric updates of conductance states up to 9 bits and 8 bits, the ultra-low-energy consumption of 75 fJ and 2.5 pJ under the electrical and optical stimuli, respectively. The artificial neural network (ANN) based on electronic synapses gives a superior recognition accuracy of 92.9% for the original handwritten digits. The anisotropic synaptic responses and multiwavelength sensitivities of optoelectronic synapses enable them to execute advanced memory and recognition functions for complex images that encompass a variety of pattern features or color information. This underscores its substantial potential for integration into efficient biomimetic visual systems.
| Original language | English |
|---|---|
| Pages (from-to) | 30871-30883 |
| Number of pages | 13 |
| Journal | ACS Nano |
| Volume | 18 |
| Issue number | 44 |
| DOIs | |
| State | Published - 5 Nov 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- artificial visual system
- neuromorphic synapse
- nonvolatile memory
- two-dimensional materials
- wrinkled structure
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