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Wrinkles, Ridges, Miura-Ori, and Moiré Patterns in MoSe 2 Using Neural Networks.

Anikeya AdityaAnkit MishraNitish BaradwajKen-Ichi NomuraAiichiro NakanoPriya D VashishtaRajiv K Kalia
Published in: The journal of physical chemistry letters (2023)
Effects of lateral compression on out-of-plane deformation of two-dimensional MoSe 2 layers are investigated. A MoSe 2 monolayer develops periodic wrinkles under uniaxial compression and Miura-Ori patterns under biaxial compression. When a flat MoSe 2 monolayer is placed on top of a wrinkled MoSe 2 layer, the van der Waals (vdW) interaction transforms wrinkles into ridges and generates mixed 2H and 1T phases and chain-like defects. Under a biaxial strain, the vdW interaction induces regions of Miura-Ori patterns in bilayers. Strained systems analyzed using a convolutional neural network show that the compressed system consists of semiconducting 2H and metallic 1T phases. The energetics, mechanical response, defect structure, and dynamics are analyzed as bilayers undergo wrinkle-ridge transformations under uniaxial compression and moiré transformations under biaxial compression. Our results indicate that in-plane compression can induce self-assembly of out-of-plane metasurfaces with controllable semiconducting and metallic phases and moiré patterns with unique optoelectronic properties.
Keyphrases
  • convolutional neural network
  • neural network
  • machine learning
  • mass spectrometry
  • atomic force microscopy