Hybrid Integrated Lead-Free Perovskite/Graphene Array Toward High-Responsivity In-Sensor Computing
Perovskite are expected to construct vision neuromorphic systems due to its unique photoelectric properties. However, the ion migration in perovskite films, as well as the toxicity of lead element limit their applications. Here we demonstrated a lead-free perovskite-graphene hybrid (PGH) integrated device via low temperature method. This hybrid structure decouples vertical carrier extraction under built-in electric field and horizontal carrier transport under applied high electric filed, which enhances carrier transport efficiency while alleviating ion migration issues. As a result, a responsivity of 199 A/W and a detectivity of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${0}.{53}\times {10} ^{{10}}$ </tex-math></inline-formula> Jones were achieved under 405 nm light illumination (power intensity: <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${0}.{24}\times {10} ^{\text {- {2}}}$ </tex-math></inline-formula> nW/<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>m<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{{2}}\text {)}$ </tex-math></inline-formula>. Furthermore, the ground-state current drift caused by charge trapping/detrapping in PGH band alignment facilitates in-situ preprocessing of visual information. A neuromorphic vision system with a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${6}\times {6}$ </tex-math></inline-formula> sensor array was constructed, and it showed a significantly accuracy enhancement (69.2% to 89.5%) in recognition tasks. This work contributes to the development of high-performance perovskite-based neuromorphic devices.
Authors
- Jiahe Zhang
- He Tian (ORCID: https://orcid.org/0000-0001-7328-2182)
- Ken Qin (ORCID: https://orcid.org/0000-0002-5908-0258)
- Yi Yang (ORCID: https://orcid.org/0000-0002-1161-9488)
- Ze‐Shu Wang (ORCID: https://orcid.org/0009-0004-2639-1422)
- Tian‐Ling Ren (ORCID: https://orcid.org/0000-0002-7330-0544)
- Jiali Peng (ORCID: https://orcid.org/0000-0003-1179-9703)
- Xiangshun Geng (ORCID: https://orcid.org/0000-0003-3170-7175)
- Guan‐Hua Dun (ORCID: https://orcid.org/0000-0003-1016-0350)
- Dan Xie
- Ruolong Zhou
Institutions
- Tsinghua University (CN)
Publication Details
- Journal
- IEEE Electron Device Letters
- Published
- 2024-09-23
- DOI
- https://doi.org/10.1109/led.2024.3465790
- Citations
- 1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.21
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- National Key Research and Development Program of China