scholarly journals A carrier velocity model for electrical detection of gas molecules

2019 ◽  
Vol 10 ◽  
pp. 644-653 ◽  
Author(s):  
Ali Hosseingholi Pourasl ◽  
Sharifah Hafizah Syed Ariffin ◽  
Mohammad Taghi Ahmadi ◽  
Razali Ismail ◽  
Niayesh Gharaei
Keyword(s):  
Graphene Nanoribbons ◽  
Tight Binding ◽  
Medical Diagnostics ◽  
Molecular Adsorption ◽  
Adsorption Effect ◽  
Detection Range ◽  
Adsorption Effects ◽  
Proposed Model ◽  
Gas Molecules ◽  
Carrier Velocity

Nanomaterial-based sensors with high sensitivity, fast response and recovery time, large detection range, and high chemical stability are in immense demand for the detection of hazardous gas molecules. Graphene nanoribbons (GNRs) which have exceptional electrical, physical, and chemical properties can fulfil all of these requirements. The detection of gas molecules using gas sensors, particularly in medical diagnostics and safety applications, is receiving particularly high demand. GNRs exhibit remarkable changes in their electrical characteristics when exposed to different gases through molecular adsorption. In this paper, the adsorption effects of the target gas molecules (CO and NO) on the electrical properties of the armchair graphene nanoribbon (AGNR)-based sensor are analytically modelled. Thus, the energy dispersion relation of AGNR is developed considering the molecular adsorption effect using a tight binding (TB) method. The carrier velocity is calculated based on the density of states (DOS) and carrier concentration (n) to obtain I–V characteristics and to monitor its variation in the presence of the gas molecules. Furthermore, the I–V characteristics and energy band structure of the AGNR sensor are simulated using first principle calculations to investigate the gas adsorption effects on these properties. To ensure the accuracy of the proposed model, the I–V characteristics of the AGNR sensor that are simulated based both on the proposed model and first principles calculations are compared, and an acceptable agreement is achieved.

scholarly journals Accurate six-band nearest-neighbor tight-binding model for the π-bands of bulk graphene and graphene nanoribbons

2011 ◽  
Vol 109 (10) ◽  
pp. 104304 ◽  
Author(s):  
Timothy B. Boykin ◽  
Mathieu Luisier ◽  
Gerhard Klimeck ◽  
Xueping Jiang ◽  
Neerav Kharche ◽  
...  
Keyword(s):  
Nearest Neighbor ◽  
Graphene Nanoribbons ◽  
Tight Binding ◽  
Tight Binding Model ◽  
Binding Model

Exciton effects in strained armchair graphene nanoribbons

2016 ◽  
Vol 30 (06) ◽  
pp. 1650021 ◽  
Author(s):  
Yonglei Jia ◽  
Junlin Liu
Keyword(s):  
Binding Energy ◽  
Excitation Energy ◽  
Graphene Nanoribbons ◽  
Tight Binding ◽  
Uniaxial Strain ◽  
Exciton Binding Energy ◽  
Coulomb Interactions ◽  
Optomechanical Systems ◽  
Armchair Graphene Nanoribbons ◽  
Armchair Graphene

The exciton effects in 1-nm-wide armchair graphene nanoribbons (AGNRs) under the uniaxial strain were studied within the nonorthogonal tight-binding (TB) model, supplemented by the long-range Coulomb interactions. The obtained results show that both the excitation energy and exciton binding energy are modulated by the uniaxial strain. The variation of these energies depends on the ribbon family. In addition, the results show that the variation of the exciton binding energy is much weaker than the variation of excitation energy. Our results provide new guidance for the design of optomechanical systems based on graphene nanoribbons.

scholarly journals One-dimensional confinement and width-dependent bandgap formation in epitaxial graphene nanoribbons

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Hrag Karakachian ◽  
T. T. Nhung Nguyen ◽  
Johannes Aprojanz ◽  
Alexei A. Zakharov ◽  
Rositsa Yakimova ◽  
...  
Keyword(s):  
Photoelectron Spectroscopy ◽  
Quantum Confinement ◽  
Field Effect Transistors ◽  
Graphene Nanoribbons ◽  
Tight Binding ◽  
Scanning Tunneling Spectroscopy ◽  
Scanning Tunneling ◽  
Pristine Graphene ◽  
One Dimensional ◽  
Experimental Findings

