Improved artificial synapse performance of Pt/HfO2/BiFeO3/HfO2/TiN memristor through N2 annealing

Xiao, Yongyue; Wu, Xinjiang; Jin, Yaoyao; Cao, Guangsen; Jiang, Bei; Ke, Shanwu; Ye, Cong

doi:10.1016/j.ceramint.2022.08.045

Cited by 7 publications

(4 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We used the methods and obtained ideal linearity in our previous work. [ 37,38 ] In addition, the cross‐crosstalk phenomenon of the memristor array needs to be considered in the construction of an artificial neural network. It is necessary to eliminate the cross‐talk phenomena of the memristor array in future work.…”

Section: Resultsmentioning

confidence: 99%

An Efficient Design of TaO_x‐Based Memristor by Inserting an Ultrathin Al₂O₃ Layer with High Stability for Neuromorphic Computing and Logic Operation

Jiang

Jin

Zhao

et al. 2023

Advanced Physics Research

Self Cite

View full text Add to dashboard Cite

New computing-in-memory architecture based on memristors can achieve in situ storage and computing of data, which greatly improves the computing efficiency of the hardware system. Here, a reliable bilayer structured TaO x /Al 2 O 3 memristor with a 2 nm Al 2 O 3 insertion layer is demonstrated. This device exhibits stable and gradual switching behavior with a low set/reset voltage (0.61 V/−0.49 V) and multilevel conductance characteristics. It is further indicated that the device has a larger ON/Off ratio (≈148×) and better nonlinearity of conductance modulation by inserting an Al 2 O 3 layer. Various forms of synaptic plasticity are mimicked, such as long-term potentiation/depression (LTP/LTD), paired-pulse facilitation (PPF), and spike-timing-dependent plasticity (STDP). Based on the quasi-linear conductance modulation characteristics, excellent classification accuracy (90.4%) is achieved for the applications of handwritten digit recognition. Moreover, the logic operations (intersection, union, and complement) are implemented on a 3 × 5 memristor array, which shows an efficient way to design versatile and reliable devices and provides a novel idea for neuromorphic computing and in-memory logic operation.

show abstract

Section: Resultsmentioning

confidence: 99%

An Efficient Design of TaO_x‐Based Memristor by Inserting an Ultrathin Al₂O₃ Layer with High Stability for Neuromorphic Computing and Logic Operation

Jiang

Jin

Zhao

et al. 2023

Advanced Physics Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…Utilizing three different voltage signals and resistance states to serve as logic inputs and outputs, the three-valued logic can be established [1,4]. In previous studies, the three-state RS effect can be realized by adjusting the fabrication process of the memristor [6][7][8][9][10]. For example, You et al presented a three-state RS effect based on the asymmetric bipolar memory [11].…”

Section: Introductionmentioning

confidence: 99%

“…Liu et al demonstrated a multi-state RS effect by inserting the BiFeO 3 (BFO) thin film to the HfO 2 memory [7]. Through applying different voltage to the sample and controlling the RS behavior of the memristor, the three-state RS effect can be obtained [6][7][8][9][10]. For the fabricated devices, the external method by tuning the compliance current was developed [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Three-state resistive switching effect in BiFeO₃ thin films

Yang¹,

Zhang²,

Yang³

et al. 2022

Phys. Scr.

View full text Add to dashboard Cite

Resistive switching (RS) memristor has been widely used in the in-memory computation systems. Due to the strong information processing capability and low area cost of the ternary logic, the development of the three-state RS memristor was promoted. Here, we demonstrate a three-state RS phenomenon on Pt/BiFeO3/SrRuO3 structure. After applying a positive voltage to the thin film for a period, an abrupt RS effect occurs, where the three-state RS behavior can be obtained. By analyzing the conduction mechanisms of the current-voltage curves and the behavior of the capacitance-voltage curves, the three-state storage capability of the memristor can be ascribed to the movement of oxygen vacancies and the trapping/detrapping of charge carriers at the interface. The ternary OR logic gate was also designed with three steps by using only one memristor.

