Abstract
We present a novel method for extracting two-dimensional (2D) conductivity profiles from large electrochemical potential datasets acquired by scanning tunneling potentiometry of a 2D conductor. The method consists of a data preprocessing procedure to reduce/eliminate noise and a numerical conductivity reconstruction. The preprocessing procedure employs an inverse consistent image registration method to align the forward and backward scans of the same line for each image line followed by a total variation (TV) based image restoration method to obtain a (nearly) noise-free potential from the aligned scans. The preprocessed potential is then used for numerical conductivity reconstruction, based on a TV model solved by accelerated alternating direction method of multiplier. The method is demonstrated on a measurement of the grain boundary of a monolayer graphene, yielding a nearly 10:1 ratio for the grain boundary resistivity over bulk resistivity.
Original language | English |
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Article number | 083702 |
Journal | Review of Scientific Instruments |
Volume | 87 |
Issue number | 8 |
DOIs | |
State | Published - Aug 1 2016 |
Funding
H. Zhang and X. Li are partially supported by the University of Florida Informatics Institute Seed fund, and Y. Chen is partially supported by the NSF Grant No. DMS-1319050. The experimental portion of this research was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility. The authors would like to thank Professor X. Ye from the Department of Mathematics at the Georgia State University for providing his inverse consistent deformable registration code to us.