Photoprogrammed Multifunctional Optoelectronic Synaptic Transistor Arrays Based on Photosensitive Polymer‐Sorted Semiconducting Single‐Walled Carbon Nanotubes for Image Recognition
The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel broadband (from 365 to 940 nm) and multilevel storage optoelectronic synaptic thin‐film transistor (TFT) arrays are reported using the photosensitive c...
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| Published in | Advanced science Vol. 11; no. 29; pp. e2401794 - n/a |
|---|---|
| Main Authors | , , , , , , , , , |
| Format | Journal Article |
| Language | English |
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Germany
John Wiley & Sons, Inc
01.08.2024
John Wiley and Sons Inc Wiley |
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| Online Access | Get full text |
| ISSN | 2198-3844 2198-3844 |
| DOI | 10.1002/advs.202401794 |
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| Abstract | The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel broadband (from 365 to 940 nm) and multilevel storage optoelectronic synaptic thin‐film transistor (TFT) arrays are reported using the photosensitive conjugated polymer (poly[(9,9‐dioctylfluorenyl‐2,7‐diyl)‐co‐(bithiophene)], F8T2) sorted semiconducting single‐walled carbon nanotubes (sc‐SWCNTs) as channel materials. The broadband synaptic responses are inherited to absorption from both photosensitive F8T2 and sorted sc‐SWCNTs, and the excellent optoelectronic synaptic behaviors with 200 linearly increasing conductance states and long retention time > 103 s are attributed to the superior charge trapping at the AlOx dielectric layer grown by atomic layer deposition. Furthermore, the synaptic TFTs can achieve IOn/IOff ratios up to 106 and optoelectronic synaptic plasticity with the low power consumption (59 aJ per single pulse), which can simulate not only basic biological synaptic functions but also optical write and electrical erase, multilevel storage, and image recognition. Further, a novel Spiking Neural Network algorithm based on hardware characteristics is designed for the recognition task of Caltech 101 dataset and multiple features of the images are successfully extracted with higher accuracy (97.92%) of the recognition task from the multi‐frequency curves of the optoelectronic synaptic devices.
The authors selectively isolated from commercial SWCNTs using the photosensitive conjugated polymers, and the optoelectronic synaptic transistors are successfully constructed with low power consumption (59 aJ per spike) and excellent storage characteristics for simulation of neuromorphic vision systems (the accuracy ≈97.92%). Their SWCNT optoelectronic synaptic transistors do not require the introduction of any additional photosensitive materials and exhibit excellent optoelectronic properties. |
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| AbstractList | The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel broadband (from 365 to 940 nm) and multilevel storage optoelectronic synaptic thin-film transistor (TFT) arrays are reported using the photosensitive conjugated polymer (poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-(bithiophene)], F8T2) sorted semiconducting single-walled carbon nanotubes (sc-SWCNTs) as channel materials. The broadband synaptic responses are inherited to absorption from both photosensitive F8T2 and sorted sc-SWCNTs, and the excellent optoelectronic synaptic behaviors with 200 linearly increasing conductance states and long retention time > 103 s are attributed to the superior charge trapping at the AlOx dielectric layer grown by atomic layer deposition. Furthermore, the synaptic TFTs can achieve IOn/IOff ratios up to 106 and optoelectronic synaptic plasticity with the low power consumption (59 aJ per single pulse), which can simulate not only basic biological synaptic functions but also optical write and electrical erase, multilevel storage, and image recognition. Further, a novel Spiking Neural Network algorithm based on hardware characteristics is designed for the recognition task of Caltech 101 dataset and multiple features of the images are successfully extracted with higher accuracy (97.92%) of the recognition task from the multi-frequency curves of the optoelectronic synaptic devices.The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel broadband (from 365 to 940 nm) and multilevel storage optoelectronic synaptic thin-film transistor (TFT) arrays are reported using the photosensitive conjugated polymer (poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-(bithiophene)], F8T2) sorted semiconducting single-walled carbon nanotubes (sc-SWCNTs) as channel