AVS 66th International Symposium & Exhibition
    Applied Surface Science Division Thursday Sessions
       Session AS-ThP

Paper AS-ThP10
Probing the Electrical Double Layer by in situ X-ray Photoelectron Spectroscopy through a Carbon Nanotube-Strengthened Graphene Window

Thursday, October 24, 2019, 6:30 pm, Room Union Station B

Session: Applied Surface Science Poster Session
Presenter: Yunfeng Li, University of Maryland, College Park
Authors: P. Wang, University of Maryland, College Park
Y.F. Li, University of Maryland, College Park
L.N. Wang, University of Maryland, College Park
J. Klos, University of Maryland, College Park
Z.W. Peng, University of Maryland, College Park
N. Kim, University of Maryland, College Park
H. Bluhm, Lawrence Berkeley National Laboratory
K.J. Gaskell, University of Maryland, College Park
S.B. Lee, University of Maryland, College Park
B. Eichhorn, University of Maryland, College Park
Y.H. Wang, University of Maryland, College Park
Correspondent: Click to Email

A detailed description of the electrical double layer structure formed at the electrode-electrolyte interface is very important for both fundamental understanding in many electrochemical processes and further advancements in energy storage devices. However, the electrical double layer is deeply “buried” by the bulk electrolyte solution, leading to significant signal loss and low detection resolution when measuring the interface structure from the electrolyte side. Here, we report the fabrication of a novel transparent electrode made of a graphene-carbon nanotube hybrid membrane that allows us to detect the electrical double layer from the solid side of the electrode using X-ray photoelectron spectroscopy. The robust and ultrathin nature of the hybrid membrane enables the detection of different elements with excellent photoelectron signals. By in situ monitoring the concentration changes of cations and anions under different local electrical potentials, we experimentally decipher the chemical structure of the electrical double layer, which is consistent with theoretical predictions.