AbstractThe ability to define an off state in logic electronics is the key ingredient that is impossible to fulfill using a conventional pristine graphene layer, due to the absence of an electronic bandgap. For years, this property has been the missing element for incorporating graphene into next-generation field effect transistors. In this work, we grow high-quality armchair graphene nanoribbons on the sidewalls of 6H-SiC mesa structures. Angle-resolved photoelectron spectroscopy (ARPES) and scanning tunneling spectroscopy measurements reveal the development of a width-dependent semiconducting gap driven by quantum confinement effects. Furthermore, ARPES demonstrates an ideal one-dimensional electronic behavior that is realized in a graphene-based environment, consisting of well-resolved subbands, dispersing and non-dispersing along and across the ribbons respectively. Our experimental findings, coupled with theoretical tight-binding calculations, set the grounds for a deeper exploration of quantum confinement phenomena and may open intriguing avenues for new low-power electronics.

scholarly journals First-principles theoretical investigation of graphene layers for sensor applications

2017 ◽  
Vol 7 ◽  
pp. 184798041773764 ◽  
Author(s):  
Yoshitaka Fujimoto
Keyword(s):  
Carbon Nanotubes ◽  
First Principles ◽  
Density Functional ◽  
Gas Adsorption ◽  
High Sensitivity ◽  
Functional Study ◽  
Graphene Layers ◽  
Sensor Applications ◽  
Adsorption Effects ◽  
Gas Molecules

Graphene is expected to be a potential device material for sensor applications due to its high charge mobility and high sensitivity to adsorbates. This article reviews the first-principles density-functional study that clarifies gas adsorption effects on graphene layers doped with boron and nitrogen atoms. We show adsorption effects of not only common gas molecules but also environmentally polluting or toxic gas molecules on stabilities and structural properties of graphene layers and carbon nanotubes. We also show physical properties induced by the adsorption of the gas molecules and discuss the possibility to detect these gas molecules.

scholarly journals Intrinsic Spin-Orbit Coupling in Zigzag and Armchair Graphene Nanoribbons

2011 ◽  
Vol 2011 ◽  
pp. 1-7
Author(s):  
Ying Li ◽  
Erhu Zhang ◽  
Baihua Gong ◽  
Shengli Zhang
Keyword(s):  
Graphene Nanoribbons ◽  
Tight Binding ◽  
Geometrical Parameters ◽  
Spin Orbit Coupling ◽  
Spin Orbit ◽  
Binding Model ◽  
Tight Binding Approximation ◽  
Energy Gaps ◽  
Armchair Graphene Nanoribbons ◽  
Armchair Graphene

Starting from a tight-binding model, we derive the energy gaps induced by intrinsic spin-orbit (ISO) coupling in the low-energy band structures of graphene nanoribbons. The armchair graphene nanoribbons may be either semiconducting or metallic, depending on their widths in the absence of ISO interactions. For the metallic ones, the gaps induced by ISO coupling decrease with increasing ribbon widths. For the ISO interactions, we find that zigzag graphene nanoribbons with odd chains still have no band gaps while those with even chains have gaps with a monotonic decreasing dependence on the widths. First-principles calculations have also been carried out, verifying the results of the tight-binding approximation. Our paper reveals that the ISO interaction of graphene nanoribbons is governed by their geometrical parameters.

scholarly journals Deep Learning and Artificial Intelligence for the Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1222 ◽  
Author(s):  
Masrour Makaremi ◽  
Camille Lacaule ◽  
Ali Mohammad-Djafari
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Cervical Vertebra ◽  
Medical Diagnostics ◽  
Great Success ◽  
X Ray ◽  
Treatment Timing ◽  
Proposed Model ◽  
The Right

