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Artificial non-monotonic neurons based on nonvolatile anti-ambipolar transistors

delete2025-04-03
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OA
AI
Y
Yue Pang
周晔欣 (Yaoqiang Zhou) *
S
Shirong Qiu
L
Lei Tong
N
Ni Zhao
DOI:10.1038/s41467-025-58541-8delete
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Abstract

Abstract

En 中文
Non-monotonic neurons integrate monotonic input into a non-monotonic response, effectively improving the efficiency of unsupervised learning and precision of information processing in peripheral sensor systems. However, non-monotonic neuron-synapse circuits based on conventional technology require multiple transistors and complicated layouts. By leveraging the advantages of compact design for complex functions with two-dimensional materials, herein, we used anti-ambipolar transistor with airgaps configuration to fabricate the non-monotonic neuron with a bell-shaped response function. The anti-ambipolar transistor demonstrated near-ideal subthreshold swings of 60 mV/dec, a benchmark combination of a high peak-to-valley ratio of similar to 10(5). By utilizing the floating gate architecture, the non-volatile transistors achieved a high operating speed similar to 10(-7) s and robust durability exceeding 10(4) cycles. The non-volatile anti-ambipolar transistor showed spike amplitude, width, and number-dependent excitation and inhibition synaptic behaviors. Furthermore, its non-volatile performance can replicate biological neurons showing a reconfigurable monotonic and non-monotonic response by modulating the amplitude and width of presynaptic input. We encoded systolic blood pressure and resting heart rate data to train non-monotonic neurons, achieving the prediction of health conditions with a detection accuracy surpassing 85% at the device level, closely corresponding to the recognized medical standards.
Keywords:
HETEROJUNCTION
DEVICE

Journal

Nature Communications cover
Nature Communications
IF:
15.7
Papers:
9.2W
Citations:
91.2W

Organization

No organization information available