N-ti-sb-te-based synaptic biomimetic devices for use in artificial neural networks

A synaptic device and a synaptic technology, applied in biological neural network models, electrical components, physical realization, etc., can solve problems such as poor linear change, low bit resolution, and large difference between high and low resistance, and achieve excellent electrical properties Effect

Active Publication Date: 2022-07-29
HANGZHOU DIANZI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the factors that limit the performance of artificial neural networks using non-volatile memory are the poor linear change of the resistance of the synaptic device to the number of pulses, the low bit resolution, and the large or small difference between high and low resistance.

Method used

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  • N-ti-sb-te-based synaptic biomimetic devices for use in artificial neural networks
  • N-ti-sb-te-based synaptic biomimetic devices for use in artificial neural networks
  • N-ti-sb-te-based synaptic biomimetic devices for use in artificial neural networks

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] Example 1: The electrodes in the medium were prepared using a standard 0.13-micron CMOS process, with a diameter of 190 nanometers. The storage medium layer is deposited by physical vapor deposition with a thickness of 120 nanometers, and the N above the electrode is prepared through processes such as glue coating, photolithography, and etching. 5 (TiSb 5 Te 7.5 ) 95 material pattern so that the N above each bottom electrode 5 (TiSb 5 Te 7.5 ) 95 The materials are electrically insulated from each other. The top electrode titanium nitride TiN was deposited by physical vapor deposition with a thickness of 20 nanometers, and N was prepared by glue coating, photolithography, etching and other processes. 5 (TiSb 5 Te 7.5 ) 95 Above the TiN electrode material pattern so that each N 5 (TiSb 5 Te 7.5 ) 95 The top electrode materials above are electrically insulated from each other. get based on N 5 (TiSb 5 Te 7.5 ) 95 The T-shaped structure synaptic bionic un...

Embodiment 2

[0046] Example 2: The electrodes in the medium were prepared using a standard 0.13-micron CMOS process, with a diameter of 190 nanometers. The storage medium layer is deposited by chemical vapor deposition with a thickness of 200 nanometers, and the N above the electrode is prepared through processes such as glue coating, photolithography, and etching. 0.1 (TiSb 40 Te 10 ) 99.9 material pattern so that the N above each bottom electrode 0.1 (TiSb 40 Te 10 ) 99.9 The materials are electrically insulated from each other. The top electrode titanium nitride TiN was deposited by physical vapor deposition with a thickness of 200 nanometers, and N was prepared by coating, photolithography, etching and other processes. 0.1 (TiSb 40 Te 10 ) 99.9 Above the TiN electrode material pattern so that each N 0.1 (TiSb 40 Te 10 ) 99.9 The top electrode materials above are electrically insulated from each other. get based on N 0.1 (TiSb 40 Te 10 ) 99.9 The T-shaped structure sy...

Embodiment 3

[0047] Example 3: Using standard CMOS technology to prepare electrodes in the medium, with a diameter of 10 nanometers. The storage medium layer is deposited by chemical vapor deposition with a thickness of 50 nanometers, and the N above the electrode is prepared through processes such as glue coating, photolithography, and etching. 3 (TiSb 10 Te 10 ) 97 material pattern so that the N above each bottom electrode 3 (TiSb 10 Te 10 ) 97 The materials are electrically insulated from each other. The top electrode titanium nitride TiN was deposited by physical vapor deposition with a thickness of 20 nanometers, and N was prepared by glue coating, photolithography, etching and other processes. 3 (TiSb 10 Te 10 ) 97 Above the TiN electrode material pattern so that each N 3 (TiSb 10 Te 10 ) 97 The top electrode materials above are electrically insulated from each other. get based on N 3 (TiSb 10 Te 10 ) 97 The T-shaped structure synaptic bionic unit of the material; ...

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Abstract

The invention discloses an N-Ti-Sb-Te-based synaptic bionic device used in an artificial neural network. The present invention is used for preparing the storage medium of synaptic bionic device, which is N x (TiSb y Te z ) 100‑x , where 0.1≤x≤5, 0.25≤y / z≤4, and 12≤y+z≤50. The material can realize the repeated conversion of multi-state high and low resistance values ​​under the operation of electrical signals, and maintain the resistance value unchanged in the absence of operation signals; wherein 500 picoseconds≤electrical signal pulse width≤500 nanoseconds. The synaptic biomimetic device based on the N‑Ti‑Sb‑Te series phase change materials can provide a resolution close to 8 bits in the intermediate state resistance value under the operation of electrical signals, and the switch resistance difference can reach 1000 times. Under the same pulse operation The linear response of resistance to the number of pulses is realized, and it has excellent electrical properties as a synaptic bionic device.

Description

technical field [0001] The invention relates to the field of semiconductor manufacturing materials and semiconductor devices, in particular to a storage medium material and a device for manufacturing synaptic bionic devices in artificial neural networks. Background technique [0002] Artificial Neural Network (ANN) has been a research hotspot in the field of artificial intelligence since the 1980s. It abstracts the neuron network of the human brain from the perspective of information processing, establishes a certain simple model, and forms different networks according to different connection methods. In engineering and academia, it is often simply referred to as neural network or neural-like network. Neural network is an operation model, which is composed of a large number of nodes (or neurons) connected with each other. Each node represents a specific output function, called the activation function. The connection between each two nodes represents a weighted value for t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H01L45/00G06N3/063
CPCG06N3/063H10N70/8828
Inventor 任堃赵哲昊季振国
Owner HANGZHOU DIANZI UNIV
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