show abstract

“…Figure a(i) shows the optical image and a schematic image of the 10 × 10 Ag/HfO 2 /NiO/Pt memristors array, and Figure a(ii) illustrates an enlarged view of the basic memristor unit. The reconfigurable device consists of a Ag top electrode, HfO 2 (5 nm), NiO (15 nm), and Pt bottom electrode, where the HfO 2 film acts as a blocking layer to limit the diffusion of Ag ions. − As shown in Figure c, when the device is stressed by a low compliance current, the device behavior changes to volatile threshold resistive switching. This behavior allows simulation of spiking neuron functions.…”

mentioning

confidence: 99%

Reconfigurable Ag/HfO₂/NiO/Pt Memristors with Stable Synchronous Synaptic and Neuronal Functions for Renewable Homogeneous Neuromorphic Computing System

Chen,

Liu,

Liu

et al. 2024

Nano Lett.

Self Cite

View full text Add to dashboard Cite

Artificial synapses and bionic neurons offer great potential in highly efficient computing paradigms. However, complex requirements for specific electronic devices in neuromorphic computing have made memristors face the challenge of process simplification and universality. Herein, reconfigurable Ag/ HfO 2 /NiO/Pt memristors are designed for feasible switching between volatile and nonvolatile modes by compliance current controlled Ag filaments, which enables stable and reconfigurable synaptic and neuronal functions. A neuromorphic computing system effectively replicates the biological synaptic weight alteration and continuously accomplishes excitation and reset of artificial neurons, which consist of bionic synapses and artificial neurons based on isotype Ag/HfO 2 /NiO/Pt memristors. This reconfigurable electrical performance of the Ag/HfO 2 /NiO/Pt memristors takes advantage of simplified hardware design and delivers integrated circuits with high density, which exhibits great potency for future neural networks.

show abstract

Improved artificial synapse performance of Pt/HfO2/BiFeO3/HfO2/TiN memristor through N2 annealing

Cited by 7 publications

References 30 publications

An Efficient Design of TaO_x‐Based Memristor by Inserting an Ultrathin Al₂O₃ Layer with High Stability for Neuromorphic Computing and Logic Operation

An Efficient Design of TaO_x‐Based Memristor by Inserting an Ultrathin Al₂O₃ Layer with High Stability for Neuromorphic Computing and Logic Operation

Three-state resistive switching effect in BiFeO₃ thin films

Reconfigurable Ag/HfO₂/NiO/Pt Memristors with Stable Synchronous Synaptic and Neuronal Functions for Renewable Homogeneous Neuromorphic Computing System

Contact Info

Product

Resources

About

Improved artificial synapse performance of Pt/HfO2/BiFeO3/HfO2/TiN memristor through N2 annealing

Cited by 7 publications

References 30 publications

An Efficient Design of TaOx‐Based Memristor by Inserting an Ultrathin Al2O3 Layer with High Stability for Neuromorphic Computing and Logic Operation

An Efficient Design of TaOx‐Based Memristor by Inserting an Ultrathin Al2O3 Layer with High Stability for Neuromorphic Computing and Logic Operation

Three-state resistive switching effect in BiFeO3 thin films

Reconfigurable Ag/HfO2/NiO/Pt Memristors with Stable Synchronous Synaptic and Neuronal Functions for Renewable Homogeneous Neuromorphic Computing System

Contact Info

Product

Resources

About

An Efficient Design of TaO_x‐Based Memristor by Inserting an Ultrathin Al₂O₃ Layer with High Stability for Neuromorphic Computing and Logic Operation

An Efficient Design of TaO_x‐Based Memristor by Inserting an Ultrathin Al₂O₃ Layer with High Stability for Neuromorphic Computing and Logic Operation

Three-state resistive switching effect in BiFeO₃ thin films

Reconfigurable Ag/HfO₂/NiO/Pt Memristors with Stable Synchronous Synaptic and Neuronal Functions for Renewable Homogeneous Neuromorphic Computing System