materials. The broadband synaptic responses are inherited to absorption from both photosensitive F8T2 and sorted sc-SWCNTs, and the excellent optoelectronic synaptic behaviors with 200 linearly increasing conductance states and long retention time > 103 s are attributed to the superior charge trapping at the AlOx dielectric layer grown by atomic layer deposition. Furthermore, the synaptic TFTs can achieve IOn/IOff ratios up to 106 and optoelectronic synaptic plasticity with the low power consumption (59 aJ per single pulse), which can simulate not only basic biological synaptic functions but also optical write and electrical erase, multilevel storage, and image recognition. Further, a novel Spiking Neural Network algorithm based on hardware characteristics is designed for the recognition task of Caltech 101 dataset and multiple features of the images are successfully extracted with higher accuracy (97.92%) of the recognition task from the multi-frequency curves of the optoelectronic synaptic devices. Abstract The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel broadband (from 365 to 940 nm) and multilevel storage optoelectronic synaptic thin‐film transistor (TFT) arrays are reported using the photosensitive conjugated polymer (poly[(9,9‐dioctylfluorenyl‐2,7‐diyl)‐co‐(bithiophene)], F8T2) sorted semiconducting single‐walled carbon nanotubes (sc‐SWCNTs) as channel materials. The broadband synaptic responses are inherited to absorption from both photosensitive F8T2 and sorted sc‐SWCNTs, and the excellent optoelectronic synaptic behaviors with 200 linearly increasing conductance states and long retention time > 103 s are attributed to the superior charge trapping at the AlOx dielectric layer grown by atomic layer deposition. Furthermore, the synaptic TFTs can achieve IOn/IOff ratios up to 106 and optoelectronic synaptic plasticity with the low power consumption (59 aJ per single pulse), which can simulate not only basic biological synaptic functions but also optical write and electrical erase, multilevel storage, and image recognition. Further, a novel Spiking Neural Network algorithm based on hardware characteristics is designed for the recognition task of Caltech 101 dataset and multiple features of the images are successfully extracted with higher accuracy (97.92%) of the recognition task from the multi‐frequency curves of the optoelectronic synaptic devices. The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel broadband (from 365 to 940 nm) and multilevel storage optoelectronic synaptic thin-film transistor (TFT) arrays are reported using the photosensitive conjugated polymer (poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-(bithiophene)], F8T2) sorted semiconducting single-walled carbon nanotubes (sc-SWCNTs) as channel materials. The broadband synaptic responses are inherited to absorption from both photosensitive F8T2 and sorted sc-SWCNTs, and the excellent optoelectronic synaptic behaviors with 200 linearly increasing conductance states and long retention time > 10 s are attributed to the superior charge trapping at the AlO dielectric layer grown by atomic layer deposition. Furthermore, the synaptic TFTs can achieve I /I ratios up to 10 and optoelectronic synaptic plasticity with the low power consumption (59 aJ per single pulse), which can simulate not only basic biological synaptic functions but also optical write and electrical erase, multilevel storage, and image recognition. Further, a novel Spiking Neural Network algorithm based on hardware characteristics is designed for the recognition task of Caltech 101 dataset and multiple features of the images are successfully extracted with higher accuracy (97.92%) of the recognition task from the multi-frequency curves of the optoelectronic synaptic devices. The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel broadband (from 365 to 940 nm) and multilevel storage optoelectronic synaptic thin‐film transistor (TFT) arrays are reported using the photosensitive conjugated polymer (poly[(9,9‐dioctylfluorenyl‐2,7‐diyl)‐co‐(bithiophene)], F8T2) sorted semiconducting single‐walled carbon nanotubes (sc‐SWCNTs) as channel materials. The broadband synaptic responses are inherited to absorption from both photosensitive F8T2 and sorted sc‐SWCNTs, and the excellent optoelectronic synaptic behaviors with 200 linearly increasing conductance states and long retention time > 10 3 s are attributed to the superior charge trapping at the AlO x dielectric layer grown by atomic layer deposition. Furthermore, the synaptic TFTs can achieve I On / I Off ratios up to 10 6 and optoelectronic synaptic plasticity with the low power consumption (59 aJ per single pulse), which can