Modification of the Interlayer Coupling and Chemical Reactivity of Multilayer Graphene through Wrinkle Engineering

2021 ◽  
Vol 33 (7) ◽  
pp. 2506-2515
Author(s):  
Xinyu Huang ◽  
Wen Zhao ◽  
Chongyang Zhu ◽  
Xianjue Chen ◽  
Xu Han ◽  
...  
2017 ◽  
Vol 121 (46) ◽  
pp. 26034-26043 ◽  
Author(s):  
Guorui Wang ◽  
Xiaoli Li ◽  
Yanlei Wang ◽  
Zhiyue Zheng ◽  
Zhaohe Dai ◽  
...  

2018 ◽  
Vol 20 (26) ◽  
pp. 17899-17908 ◽  
Author(s):  
Huynh V. Phuc ◽  
Nguyen N. Hieu ◽  
Bui D. Hoi ◽  
Chuong V. Nguyen

In this work, using density functional theory we investigated systematically the electronic properties and Schottky barrier modulation in a multilayer graphene/bilayer-GaSe heterostructure by varying the interlayer spacing and by applying an external electric field.


2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
S. C. Bodepudi ◽  
X. Wang ◽  
A. P. Singh ◽  
S. Pramanik

Chemical Vapor Deposition grown multilayer graphene (MLG) exhibits large out-of-plane magnetoresistance due to interlayer magnetoresistance (ILMR) effect. It is essential to identify the factors that influence this effect in order to explore its potential in magnetic sensing and data storage applications. It has been demonstrated before that the ILMR effect is sensitive to the interlayer coupling and the orientation of the magnetic field with respect to the out-of-plane (c-axis) direction. In this work, we investigate the role of MLG thickness on ILMR effect. Our results show that the magnitude of ILMR effect increases with the number of graphene layers in the MLG stack. Surprisingly, thicker devices exhibit field induced resistance switching by a factor of at least ~107. This effect persists even at room temperature and to our knowledge such large magnetoresistance values have not been reported before in the literature at comparable fields and temperatures. In addition, an oscillatory MR effect is observed at higher field values. A physical explanation of this effect is presented, which is consistent with our experimental scenario.


Author(s):  
A. M. Bradshaw

X-ray photoelectron spectroscopy (XPS or ESCA) was not developed by Siegbahn and co-workers as a surface analytical technique, but rather as a general probe of electronic structure and chemical reactivity. The method is based on the phenomenon of photoionisation: The absorption of monochromatic radiation in the target material (free atoms, molecules, solids or liquids) causes electrons to be injected into the vacuum continuum. Pseudo-monochromatic laboratory light sources (e.g. AlKα) have mostly been used hitherto for this excitation; in recent years synchrotron radiation has become increasingly important. A kinetic energy analysis of the so-called photoelectrons gives rise to a spectrum which consists of a series of lines corresponding to each discrete core and valence level of the system. The measured binding energy, EB, given by EB = hv−EK, where EK is the kineticenergy relative to the vacuum level, may be equated with the orbital energy derived from a Hartree-Fock SCF calculation of the system under consideration (Koopmans theorem).


Author(s):  
Thomas W. Shattuck ◽  
James R. Anderson ◽  
Neil W. Tindale ◽  
Peter R. Buseck

Individual particle analysis involves the study of tens of thousands of particles using automated scanning electron microscopy and elemental analysis by energy-dispersive, x-ray emission spectroscopy (EDS). EDS produces large data sets that must be analyzed using multi-variate statistical techniques. A complete study uses cluster analysis, discriminant analysis, and factor or principal components analysis (PCA). The three techniques are used in the study of particles sampled during the FeLine cruise to the mid-Pacific ocean in the summer of 1990. The mid-Pacific aerosol provides information on long range particle transport, iron deposition, sea salt ageing, and halogen chemistry.Aerosol particle data sets suffer from a number of difficulties for pattern recognition using cluster analysis. There is a great disparity in the number of observations per cluster and the range of the variables in each cluster. The variables are not normally distributed, they are subject to considerable experimental error, and many values are zero, because of finite detection limits. Many of the clusters show considerable overlap, because of natural variability, agglomeration, and chemical reactivity.


Sign in / Sign up

Export Citation Format

Share Document