Deep Learning (DL) and Artificial Intelligence (AI) tools have shown great success in different areas of medical diagnostics. In this paper, we show another success in orthodontics. In orthodontics, the right treatment timing of many actions and operations is crucial because many environmental and genetic conditions may modify jaw growth. The stage of growth is related to the Cervical Vertebra Maturation (CVM) degree. Thus, determining the CVM to determine the suitable timing of the treatment is important. In orthodontics, lateral X-ray radiography is used to determine it. Many classical methods need knowledge and time to look and identify some features. Nowadays, ML and AI tools are used for many medical and biological diagnostic imaging. This paper reports on the development of a Deep Learning (DL) Convolutional Neural Network (CNN) method to determine (directly from images) the degree of maturation of CVM classified in six degrees. The results show the performances of the proposed method in different contexts with different number of images for training, evaluation and testing and different pre-processing of these images. The proposed model and method are validated by cross validation. The implemented software is almost ready for use by orthodontists.

Lattice Dynamics of Graphene Nanoribbons under Twisting

2021 ◽  
Author(s):  
Zhao Liu ◽  
Zhen Zhang ◽  
Hui-Yan Zhao ◽  
Jing Wang ◽  
Ying Liu
Keyword(s):  
Thermal Conductivity ◽  
Lattice Dynamics ◽  
Density Functional ◽  
Lattice Thermal Conductivity ◽  
Graphene Nanoribbons ◽  
Tight Binding ◽  
Tight Binding Method ◽  
Twisted Graphene

In this communication, we investigate the lattice dynamics of twisted graphene nanoribbons utilizing the density-functional tight-binding method based on screw symmetry and report the reduced lattice thermal conductivity due to...

Gas molecular adsorption effects on the electronic and optical properties of monolayer SnP3

Vacuum ◽  
2019 ◽  
Vol 168 ◽  
pp. 108823 ◽  
Author(s):  
Fanfan Niu ◽  
Miao Cai ◽  
Jiu Pang ◽  
Xiaoling Li ◽  
Daoguo Yang ◽  
...  
Keyword(s):  
Optical Properties ◽  
Molecular Adsorption ◽  
Electronic And Optical Properties ◽  
Adsorption Effects

scholarly journals An Analytical Conductance Model for Gas Detection Based on a Zigzag Carbon Nanotube Sensor

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 357
Author(s):  
Ali Hosseingholipourasl ◽  
Sharifah Hafizah Syed Ariffin ◽  
Mohammad Taghi Ahmadi ◽  
Seyed Saeid Rahimian Koloor ◽  
Michal Petrů ◽  
...  
Keyword(s):  
Carbon Nanotube ◽  
Band Structure ◽  
Gas Adsorption ◽  
Gas Sensing ◽  
Electrical Conductance ◽  
Analytical Models ◽  
Adsorption Effect ◽  
Sensing Applications ◽  
New Energy ◽  
Gas Molecules

Recent advances in nanotechnology have revealed the superiority of nanocarbon species such as carbon nanotubes over other conventional materials for gas sensing applications. In this work, analytical modeling of the semiconducting zigzag carbon nanotube field-effect transistor (ZCNT-FET) based sensor for the detection of gas molecules is demonstrated. We propose new analytical models to strongly simulate and investigate the physical and electrical behavior of the ZCNT sensor in the presence of various gas molecules (CO2, H2O, and CH4). Therefore, we start with the modeling of the energy band structure by acquiring the new energy dispersion relation for the ZCNT and introducing the gas adsorption effects to the band structure model. Then, the electrical conductance of the ZCNT is modeled and formulated while the gas adsorption effect is considered in the conductance model. The band structure analysis indicates that, the semiconducting ZCNT experiences band gap variation after the adsorption of the gases. Furthermore, the bandgap variation influences the conductance of the ZCNT and the results exhibit increments of the ZCNT conductance in the presence of target gases while the minimum conductance shifted upward around the neutrality point. Besides, the I-V characteristics of the sensor are extracted from the conductance model and its variations after adsorption of different gas molecules are monitored and investigated. To verify the accuracy of the proposed models, the conductance model is compared with previous experimental and modeling data and a good consensus is observed. It can be concluded that the proposed analytical models can successfully be applied to predict sensor behavior against different gas molecules.

Sign in / Sign up

Export Citation Format

Share Document