Compact artificial neuron based on anti-ferroelectric transistor

Abstract

Neuromorphic machines are intriguing for building energy-efficient intelligent systems, where spiking neurons are pivotal components. Recently, memristive neurons with promising bio-plausibility have been developed, but with limited reliability, bulky capacitors or additional reset circuits. Here, we propose an anti-ferroelectric field-effect transistor neuron based on the inherent polarization and depolarization of Hf0.2Zr0.8O2 anti-ferroelectric film to meet these challenges. The intrinsic accumulated polarization/spontaneous depolarization of Hf0.2Zr0.8O2 films implements the integration/leaky behavior of neurons, avoiding external capacitors and reset circuits. Moreover, the anti-ferroelectric neuron exhibits low energy consumption (37 fJ/spike), high endurance (>1012), high uniformity and high stability. We further construct a two-layer fully ferroelectric spiking neural networks that combines anti-ferroelectric neurons and ferroelectric synapses, achieving 96.8% recognition accuracy on the Modified National Institute of Standards and Technology dataset. This work opens the way to emulate neurons with anti-ferroelectric materials and provides a promising approach to building high-efficient neuromorphic hardware.

Interlayer Transition Induced Infrared Response in ReS2/2D Perovskite van der Waals Heterostructure Photodetector

“…Figure S8 shows the variation in V oc and I sc (short circuit current) with varing power density. The device shows relatively low V oc value under weak light irradiation, which may be caused by large lateral resistance . With the information above, the output electrical power P el can be extracted with the formula P el = V oc × I sc (Figure b inset) .…”

“…The device shows relatively low V oc value under weak light irradiation, which may be caused by large lateral resistance. 5 With the information above, the output electrical power P el can be extracted with the formula P el = V oc × I sc (Figure 4b inset). 33 Moreover, the external quantum efficiency (EQE) is evaluated by the following equation: 34 which is defined as the ratio of charge carriers collected by the electrode to incident photons.…”

“…Epitaxy-free van der Waals (vdW) heterostructures formed by vertically stacking two-dimensional (2D) materials have led to a new era in both fundamental physics and applied research due to high-quality heterogeneous interface and tailored energy band alignment . Specifically, the ultrathin heterostructures with a variety of stacking orders have exhibited promising prospect in electronic and optoelectronic applications including field-effect transistors, , memristor, , light-emitting diodes, photodetectors, and so on . Among them, most reported photodetectors were realized by conjugating 2D pn heterostructure with separate p- and n-type semiconductors, which exhibited atomically abrupt heterojunctions and efficient photogenerated carriers separation owing to the large built-in barrier as seen in GaSe/ReS 2 , WSe 2 /MoS 2 , MoTe 2 /ReS 2 , WS 2 /ReS 2 , and WSe 2 /ReSe 2 heterostructures.…”

Quasi-Volatile MoS2 Barristor Memory for 1T Compact Neuron by Correlative Charges Trapping and Schottky Barrier Modulation

“…Figure d shows the increase in the selected threshold current and the test accuracy increases. We also compare the accuracy of the SNN based on this CT-SB MoS 2 neuron with the accuracy of the SNN based on neurons proposed by some publications. ,− From Table , we can see that our accuracy is at the leading level. This result shows that the proposed CT-SB MoS 2 barristor neurons have great potential for fabricating SNN chips.…”

Margin‐based reliability reinforcement method for stateful logic

“…In‐memory computing is regarded as one of the most promising methods to break the “Memory Wall” [1]. Stateful logic uses the non‐volatile resistance state to represent logic value, thus can realize in‐memory computation [2].…”