simulate not only basic biological synaptic functions but also optical write and electrical erase, multilevel storage, and image recognition. Further, a novel Spiking Neural Network algorithm based on hardware characteristics is designed for the recognition task of Caltech 101 dataset and multiple features of the images are successfully extracted with higher accuracy (97.92%) of the recognition task from the multi‐frequency curves of the optoelectronic synaptic devices. The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel broadband (from 365 to 940 nm) and multilevel storage optoelectronic synaptic thin-film transistor (TFT) arrays are reported using the photosensitive conjugated polymer (poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-(bithiophene)], F8T2) sorted semiconducting single-walled carbon nanotubes (sc-SWCNTs) as channel materials. The broadband synaptic responses are inherited to absorption from both photosensitive F8T2 and sorted sc-SWCNTs, and the excellent optoelectronic synaptic behaviors with 200 linearly increasing conductance states and long retention time > 103 s are attributed to the superior charge trapping at the AlOx dielectric layer grown by atomic layer deposition. Furthermore, the synaptic TFTs can achieve IOn/IOff ratios up to 106 and optoelectronic synaptic plasticity with the low power consumption (59 aJ per single pulse), which can simulate not only basic biological synaptic functions but also optical write and electrical erase, multilevel storage, and image recognition. Further, a novel Spiking Neural Network algorithm based on hardware characteristics is designed for the recognition task of Caltech 101 dataset and multiple features of the images are successfully extracted with higher accuracy (97.92%) of the recognition task from the multi-frequency curves of the optoelectronic synaptic devices. The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel broadband (from 365 to 940 nm) and multilevel storage optoelectronic synaptic thin‐film transistor (TFT) arrays are reported using the photosensitive conjugated polymer (poly[(9,9‐dioctylfluorenyl‐2,7‐diyl)‐co‐(bithiophene)], F8T2) sorted semiconducting single‐walled carbon nanotubes (sc‐SWCNTs) as channel materials. The broadband synaptic responses are inherited to absorption from both photosensitive F8T2 and sorted sc‐SWCNTs, and the excellent optoelectronic synaptic behaviors with 200 linearly increasing conductance states and long retention time > 103 s are attributed to the superior charge trapping at the AlOx dielectric layer grown by atomic layer deposition. Furthermore, the synaptic TFTs can achieve I On/I Off ratios up to 106 and optoelectronic synaptic plasticity with the low power consumption (59 aJ per single pulse), which can simulate not only basic biological synaptic functions but also optical write and electrical erase, multilevel storage, and image recognition. Further, a novel Spiking Neural Network algorithm based on hardware characteristics is designed for the recognition task of Caltech 101 dataset and multiple features of the images are successfully extracted with higher accuracy (97.92%) of the recognition task from the multi‐frequency curves of the optoelectronic synaptic devices. The authors selectively isolated from commercial SWCNTs using the photosensitive conjugated polymers, and the optoelectronic synaptic transistors are successfully constructed with low power consumption (59 aJ per spike) and excellent storage characteristics for simulation of neuromorphic vision systems (the accuracy ≈97.92%). Their SWCNT optoelectronic synaptic transistors do not require the introduction of any additional photosensitive materials and exhibit excellent optoelectronic properties. The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel broadband (from 365 to 940 nm) and multilevel storage optoelectronic synaptic thin‐film transistor (TFT) arrays are reported using the photosensitive conjugated polymer (poly[(9,9‐dioctylfluorenyl‐2,7‐diyl)‐co‐(bithiophene)], F8T2) sorted semiconducting single‐walled carbon nanotubes (sc‐SWCNTs) as channel materials. The broadband synaptic responses are inherited to absorption from both photosensitive F8T2 and sorted sc‐SWCNTs, and the excellent optoelectronic synaptic behaviors with 200 linearly increasing conductance states and long retention time > 103 s are attributed to the superior charge trapping at the AlOx dielectric layer grown by atomic layer deposition. Furthermore, the synaptic TFTs can achieve IOn/IOff ratios up to 106 and optoelectronic synaptic plasticity with the low power consumption (59 aJ per single pulse), which can simulate not only basic biological