Abstract

Van der Waals heterostructures are comprised of stacked atomically thin two-dimensional crystals and serve as novel materials providing unprecedented properties. However, the random natures in positions and shapes of exfoliated two-dimensional crystals have required the repetitive manual tasks of optical microscopy-based searching and mechanical transferring, thereby severely limiting the complexity of heterostructures. To solve the problem, here we develop a robotic system that searches exfoliated two-dimensional crystals and assembles them into superlattices inside the glovebox. The system can autonomously detect 400 monolayer graphene flakes per hour with a small error rate (<7%) and stack four cycles of the designated two-dimensional crystals per hour with few minutes of human intervention for each stack cycle. The system enabled fabrication of the superlattice consisting of 29 alternating layers of the graphene and the hexagonal boron nitride. This capacity provides a scalable approach for prototyping a variety of van der Waals superlattices.

Highlights

  • Gauss filter Mean filter Convert from RGB to HSV Threshold imageMorphology operation i0 Y j 200 Y = 600 1501000 1500 X k lMonolayer graphene m n oMonolayer graphene pTarget material q 600Monolayer graphene Bilayer graphene Trilayer graphene Monolayer MoS2 Bilayer MoS2 Trilayer MoS2

  • To solve the problem we report on the development of an autonomous robotic system for the assembly of van der Waals (vdW) heterostructures, which we refer to as a 2D materials manufacturing system (2DMMS)

  • The design is transferred to the stamping apparatus, and robots directed by the computervision algorithm assemble the vdW heterostructures layer by layer onto a polymer stamp through the vdW force (Supplementary Movies 3–5)

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Summary

Results

The automated high-speed optical microscope with motorized XY scanning stage scans the surfaces of SiO2/Si chips, the optical microscope images are analyzed by computer-vision algorithm, and discerns whether targeted 2D crystals are present in the image or not (Supplementary Movie 1). The optical microscope image was analyzed by the computer-vision algorithm, and XYZ stage was automatically navigated to align the targeted 2D crystals (Supplementary Movie 5). IBHG;S;Vðx; yÞ is the background image of SiO2/Si without 2D crystals (recorded manually before starting the automated search), and CH,S,V and DH,S,V are the parameters (Supplementary Table 3) adjusted by the procedure described in the Methods section. This procedure extracts the region of atomically thin 2D crystals (Fig. 4g). By taking the intersection between the color-threshold and entropy-threshold regions

Background
Design window c
Discussion
Methods
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