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A review on accelerated development of skin-like MXene electrodes: from experimental to machine learning.

Romy GargNikhil Ram PatraSoumyajit SamalShubham BabbarKaushik Parida
Published in: Nanoscale (2023)
Foreshadowing future needs has catapulted the progress of skin-like electronic devices for human-machine interactions. These devices possess human skin-like properties such as stretchability, self-healability, transparency, biocompatibility, and wearability. This review highlights the recent progress in a promising material, MXenes, to realize soft, deformable, skin-like electrodes. Various structural designs, fabrication strategies, and rational guidelines adopted to realize MXene-based skin-like electrodes are outlined. We explicitly discussed machine learning-based material informatics to understand and predict the properties of MXenes. Finally, an outlook on the existing challenges and the future roadmap to realize soft skin-like MXene electrodes to facilitate technological advances in the next-generation human-machine interactions has been described.
Keyphrases
  • machine learning
  • soft tissue
  • wound healing
  • endothelial cells
  • deep learning
  • reduced graphene oxide
  • carbon nanotubes
  • current status
  • big data
  • pluripotent stem cells
  • clinical practice
  • gold nanoparticles