synaptic functions but also optical write and electrical erase, multilevel storage, and image recognition. Further, a novel Spiking Neural Network algorithm based on hardware characteristics is designed for the recognition task of Caltech 101 dataset and multiple features of the images are successfully extracted with higher accuracy (97.92%) of the recognition task from the multi‐frequency curves of the optoelectronic synaptic devices. The authors selectively isolated from commercial SWCNTs using the photosensitive conjugated polymers, and the optoelectronic synaptic transistors are successfully constructed with low power consumption (59 aJ per spike) and excellent storage characteristics for simulation of neuromorphic vision systems (the accuracy ≈97.92%). Their SWCNT optoelectronic synaptic transistors do not require the introduction of any additional photosensitive materials and exhibit excellent optoelectronic properties. |
| Author | Sui, Nianzi Liu, Zhaoxin Wu, Jinjian Ji, Yixi Li, Min Li, Jiaqi Li, Lain‐Jong Zheng, Fanyuan Zhao, Jianwen Shao, Shuangshuang |
| AuthorAffiliation | 3 School of Artificial Intelligence Xidian University Xi'an 710071 P. R. China 4 Department of Mechanical Engineering The University of Hong Kong Pokfulam Road Hong Kong 999077 P. R. China 1 School of Nano‐Tech and Nano‐Bionics University of Science and Technology of China No. 398 Ruoshui Road, Suzhou Industrial Park Suzhou Jiangsu Province 215123 P. R. China 2 Division of Nanodevices and Related Nanomaterials Suzhou Institute of Nano‐Tech and Nano‐Bionics Chinese Academy of Sciences No. 398 Ruoshui Road, Suzhou Industrial Park Suzhou Jiangsu Province 215123 P. R. China |
| AuthorAffiliation_xml | – name: 1 School of Nano‐Tech and Nano‐Bionics University of Science and Technology of China No. 398 Ruoshui Road, Suzhou Industrial Park Suzhou Jiangsu Province 215123 P. R. China – name: 2 Division of Nanodevices and Related Nanomaterials Suzhou Institute of Nano‐Tech and Nano‐Bionics Chinese Academy of Sciences No. 398 Ruoshui Road, Suzhou Industrial Park Suzhou Jiangsu Province 215123 P. R. China – name: 3 School of Artificial Intelligence Xidian University Xi'an 710071 P. R. China – name: 4 Department of Mechanical Engineering The University of Hong Kong Pokfulam Road Hong Kong 999077 P. R. China |
| Author_xml | – sequence: 1 givenname: Nianzi surname: Sui fullname: Sui, Nianzi organization: Chinese Academy of Sciences – sequence: 2 givenname: Yixi surname: Ji fullname: Ji, Yixi organization: Xidian University – sequence: 3 givenname: Min surname: Li fullname: Li, Min organization: Chinese Academy of Sciences – sequence: 4 givenname: Fanyuan surname: Zheng fullname: Zheng, Fanyuan organization: The University of Hong Kong – sequence: 5 givenname: Shuangshuang surname: Shao fullname: Shao, Shuangshuang organization: Chinese Academy of Sciences – sequence: 6 givenname: Jiaqi surname: Li fullname: Li, Jiaqi organization: Chinese Academy of Sciences – sequence: 7 givenname: Zhaoxin surname: Liu fullname: Liu, Zhaoxin organization: Xidian University – sequence: 8 givenname: Jinjian surname: Wu fullname: Wu, Jinjian email: jinjian.wu@mail.xidian.edu.cn organization: Xidian University – sequence: 9 givenname: Jianwen surname: Zhao fullname: Zhao, Jianwen email: jwzhao2011@sinano.ac.cn organization: Chinese Academy of Sciences – sequence: 10 givenname: Lain‐Jong orcidid: 0000-0002-4059-7783 surname: Li fullname: Li, Lain‐Jong email: lanceli1@hku.hk organization: The University of Hong Kong |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38828719$$D View this record in MEDLINE/PubMed |
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| Keywords | flexible optoelectronic synaptic devices multilevel storage spiking neural network broadband response photosensitive conjugated polymer |
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| Snippet | The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel broadband... Abstract The development of neuromorphic optoelectronic systems opens up the possibility of the next generation of artificial vision. In this work, the novel... |
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| SubjectTerms | Arrays Brain broadband response Carbon flexible optoelectronic synaptic devices Light multilevel storage Neural networks photosensitive conjugated polymer Polymers Power spiking neural network Transistors |
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| Title | Photoprogrammed Multifunctional Optoelectronic Synaptic Transistor Arrays Based on Photosensitive Polymer‐Sorted Semiconducting Single‐Walled Carbon Nanotubes for Image Recognition |
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