Tunable flexible artificial synapses: a new path toward a wearable electronic system

Abstract

The flexible electronics has been deemed to be a promising approach to the wearable electronic systems. However, the mismatching between the existing flexible deices and the conventional computing paradigm results an impasse in this field. In this work, a new way to access to this goal is proposed by combining flexible devices and the neuromorphic architecture together. To achieve that, a high-performance flexible artificial synapse is created based on a carefully designed and optimized memristive transistor. The device exhibits high-performance which has near-linear non-volatile resistance change under 10,000 identical pulse signals within the 515% dynamic range, and has the energy consumption as low as 45 fJ per pulse. It also displays multiple synaptic plasticity features, which demonstrates its potential for real-time online learning. Besides, the adaptability by virtue of its threeterminal structure specifically contributes its improved uniformity, repeatability, and reduced power consumption. This work offers a very viable solution for the future wearable computing.

Stretchable elastic synaptic transistors for neurologically integrated soft engineering systems

“…1A. The understandings in biology and advances in materials and electronic technologies have led to the recent development of artificial synaptic devices, mostly in rigid or flexible formats (10)(11)(12)(13)(14)(15)(16)(17), to emulate the biological counterparts toward emerging applications, such as parallel processing (18)(19)(20)(21)(22)(23), low-power computing (10,24), neuroprosthetics (11,25), etc. Artificial synapses, which are very stretchable similar to those that appear in soft animals, are key to enabled neurological functions in soft machines and many other applications, such as neuroprosthetics (11,(26)(27)(28)(29).…”

Recent Advances in Transistor‐Based Artificial Synapses

“…In the past few years, scientists around the world have tried to mimic the signal transmission process and various types of synaptic plasticity in the brain, although the brain mystery has not yet been fully revealed . The realization of “brain‐like computing” can start from simulating the structure and function of neural networks and artificial synapses, without waiting for neuroscientists and cognitive scientists to fully understand the brain's mechanism, which may even need the exploration process to be longer.…”

Ultrathin electronic synapse having high temporal/spatial uniformity and an Al2O3/graphene quantum dots/Al2O3 sandwich structure for neuromorphic computing

“…Two-terminal memristive devices are promising candidates to act as a compact electronic element and have been widely demonstrated in the pursuit of certain synaptic functions [8][9][10] . Specifically, synaptic operations, including long-term potentiation/depression (LTP/LTD), short-term potentiation/depression (STP/STD), spiketiming-dependent plasticity (STDP) learning rules, paired-pulse facilitation (PPF), and low-power consumption have been extensively simulated in these electronic synapses (e-synapses) [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] . However, e-synapses usually suffer from unavoidable temporal (cycle-to-cycle) and spatial (device-to-device) variations due to their intrinsic working mechanism and structure interaction.…”