Cao, Y., Yin, L., Zhao, C., Zhao, T., Li, T., Kong, S., Shi, L., Zhou, J., Zhang, Z., Yang, K., Xue, Z., Wang, H., Wu, R., Ding, C., Han, Y., Luo, Q., Gu, M. Q., Wang, X., Xu, W., ... Wen, Z. (2024). Perovskite-based optoelectronic systems for neuromorphic computing. Nano Energy, 120, Article 109169. https://doi.org/10.1016/j.nanoen.2023.109169
Cao, Yixin ; Yin, Li ; Zhao, Chun et al. / Perovskite-based optoelectronic systems for neuromorphic computing. In: Nano Energy. 2024 ; Vol. 120.
@article{a656b65cc20440119cf3dd04fad3a243,
title = "Perovskite-based optoelectronic systems for neuromorphic computing",
abstract = "Brain-like neuromorphic computing system offers the ability to be used in neural networks on demand and are rapidly gaining interest by researchers due to their outstanding photoelectric stimulation response-ability and multi-segment storage function. In this work, we show the processing capabilities of the neuromorphic computing units for optoelectronic signals and high label noise ratio signals. Demonstrated the functions of potassium ion doped perovskite-based unit resembles properties found in neuronal synapses. Potassium ion passivates perovskite and promotes the formation of the electric double layer and ion doping in the unit so that the unit can simulate the characteristics of biological synapses generated by various electrical simulations according to the demand. Perovskite significantly enhances the unit's responsiveness to light pulses in the visible light range. By implementing the 'resolving training biases via influence-base data relabeling' strategy, the unit demonstrates remarkable performance in high noise recognition tasks. These results open a new direction for the construction of brain-like computers that deal with a complex and high proportion of harmful samples.",
keywords = "Artificial intelligence, COVID-19, Neuromorphic computing, Perovskite",
author = "Yixin Cao and Li Yin and Chun Zhao and Tianshi Zhao and Tianyou Li and Shuming Kong and Liming Shi and Jiabao Zhou and Zhiyuan Zhang and Ke Yang and Zhihao Xue and Hangyu Wang and Rui Wu and Changzeng Ding and Yunfei Han and Qun Luo and Gu, {Maxwell Qihan} and Xin Wang and Wangying Xu and Jiangmin Gu and Yingli Shi and Li Yang and Xiao Gong and Zhen Wen",
note = "Publisher Copyright: {\textcopyright} 2023 Elsevier Ltd",
year = "2024",
month = feb,
doi = "10.1016/j.nanoen.2023.109169",
language = "English",
volume = "120",
journal = "Nano Energy",
issn = "2211-2855",
}
Cao, Y, Yin, L, Zhao, C, Zhao, T, Li, T, Kong, S, Shi, L, Zhou, J, Zhang, Z, Yang, K, Xue, Z, Wang, H, Wu, R, Ding, C, Han, Y, Luo, Q, Gu, MQ, Wang, X, Xu, W, Gu, J, Shi, Y, Yang, L, Gong, X & Wen, Z 2024, 'Perovskite-based optoelectronic systems for neuromorphic computing', Nano Energy, vol. 120, 109169. https://doi.org/10.1016/j.nanoen.2023.109169
Perovskite-based optoelectronic systems for neuromorphic computing. / Cao, Yixin; Yin, Li
; Zhao, Chun et al.
In:
Nano Energy, Vol. 120, 109169, 02.2024.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Perovskite-based optoelectronic systems for neuromorphic computing
AU - Cao, Yixin
AU - Yin, Li
AU - Zhao, Chun
AU - Zhao, Tianshi
AU - Li, Tianyou
AU - Kong, Shuming
AU - Shi, Liming
AU - Zhou, Jiabao
AU - Zhang, Zhiyuan
AU - Yang, Ke
AU - Xue, Zhihao
AU - Wang, Hangyu
AU - Wu, Rui
AU - Ding, Changzeng
AU - Han, Yunfei
AU - Luo, Qun
AU - Gu, Maxwell Qihan
AU - Wang, Xin
AU - Xu, Wangying
AU - Gu, Jiangmin
AU - Shi, Yingli
AU - Yang, Li
AU - Gong, Xiao
AU - Wen, Zhen
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2024/2
Y1 - 2024/2
N2 - Brain-like neuromorphic computing system offers the ability to be used in neural networks on demand and are rapidly gaining interest by researchers due to their outstanding photoelectric stimulation response-ability and multi-segment storage function. In this work, we show the processing capabilities of the neuromorphic computing units for optoelectronic signals and high label noise ratio signals. Demonstrated the functions of potassium ion doped perovskite-based unit resembles properties found in neuronal synapses. Potassium ion passivates perovskite and promotes the formation of the electric double layer and ion doping in the unit so that the unit can simulate the characteristics of biological synapses generated by various electrical simulations according to the demand. Perovskite significantly enhances the unit's responsiveness to light pulses in the visible light range. By implementing the 'resolving training biases via influence-base data relabeling' strategy, the unit demonstrates remarkable performance in high noise recognition tasks. These results open a new direction for the construction of brain-like computers that deal with a complex and high proportion of harmful samples.
AB - Brain-like neuromorphic computing system offers the ability to be used in neural networks on demand and are rapidly gaining interest by researchers due to their outstanding photoelectric stimulation response-ability and multi-segment storage function. In this work, we show the processing capabilities of the neuromorphic computing units for optoelectronic signals and high label noise ratio signals. Demonstrated the functions of potassium ion doped perovskite-based unit resembles properties found in neuronal synapses. Potassium ion passivates perovskite and promotes the formation of the electric double layer and ion doping in the unit so that the unit can simulate the characteristics of biological synapses generated by various electrical simulations according to the demand. Perovskite significantly enhances the unit's responsiveness to light pulses in the visible light range. By implementing the 'resolving training biases via influence-base data relabeling' strategy, the unit demonstrates remarkable performance in high noise recognition tasks. These results open a new direction for the construction of brain-like computers that deal with a complex and high proportion of harmful samples.
KW - Artificial intelligence
KW - COVID-19
KW - Neuromorphic computing
KW - Perovskite
UR - http://www.scopus.com/inward/record.url?scp=85180369090&partnerID=8YFLogxK
U2 - 10.1016/j.nanoen.2023.109169
DO - 10.1016/j.nanoen.2023.109169
M3 - Article
AN - SCOPUS:85180369090
SN - 2211-2855
VL - 120
JO - Nano Energy
JF - Nano Energy
M1 - 109169
ER -
Cao Y, Yin L, Zhao C, Zhao T, Li T, Kong S et al. Perovskite-based optoelectronic systems for neuromorphic computing. Nano Energy. 2024 Feb;120:109169. doi: 10.1016/j.nanoen.2023.109169