Automated Nanoscale Absolute Accuracy Alignment System for Transfer Printing
Author(s) -
John McPhillimy,
Dimitars Jevtics,
Benoit Guilhabert,
Charalambos Klitis,
Antonio Hurtado,
Marc Sorel,
Martin D. Dawson,
Michael J. Strain
Publication year - 2020
Publication title -
acs applied nano materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.227
H-Index - 29
ISSN - 2574-0970
DOI - 10.1021/acsanm.0c02224
Subject(s) - offset (computer science) , computer science , photonics , chip , scalability , nanoscopic scale , automation , materials science , transfer printing , integrated circuit , scaling , computer hardware , optoelectronics , nanotechnology , engineering , telecommunications , mechanical engineering , geometry , mathematics , database , composite material , programming language
The heterogeneous integration of micro- and nanoscale devices with on-chip circuits and waveguide platforms is a key enabling technology, with wide-ranging applications in areas including telecommunications, quantum information processing, and sensing. Pick and place integration with absolute positional accuracy at the nanoscale has been previously demonstrated for single proof-of-principle devices. However, to enable scaling of this technology for realization of multielement systems or high throughput manufacturing, the integration process must be compatible with automation while retaining nanoscale accuracy. In this work, an automated transfer printing process is realized by using a simple optical microscope, computer vision, and high accuracy translational stage system. Automatic alignment using a cross-correlation image processing method demonstrates absolute positional accuracy of transfer with an average offset of <40 nm (3σ < 390 nm) for serial device integration of both thin film silicon membranes and single nanowire devices. Parallel transfer of devices across a 2 × 2 mm 2 area is demonstrated with an average offset of <30 nm (3σ < 705 nm). Rotational accuracy better than 45 mrad is achieved for all device variants. Devices can be selected and placed with high accuracy on a target substrate, both from lithographically defined positions on their native substrate or from a randomly distributed population. These demonstrations pave the way for future scalable manufacturing of heterogeneously integrated chip systems.
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