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Multilevel design and construction in nanomembrane rolling for three-dimensional angle-sensitive photodetection

Author

Listed:
  • Ziyu Zhang

    (Fudan University)

  • Binmin Wu

    (Fudan University)

  • Yang Wang

    (Fudan University)

  • Tianjun Cai

    (Fudan University)

  • Mingze Ma

    (Fudan University)

  • Chunyu You

    (Fudan University)

  • Chang Liu

    (Fudan University)

  • Guobang Jiang

    (Fudan University)

  • Yuhang Hu

    (Fudan University)

  • Xing Li

    (Fudan University)

  • Xiang-Zhong Chen

    (Fudan University
    Yiwu Research Institute of Fudan University
    Fudan University)

  • Enming Song

    (Fudan University
    Fudan University)

  • Jizhai Cui

    (Fudan University
    Fudan University)

  • Gaoshan Huang

    (Fudan University
    Yiwu Research Institute of Fudan University
    Fudan University)

  • Suwit Kiravittaya

    (Chulalongkorn University)

  • Yongfeng Mei

    (Fudan University
    Fudan University
    Yiwu Research Institute of Fudan University
    Fudan University)

Abstract

Releasing pre-strained two-dimensional nanomembranes to assemble on-chip three-dimensional devices is crucial for upcoming advanced electronic and optoelectronic applications. However, the release process is affected by many unclear factors, hindering the transition from laboratory to industrial applications. Here, we propose a quasistatic multilevel finite element modeling to assemble three-dimensional structures from two-dimensional nanomembranes and offer verification results by various bilayer nanomembranes. Take Si/Cr nanomembrane as an example, we confirm that the three-dimensional structural formation is governed by both the minimum energy state and the geometric constraints imposed by the edges of the sacrificial layer. Large-scale, high-yield fabrication of three-dimensional structures is achieved, and two distinct three-dimensional structures are assembled from the same precursor. Six types of three-dimensional Si/Cr photodetectors are then prepared to resolve the incident angle of light with a deep neural network model, opening up possibilities for the design and manufacturing methods of More-than-Moore-era devices.

Suggested Citation

  • Ziyu Zhang & Binmin Wu & Yang Wang & Tianjun Cai & Mingze Ma & Chunyu You & Chang Liu & Guobang Jiang & Yuhang Hu & Xing Li & Xiang-Zhong Chen & Enming Song & Jizhai Cui & Gaoshan Huang & Suwit Kiravi, 2024. "Multilevel design and construction in nanomembrane rolling for three-dimensional angle-sensitive photodetection," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47405-2
    DOI: 10.1038/s41467-024-47405-2
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    References listed on IDEAS

    as
    1. Wonho Lee & Yuan Liu & Yongjun Lee & Bhupendra K. Sharma & Sachin M. Shinde & Seong Dae Kim & Kewang Nan & Zheng Yan & Mengdi Han & Yonggang Huang & Yihui Zhang & Jong-Hyun Ahn & John A. Rogers, 2018. "Two-dimensional materials in functional three-dimensional architectures with applications in photodetection and imaging," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
    2. Farshid Ashtiani & Alexander J. Geers & Firooz Aflatouni, 2022. "An on-chip photonic deep neural network for image classification," Nature, Nature, vol. 606(7914), pages 501-506, June.
    3. Xueping Cui & Zhizhi Kong & Enlai Gao & Dazhen Huang & Yang Hao & Hongguang Shen & Chong-an Di & Zhiping Xu & Jian Zheng & Daoben Zhu, 2018. "Rolling up transition metal dichalcogenide nanoscrolls via one drop of ethanol," Nature Communications, Nature, vol. 9(1), pages 1-7, December.
    4. Jizhai Cui & Tian-Yun Huang & Zhaochu Luo & Paolo Testa & Hongri Gu & Xiang-Zhong Chen & Bradley J. Nelson & Laura J. Heyderman, 2019. "Nanomagnetic encoding of shape-morphing micromachines," Nature, Nature, vol. 575(7781), pages 164-168, November.
    5. Borui Xu & Xinyuan Zhang & Ziao Tian & Di Han & Xingce Fan & Yimeng Chen & Zengfeng Di & Teng Qiu & Yongfeng Mei, 2019. "Microdroplet-guided intercalation and deterministic delamination towards intelligent rolling origami," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
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