Analytical modelling of monolayer graphene-based ion-sensitive FET to pH changes

Kiani, Mohammad Javad; Ahmadi, Mohammad Taghi; Abadi, H. Karimi Feiz; Rahmani, Meisam; Hashim, Amin; Harun, Fauzan Khairi Che

doi:10.1186/1556-276x-8-173

Cited by 33 publications

(24 citation statements)

References 43 publications

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“…In such device the sensing performances are related to the changes in graphene conductivity when the pH of the buffer is changed. (Kiani, 2013;Ohno, 2010). Moreover, ISFETs turned out to be very useful in biology to measure for instance the biological activities of cells or enzymes (Lin, 2013b).…”

Section: Introductionmentioning

confidence: 99%

A field effect transistor biosensor with a γ-pyrone derivative engineered lipid-sensing layer for ultrasensitive Fe3+ ion detection with low pH interference

Nguyen

Labed

Zein

et al. 2014

Biosensors and Bioelectronics

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Field effect transistors have risen as one of the most promising techniques in the development of biomedical diagnosis and monitoring. In such devices, the sensitivity and specificity of the sensor rely on the properties of the active sensing layer (gate dielectric and probe layer). We propose here a new type of transistor developed for the detection of Fe(3+) ions in which this sensing layer is made of a monolayer of lipids, engineered in such a way that it is not sensitive to pH in the acidic range, therefore making the device perfectly suitable for biomedical diagnosis. Probes are γ-pyrone derivatives that have been grafted to the lipid headgroups. Affinity constants derived for the chelator/Fe(3+) complexation as well as for other ions demonstrate very high sensitivity and specificity towards ferric ions with values as high as 5.10(10) M and a detected concentration as low as 50 fM.

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Section: Introductionmentioning

confidence: 99%

A field effect transistor biosensor with a γ-pyrone derivative engineered lipid-sensing layer for ultrasensitive Fe3+ ion detection with low pH interference

Nguyen

Labed

Zein

et al. 2014

Biosensors and Bioelectronics

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“…where is the electron charge, ℎ denotes Planck's constant, represents the energy band structure, ( ) is the transmission probability, ( ) is the number of modes, and denotes the Fermi-Dirac distribution function [34,35]. In other words, ( ) is the average probability of electron transmission in the channel from one electrode to another.…”

Section: Methodsmentioning

confidence: 99%

Optimization of DNA Sensor Model Based Nanostructured Graphene Using Particle Swarm Optimization Technique

Karimi

Yusof

Rahmani

et al. 2013

Journal of Nanomaterials

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It has been predicted that the nanomaterials of graphene will be among the candidate materials for postsilicon electronics due to their astonishing properties such as high carrier mobility, thermal conductivity, and biocompatibility. Graphene is a semimetal zero gap nanomaterial with demonstrated ability to be employed as an excellent candidate for DNA sensing. Graphene-based DNA sensors have been used to detect the DNA adsorption to examine a DNA concentration in an analyte solution. In particular, there is an essential need for developing the cost-effective DNA sensors holding the fact that it is suitable for the diagnosis of genetic or pathogenic diseases. In this paper, particle swarm optimization technique is employed to optimize the analytical model of a graphene-based DNA sensor which is used for electrical detection of DNA molecules. The results are reported for 5 different concentrations, covering a range from 0.01 nM to 500 nM. The comparison of the optimized model with the experimental data shows an accuracy of more than 95% which verifies that the optimized model is reliable for being used in any application of the graphene-based DNA sensor.

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“…By applying an external electric field and intentional doping, various Shottky barriers of GSJ can be achieved [7,8]. Furthermore, that GSJ can also integrate to other 2D semiconductors to form different heterojunctions such as graphene-hBN [9,10], graphene-MoS 2 and also graphene-black phosphorus [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Negative differential resistance effect of blue phosphorene-graphene heterostructure device

Zhu

et al. 2020

J. Phys. Commun.

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We report on the electrical transport properties of new graphene/blue phosphorene heterostructure devices by density functional theory (DFT) within the non-equilibrium Green's function (NEGF) approach. From the results, it is found that the devices with different length of contacts layers show semiconducting nature. The integrated contacted length of graphene/blue phosphorene two-layer device shows the best conductivity under a bias voltage. The negative differential resistance effect (NDR) is also found in the current-voltage curve of all the graphene/blue phosphorene devices. Transport characteristics can be explained by the eigenvalues of self-consistent Hamiltonian (MPSH). The results show that the device is fabricated from graphene/blue phosphorous and has good electrical conductivity. These interesting features will be useful for future electronic products.

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Analytical modelling of monolayer graphene-based ion-sensitive FET to pH changes

Cited by 33 publications

References 43 publications

A field effect transistor biosensor with a γ-pyrone derivative engineered lipid-sensing layer for ultrasensitive Fe3+ ion detection with low pH interference

A field effect transistor biosensor with a γ-pyrone derivative engineered lipid-sensing layer for ultrasensitive Fe3+ ion detection with low pH interference

Optimization of DNA Sensor Model Based Nanostructured Graphene Using Particle Swarm Optimization Technique

Negative differential resistance effect of blue phosphorene-graphene heterostructure device

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