Imaging electrostatic potential profiles induced by a patterned gate in the quantum Hall regime
ORAL
Abstract
Monolayer graphene has been experimentally demonstrated as an ultra-clean platform to realize
robust integer and fractional quantum Hall effect. Although such quantum Hall states in graphene
systems have been intensively studied through multiple experimental probes, the technique of
isolating and trapping of the exotic quasiparticles in the quantum Hall regime is still lacking. Here,
we use AFM-based etching to pattern an array of holes in a few-layer graphite flake, which serves
as a bottom gate of a monolayer graphene. With an additional un-patterned graphite bottom gate,
we are able to realize an electrostatic potential well around the hole area in the monolayer
graphene. By performing STM measurements on the graphene layer, we can quantify the real-
space electrostatic potential distribution of the tunable potential well. Our experiment shows a
promising method to image trapped particles and quasiparticles in highly tunable graphene devices
and might pave the way for observation and manipulation of anyons.
robust integer and fractional quantum Hall effect. Although such quantum Hall states in graphene
systems have been intensively studied through multiple experimental probes, the technique of
isolating and trapping of the exotic quasiparticles in the quantum Hall regime is still lacking. Here,
we use AFM-based etching to pattern an array of holes in a few-layer graphite flake, which serves
as a bottom gate of a monolayer graphene. With an additional un-patterned graphite bottom gate,
we are able to realize an electrostatic potential well around the hole area in the monolayer
graphene. By performing STM measurements on the graphene layer, we can quantify the real-
space electrostatic potential distribution of the tunable potential well. Our experiment shows a
promising method to image trapped particles and quasiparticles in highly tunable graphene devices
and might pave the way for observation and manipulation of anyons.
*This work is supported by ONR, MURI, ARO-MURI, NSF-DMR.
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Presenters
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Haotan Han
- Princeton University