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基于非易失性反双极性晶体管的人工非单调神经元。

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

作者信息

Pang Yue, Zhou Yaoqiang, Qiu Shirong, Tong Lei, Zhao Ni, Xu Jian-Bin

机构信息

Department of Electronic Engineering and Materials Science and Technology Research Center, The Chinese University of Hong Kong, Hong Kong SAR, China.

Department of Electronics and Nanoengineering, Aalto University, Espoo, 02150, Finland.

出版信息

Nat Commun. 2025 Apr 3;16(1):3188. doi: 10.1038/s41467-025-58541-8.

DOI:10.1038/s41467-025-58541-8
PMID:40181010
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11968844/
Abstract

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 ~10. By utilizing the floating gate architecture, the non-volatile transistors achieved a high operating speed ~10s and robust durability exceeding 10 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.

摘要

非单调神经元将单调输入整合为非单调响应,有效提高了外周传感器系统中无监督学习的效率和信息处理的精度。然而,基于传统技术的非单调神经元 - 突触电路需要多个晶体管和复杂的布局。通过利用二维材料对复杂功能进行紧凑设计的优势,在此我们使用具有气隙配置的反双极晶体管来制造具有钟形响应函数的非单调神经元。该反双极晶体管展示了接近理想的60 mV/dec亚阈值摆幅,这是高达约10的高峰谷比的基准组合。通过采用浮栅架构,非易失性晶体管实现了高达约10s的高运行速度和超过10个周期的强大耐久性。非易失性反双极晶体管表现出与尖峰幅度、宽度和数量相关的兴奋和抑制突触行为。此外,其非易失性性能可以通过调节突触前输入的幅度和宽度来复制显示可重构单调和非单调响应的生物神经元。我们对收缩压和静息心率数据进行编码以训练非单调神经元,在器件层面实现了对健康状况的预测,检测准确率超过85%,与公认的医学标准密切对应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/11968844/ff59d7e80403/41467_2025_58541_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/11968844/026e2cae4a3f/41467_2025_58541_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/11968844/49f2251c65a7/41467_2025_58541_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/11968844/866165bed38b/41467_2025_58541_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/11968844/940b296c6fe6/41467_2025_58541_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/11968844/ff59d7e80403/41467_2025_58541_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/11968844/026e2cae4a3f/41467_2025_58541_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/11968844/49f2251c65a7/41467_2025_58541_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/11968844/866165bed38b/41467_2025_58541_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/11968844/940b296c6fe6/41467_2025_58541_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/11968844/ff59d7e80403/41467_2025_58541_Fig5_HTML.jpg

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