Advancing Scalability & Process Benchmarking in Mechanical Exfoliation of Superconducting 2D Materials
Date: Wed, December 10, 2025
Time: 4:00pm - 5:00pm
Location: Holmes Hall 389; online available, check your email or contact the ECE office.
Speaker: Anthony Gasbarro, candidate for PhD, advisor: Dr. Victor Lubecke
ECE Graduate Students: This will count towards your seminar credit.
Abstract
Mechanical exfoliation remains the most accessible route to atomically pristine, large-area, single-crystal 2D flakes for superconducting quantum devices, multidimensional photodetectors, and biosensing systems. However, the process is slow, operator-dependent, prone to variability, and often guided by heuristics lacking practical empirical validation. This work introduces an end-to-end framework to enable the shift for mechanical exfoliation procedures from a manual, artisanal procedure into a measurable, optimizable process by presenting the following: (i) a low-cost, open, and electronically controlled instrument that enforces adhesive peel kinematics and normalizes tape- removal speed across angles; (ii) a GPU-accelerated pipeline using a machine learning segmentation model to perform optical-classification for high-throughput 2D material flake thickness mapping; and (iii) a systematic study isolating peel angle and speed to quantify yield-residue trade-offs using computer vision techniques to normalize comparisons. Taken together, the open instrument, software, and data-driven optimization testing framework provide practical guidance for reproducible exfoliation, and a scalable baseline for benchmarking materials, substrates, and future automation.
Biography
Anthony Gasbarro was a Navy Nuclear Electronics Technician from 2011-2017. In 2017, He received his B.S. in Nuclear Engineering Technology from Excelsior University. He received his M.S in Electrical Engineering in 2020. He is currently a PhD candidate in the Department of Electrical and Computer Engineering at the University of Hawaii at Manoa and an Electronics Engineer at Naval Information Warfare Center Pacific. His research interests are quantum computing, superconducting nanomaterials, and machine learning.