Neuromorphic Devices

Neuromorphic Devices is a class of electronic systems that emulate the structure and function of biological neural networks, distinguished by their ability to process information using physical mechanisms akin to synaptic and neuronal dynamics in the brain.

5.3K

Publications

367.2K

Citations

16.7K

Authors

2.3K

Institutions

Publications per year

2017–2026

4K

Authors

16.7K

  1. GI
    Giacomo Indiveri

    ETH Zurich, Switzerland

    116 publications · 10.7K citations

    44

    h-index

  2. SY
    Shimeng Yu

    Georgia Institute of Technology, United States

    50 publications · 9.2K citations

    36

    h-index

  3. QW
    Qing Wan

    Nanjing University, China

    53 publications · 4.9K citations

    34

    h-index

  4. SK
    Sungjun Kim

    Dongguk University, South Korea

    65 publications · 2.5K citations

    33

    h-index

  5. SH
    Su‐Ting Han

    Shenzhen University, China

    43 publications · 4K citations

    33

    h-index

1–5 of 16.7K

Venues

  1. Nature Communications

    170 publications · 23.5K citations

    85

    h-index

  2. Advanced Functional Materials

    220 publications · 21.2K citations

    83

    h-index

  3. Advanced Materials

    162 publications · 19.7K citations

    77

    h-index

  4. ACS Applied Materials & Interfaces

    163 publications · 9.5K citations

    59

    h-index

  5. Advanced Electronic Materials

    152 publications · 8.8K citations

    53

    h-index

1–5