ZnO-SnO2/WO3-x heterojunction artificial synapse for realization and integration of multiple biological cognitive functions
In current memristor-based neuromorphic computing research, several studies face the challenge of realizing only a single function at a time or having isolated functions. This limitation is particularly evident when simulating biological cognition, as the overall synergy between multiple cognitive f...
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| Format: | Article |
| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | International Journal of Extreme Manufacturing |
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| Online Access: | https://doi.org/10.1088/2631-7990/addf1e |
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| author | Pengfei Sun Ruidong Li Haotian Meng Tao Sun Song Gao Yang Li |
| author_facet | Pengfei Sun Ruidong Li Haotian Meng Tao Sun Song Gao Yang Li |
| author_sort | Pengfei Sun |
| collection | DOAJ |
| description | In current memristor-based neuromorphic computing research, several studies face the challenge of realizing only a single function at a time or having isolated functions. This limitation is particularly evident when simulating biological cognition, as the overall synergy between multiple cognitive functions is difficult to represent. In this work, a high-performance heterojunction memristor is presented at first. The memristor-based neural network and functional circuit are further implemented to realize and integrate multiple cognitive functions. Specifically, the proposed photoelectric memristor has the structure of Ag/ZnO-SnO _2 /WO _3-x /ITO, it exhibits various synaptic behaviors under external modulations, which are characterized by good stability and repeatability. Based on this device, a neural network is built to realize the basic recognition function in biological cognition. The recognition results are translated into different labelled voltage signals and subsequently fed into a memristor-based functional circuit. By leveraging memory characteristics and tunable conductance of the memristor, and controlling the specific circuit functionalities, the input signals are processed to produce different outputs representing various cognitive functions. This methodology allows the realization and integration of recognition, memory, learning, association, relearning, and forgetting into one single system, thereby enabling a more comprehensive and authentic simulation of biological cognition. This work presents a novel memristor and a method for achieving and integrating multiple neuromorphic computing functions within a single system, providing a successful example for achieving complete biological function. |
| format | Article |
| id | doaj-art-f31ce70f851a4b829e52b7eb02b0f6d1 |
| institution | OA Journals |
| issn | 2631-7990 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | International Journal of Extreme Manufacturing |
| spelling | doaj-art-f31ce70f851a4b829e52b7eb02b0f6d12025-08-20T02:35:01ZengIOP PublishingInternational Journal of Extreme Manufacturing2631-79902025-01-017505550510.1088/2631-7990/addf1eZnO-SnO2/WO3-x heterojunction artificial synapse for realization and integration of multiple biological cognitive functionsPengfei Sun0Ruidong Li1Haotian Meng2https://orcid.org/0000-0001-5869-8964Tao Sun3Song Gao4https://orcid.org/0000-0001-9410-3040Yang Li5https://orcid.org/0000-0001-5260-5157School of Information Science and Engineering, University of Jinan , Jinan 250022, People’s Republic of ChinaShandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Co. , Ltd., Jinnan 250101, People’s Republic of ChinaSchool of Information Science and Engineering, University of Jinan , Jinan 250022, People’s Republic of ChinaAcademy of Intelligent Innovation, Shandong University , Jinan 250101, People’s Republic of ChinaSchool of Information Science and Engineering, University of Jinan , Jinan 250022, People’s Republic of ChinaSchool of Integrated Circuits, Shandong University , Jinan 250100, People’s Republic of China; Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Co. , Ltd., Jinnan 250101, People’s Republic of ChinaIn current memristor-based neuromorphic computing research, several studies face the challenge of realizing only a single function at a time or having isolated functions. This limitation is particularly evident when simulating biological cognition, as the overall synergy between multiple cognitive functions is difficult to represent. In this work, a high-performance heterojunction memristor is presented at first. The memristor-based neural network and functional circuit are further implemented to realize and integrate multiple cognitive functions. Specifically, the proposed photoelectric memristor has the structure of Ag/ZnO-SnO _2 /WO _3-x /ITO, it exhibits various synaptic behaviors under external modulations, which are characterized by good stability and repeatability. Based on this device, a neural network is built to realize the basic recognition function in biological cognition. The recognition results are translated into different labelled voltage signals and subsequently fed into a memristor-based functional circuit. By leveraging memory characteristics and tunable conductance of the memristor, and controlling the specific circuit functionalities, the input signals are processed to produce different outputs representing various cognitive functions. This methodology allows the realization and integration of recognition, memory, learning, association, relearning, and forgetting into one single system, thereby enabling a more comprehensive and authentic simulation of biological cognition. This work presents a novel memristor and a method for achieving and integrating multiple neuromorphic computing functions within a single system, providing a successful example for achieving complete biological function.https://doi.org/10.1088/2631-7990/addf1eoptoelectronic deviceoxide heterojunction memristorneuromorphic computingmultiple biological cognitive functionslow-power consumption system |
| spellingShingle | Pengfei Sun Ruidong Li Haotian Meng Tao Sun Song Gao Yang Li ZnO-SnO2/WO3-x heterojunction artificial synapse for realization and integration of multiple biological cognitive functions International Journal of Extreme Manufacturing optoelectronic device oxide heterojunction memristor neuromorphic computing multiple biological cognitive functions low-power consumption system |
| title | ZnO-SnO2/WO3-x heterojunction artificial synapse for realization and integration of multiple biological cognitive functions |
| title_full | ZnO-SnO2/WO3-x heterojunction artificial synapse for realization and integration of multiple biological cognitive functions |
| title_fullStr | ZnO-SnO2/WO3-x heterojunction artificial synapse for realization and integration of multiple biological cognitive functions |
| title_full_unstemmed | ZnO-SnO2/WO3-x heterojunction artificial synapse for realization and integration of multiple biological cognitive functions |
| title_short | ZnO-SnO2/WO3-x heterojunction artificial synapse for realization and integration of multiple biological cognitive functions |
| title_sort | zno sno2 wo3 x heterojunction artificial synapse for realization and integration of multiple biological cognitive functions |
| topic | optoelectronic device oxide heterojunction memristor neuromorphic computing multiple biological cognitive functions low-power consumption system |
| url | https://doi.org/10.1088/2631-7990/addf1e |
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