Two-dimensional materials for bio-realistic neuronal computing networks

Vinod K. Sangwan*, Stephanie E. Liu, Amit R. Trivedi, Mark C. Hersam*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

5 Scopus citations


Two-dimensional (2D) van der Waals materials have found broad utility in a diverse range of applications including electronics, optoelectronics, renewable energy, and quantum information technologies. Meanwhile, exponentially growing digital data coupled with the ubiquity of artificial intelligence algorithms have generated significant interest in edge neuromorphic computing as an alternative to centralized cloud computing. The drive to incorporate neuroscience principles into computing hardware is motivated by the low power consumption, parallel processing, and reconfigurability of the human brain. The diverse library of 2D materials with atomic-level thicknesses, exceptional electrostatic tunability, and integration versatility is particularly well-suited for realizing bio-realistic synaptic and neuronal functionality. Here, we summarize past and present work in this field and outline the frontier challenges that have not yet been overcome. We also delineate potential solutions and suggest that the neuroscience principles of criticality and synchrony have the potential to inspire breakthrough applications of 2D materials in neuronal computing networks.

Original languageEnglish (US)
Pages (from-to)4133-4152
Number of pages20
Issue number12
StatePublished - Dec 7 2022


  • artificial intelligence
  • layered materials
  • machine learning
  • neuromorphic computing
  • van der Waals heterojunction

ASJC Scopus subject areas

  • Materials Science(all)


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