An Organic Flexible Artificial Bio-Synapses with Long-Term Plasticity for Neuromorphic Computing

Abstract

Artificial synapses, with synaptic plasticity, are the key components of constructing the neuromorphic computing system and mimicking the bio-synaptic function. Traditional synaptic devices are based on silicon and inorganic materials, while organic electronics can open up new opportunities for flexible devices. Here, a flexible artificial synaptic device with an organic functional layer was proposed. The organic device showed good switching behaviors such as ON/OFF ratio over 100 at low operation voltages. The set and reset voltages were lower than 0.5 V and −0.25 V, respectively. The long-term plasticity, spike-timing-dependent plasticity learning rules (STDP), and forgetting function were emulated using the device. The retention times of the excitatory and inhibitory post-synaptic currents were both longer than 60 s. The long-term plasticity was repeatable without noticeable degradation after the application of five voltage pulse cycles to the top electrode. These results indicate that our organic flexible device has the potential to be applied in bio-inspired neuromorphic systems.

Advances of RRAM Devices: Resistive Switching Mechanisms, Materials and Bionic Synaptic Application

“…Compared with the investigation of STP, current research on LTP mainly focuses on long-term potentiation/depression and transition from STP to LTP [ 79 , 163 , 164 ]. Wang et al proposed a flexible bipolar RRAM device with ALD-deposited Hf 0.5 Zr 0.5 O 2 (HZO) dielectric layer, as illustrated in Figure 13 a–c, which worked as artificial synapses in the neuromorphic network in order to overcome the bottleneck based on traditional Von Neumann structure [ 79 ].…”

Implementation of Dropout Neuronal Units Based on Stochastic Memristive Devices in Neural Networks with High Classification Accuracy

“…Thanks to the compact structure and intrinsic learning ability, [ 2‐8 ] and the advantages of parallel computing and low energy consumption, [ 2,9‐15 ] memristive devices are commonly used as artificial synapses. However, the conductance (weight) of many memristive devices is modulated nonlinearly and asymmetrically during training, [ 16‐21 ] which limits the classification accuracy. [ 8 ] Great efforts were made to improve the performances of memristive devices, such as developing three‐terminal devices, [ 4 ] preparing changeable compliance current devices, [ 22 ] and designing specific pulses for SET/RESET.…”

Editorial for Special Issue on Flexible Electronics: Fabrication and Ubiquitous Integration

“…There are 10 papers published in this Special Issue, covering new strategies for a paradigm shift in the design [ 1 , 2 , 3 ], fabrication [ 4 , 5 , 6 , 7 ], and encapsulation [ 8 , 9 , 10 ] of next-generation flexible systems. Xiao et al [ 1 ] proposed an “island-bridge” strategy to design high-performance stretchable electronics composed of inorganic rigid components so that that can they can be conformally transferred to non-developable surfaces.…”

“…On the application side, these papers have focused on the implementation of flexible systems in healthcare [ 4 , 10 ], photonics [ 3 ], and the human–machine interface [ 9 ]. Traditional manufacturing approaches and materials used to fabricate flexible epidermal electronics for physiological monitoring, transdermal stimulation, and therapeutics have proven to be complex and expensive, impeding the fabrication of flexible electronic systems that can be used as single-use medical devices.…”

“…This flexible plasmonic variable attenuator constitutes a step forward towards the fabrication of high-density photonic integrated circuits and a new solution for data transmission and amplitude control in microwave photonic systems. To improve human–machine interfaces through the construction of neuromorphic computing systems capable of mimicking the bio-synaptic functions, Wang et al [ 9 ] developed a flexible artificial synaptic device with an organic functional layer. This flexible device exhibits retention times of the excitatory and inhibitory post-synaptic currents longer than 60 s.…”