In-material physical computing based on reconfigurable microwire arrays via halide-ion segregation
Abstract Conventional computer systems based on the Von Neumann architecture rely on silicon transistors with binary states for information representation and processing. However, exploiting emerging materials’ intrinsic physical properties and dynamic behaviors offers a promising pathway for develo...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-60530-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849334306118303744 |
|---|---|
| author | Dengji Li Pengshan Xie Yuekun Yang Yunfan Wang Changyong Lan Yiyang Wei Jiachi Liao Bowen Li Zenghui Wu Quan Quan Yuxuan Zhang You Meng Mingqi Ding Yan Yan Yi Shen Weijun Wang Sai-Wing Tsang Shi-Jun Liang Feng Miao Johnny C. Ho |
| author_facet | Dengji Li Pengshan Xie Yuekun Yang Yunfan Wang Changyong Lan Yiyang Wei Jiachi Liao Bowen Li Zenghui Wu Quan Quan Yuxuan Zhang You Meng Mingqi Ding Yan Yan Yi Shen Weijun Wang Sai-Wing Tsang Shi-Jun Liang Feng Miao Johnny C. Ho |
| author_sort | Dengji Li |
| collection | DOAJ |
| description | Abstract Conventional computer systems based on the Von Neumann architecture rely on silicon transistors with binary states for information representation and processing. However, exploiting emerging materials’ intrinsic physical properties and dynamic behaviors offers a promising pathway for developing next-generation brain-inspired neuromorphic hardware. Here, we introduce a stable and controllable photoelectricity-induced halide-ion segregation effect in epitaxially grown mixed-halide perovskite CsPbBr1.5I1.5 microwire networks on mica, as confirmed by various in-situ measurements. The dynamic segregation and recovery processes show the reconfigurable, self-powered photoresponse, enabling non-volatile light information storage and precise modulation of optoelectronic properties. Furthermore, our microwire array successfully addressed a typical graphical neural network problem and an image restoration task without external circuits, underscoring the potential of in-material dynamics to achieve highly parallel and energy-efficient physical computing in the post-Moore era. |
| format | Article |
| id | doaj-art-7da029eb73be474cafff7b4ee8db7ea3 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-7da029eb73be474cafff7b4ee8db7ea32025-08-20T03:45:35ZengNature PortfolioNature Communications2041-17232025-07-0116111010.1038/s41467-025-60530-wIn-material physical computing based on reconfigurable microwire arrays via halide-ion segregationDengji Li0Pengshan Xie1Yuekun Yang2Yunfan Wang3Changyong Lan4Yiyang Wei5Jiachi Liao6Bowen Li7Zenghui Wu8Quan Quan9Yuxuan Zhang10You Meng11Mingqi Ding12Yan Yan13Yi Shen14Weijun Wang15Sai-Wing Tsang16Shi-Jun Liang17Feng Miao18Johnny C. Ho19Department of Materials Science and Engineering, City University of Hong KongDepartment of Materials Science and Engineering, City University of Hong KongInstitute of Brain-Inspired Intelligence, National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing UniversityDepartment of Materials Science and Engineering, City University of Hong KongState Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of ChinaState Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of ChinaDepartment of Materials Science and Engineering, City University of Hong KongDepartment of Materials Science and Engineering, City University of Hong KongDepartment of Materials Science and Engineering, City University of Hong KongDepartment of Materials Science and Engineering, City University of Hong KongDepartment of Materials Science and Engineering, City University of Hong KongDepartment of Materials Science and Engineering, City University of Hong KongDepartment of Materials Science and Engineering, City University of Hong KongDepartment of Materials Science and Engineering, City University of Hong KongDepartment of Materials Science and Engineering, City University of Hong KongDepartment of Materials Science and Engineering, City University of Hong KongDepartment of Materials Science and Engineering, City University of Hong KongInstitute of Brain-Inspired Intelligence, National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing UniversityInstitute of Brain-Inspired Intelligence, National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing UniversityDepartment of Materials Science and Engineering, City University of Hong KongAbstract Conventional computer systems based on the Von Neumann architecture rely on silicon transistors with binary states for information representation and processing. However, exploiting emerging materials’ intrinsic physical properties and dynamic behaviors offers a promising pathway for developing next-generation brain-inspired neuromorphic hardware. Here, we introduce a stable and controllable photoelectricity-induced halide-ion segregation effect in epitaxially grown mixed-halide perovskite CsPbBr1.5I1.5 microwire networks on mica, as confirmed by various in-situ measurements. The dynamic segregation and recovery processes show the reconfigurable, self-powered photoresponse, enabling non-volatile light information storage and precise modulation of optoelectronic properties. Furthermore, our microwire array successfully addressed a typical graphical neural network problem and an image restoration task without external circuits, underscoring the potential of in-material dynamics to achieve highly parallel and energy-efficient physical computing in the post-Moore era.https://doi.org/10.1038/s41467-025-60530-w |
| spellingShingle | Dengji Li Pengshan Xie Yuekun Yang Yunfan Wang Changyong Lan Yiyang Wei Jiachi Liao Bowen Li Zenghui Wu Quan Quan Yuxuan Zhang You Meng Mingqi Ding Yan Yan Yi Shen Weijun Wang Sai-Wing Tsang Shi-Jun Liang Feng Miao Johnny C. Ho In-material physical computing based on reconfigurable microwire arrays via halide-ion segregation Nature Communications |
| title | In-material physical computing based on reconfigurable microwire arrays via halide-ion segregation |
| title_full | In-material physical computing based on reconfigurable microwire arrays via halide-ion segregation |
| title_fullStr | In-material physical computing based on reconfigurable microwire arrays via halide-ion segregation |
| title_full_unstemmed | In-material physical computing based on reconfigurable microwire arrays via halide-ion segregation |
| title_short | In-material physical computing based on reconfigurable microwire arrays via halide-ion segregation |
| title_sort | in material physical computing based on reconfigurable microwire arrays via halide ion segregation |
| url | https://doi.org/10.1038/s41467-025-60530-w |
| work_keys_str_mv | AT dengjili inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT pengshanxie inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT yuekunyang inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT yunfanwang inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT changyonglan inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT yiyangwei inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT jiachiliao inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT bowenli inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT zenghuiwu inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT quanquan inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT yuxuanzhang inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT youmeng inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT mingqiding inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT yanyan inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT yishen inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT weijunwang inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT saiwingtsang inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT shijunliang inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT fengmiao inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation AT johnnycho inmaterialphysicalcomputingbasedonreconfigurablemicrowirearraysviahalideionsegregation |