Scalable construction of quantum dot arrays using optical tweezers and deep learning

Martin Selin; Adrià Grabulosa; Johnny Moughames; Xavier Porte; Daniel Brunner; Giovanni Volpe

doi:10.1117/12.2593584

1 August 2021 Scalable construction of quantum dot arrays using optical tweezers and deep learning

Martin Selin, Adrià Grabulosa, Johnny Moughames, Xavier Porte, Daniel Brunner, Giovanni Volpe

Proceedings Volume 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021; 1180422 (2021) https://doi.org/10.1117/12.2593584
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States

Conference Poster

Abstract

We present a novel method for constructing quantum dot arrays using optical tweezers. By optically trapping 10 nm core-shell quantum dots we can position the quantum dots with submicron precision. The quantum dots are suspended in a resin (nanoscribe IP-G 780) which is then polymerized locally around the trapped quantum dot, fixating its position. The process of trapping and positioning is automated using a neural network to locate both free quantum dots and the position of quantum dots already in the array. The ability to locate the already positioned quantum dots is essential to achieving high precision and accuracy in the placement. Automation makes the process scalable and enables the manufacturing of large arrays. As a first step we demonstrate the construction of a 4x4 array of quantum dots.

Conference Presentation

Citation Download Citation

Martin Selin, Adrià Grabulosa, Johnny Moughames, Xavier Porte, Daniel Brunner, and Giovanni Volpe "Scalable construction of quantum dot arrays using optical tweezers and deep learning", Proc. SPIE 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021, 1180422 (1 August 2021); https://doi.org/10.1117/12.2593584

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