2023
DOI: 10.1016/j.jallcom.2023.170920
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Highly uniform resistive switching characteristics of Ti/TaOx/ITO memristor devices for neuromorphic system

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Cited by 38 publications
(15 citation statements)
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“…Before the resistive switching phenomenon was observed, an initial soft breakdown process, known as the forming process, was required for converting the device from the HRS to the LRS. As shown in Figure a, a bias of 4 V and a compliance current (CC) of 1 mA is applied to the device to complete the forming process and prevent a hard breakdown . The I–V curve representing the 100-cycle bipolar resistive-switching characteristic of the Pt/WO x /ITO device is illustrated in Figure b.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Before the resistive switching phenomenon was observed, an initial soft breakdown process, known as the forming process, was required for converting the device from the HRS to the LRS. As shown in Figure a, a bias of 4 V and a compliance current (CC) of 1 mA is applied to the device to complete the forming process and prevent a hard breakdown . The I–V curve representing the 100-cycle bipolar resistive-switching characteristic of the Pt/WO x /ITO device is illustrated in Figure b.…”
Section: Resultsmentioning
confidence: 99%
“…As shown in Figure 2a, a bias of 4 V and a compliance current (CC) of 1 mA is applied to the device to complete the forming process and prevent a hard breakdown. 53 The I−V curve representing the 100-cycle bipolar resistive-switching characteristic of the Pt/WO x /ITO device is illustrated in Figure 2b. To turn on the device, a voltage of 3 V and a CC of 100 μA were applied, switching the device from the HRS to the LRS.…”
Section: ■ Results and Discussionmentioning
confidence: 99%
“…Additionally, a pattern recognition test using handwritten digits from an MNIST dataset was conducted to check the further application of the device as a synaptic device. The training was conducted with unclear images, and the gradual and symmetric conductance changes in potentiation and depression resulted in clearer images with higher accuracy [ 59 , 60 ]. As shown in Figure 7 c, the deep neural network (DNN) comprised 784 input neurons, 3 hidden layers, and 10 output neurons.…”
Section: Resultsmentioning
confidence: 99%
“…In the case of filament type memristors, conductive filaments are formed and broken due to ion migration in response to bias, resulting in the transition between the LRS and HRS. [6][7][8][9]29,30 These conductive filaments are inherently incapable of exhibiting self-rectification, which leads to sneak currents in a crossbar array. Furthermore, the formation of these conductive filaments is highly irregular, and controlling the filament size is very difficult.…”
Section: Introductionmentioning
confidence: 99%