2D Materials Powering Neuromorphic Intelligence (IMAGE)
Caption
- Two-dimensional materials enable energy-efficient neuromorphic computing through gate tuneable bandgaps, fast switching kinetics, and compatibility with spiking neural networks for adaptive learning.
- Emerging memory devices leveraging 2D materials—including resistive, ferroelectric, and phase-change systems—mimic synaptic plasticity to revolutionize neuromorphic architectures.
- Future advances in thin-film synthesis, defect engineering, and quantum-inspired designs will unlock scalable, sustainable 2D neuromorphic systems for healthcare, edge AI, and quantum computing.
Credit
Jamal Kazmi*, Waqas Ahmad, Muhammad Naqi, Yawar Abbas, Aumber Abbas, Peijian Wang*, Mohd Ambri Mohamed*, Federico Rosei*, Zhiming M. Wang*, Hongwei Song*.
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Credit must be given to the creator. Only noncommercial uses of the work are permitted. No derivatives or adaptations of the work are permitted.
License
CC BY-NC-ND