2019
DOI: 10.1039/c8cp05093g
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Electronic transport in a graphene single layer: application in amino acid sensing

Abstract: We modeled a type of field-effect transistor device based on graphene for the recognition of amino acids with a potential application in the building of a protein sequencer.

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Cited by 29 publications
(21 citation statements)
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“…We note the asymmetry of I-V curves upon bias voltage inversion offers useful information, similar to studies reported in 24,27 . Essentially, analysis of either I-V curves or differential conductance (here, both), points towards energy levels where main conduction channels occur.…”
Section: Resultssupporting
confidence: 83%
See 1 more Smart Citation
“…We note the asymmetry of I-V curves upon bias voltage inversion offers useful information, similar to studies reported in 24,27 . Essentially, analysis of either I-V curves or differential conductance (here, both), points towards energy levels where main conduction channels occur.…”
Section: Resultssupporting
confidence: 83%
“…The Hamiltonian in MLWF describing the quantum conductance is then solved by constructing the left and the right leads. The method details mirror the efforts in reference 20 , and related references [21][22][23][24] . We caution that we are using a simplified model system in the form of Bias Lead -GaAs -Bias Lead and a single amino acid molecule, instead of a more realistic AlGaAs-GaAs-AlGaAs N-I-P system with a larger number of atoms and with a water solution of amino acid.…”
Section: Please Cite This Article Asmentioning
confidence: 95%
“…Studying proteins at the molecular level is of particular importance as it provides insight into molecular mechanisms and gives the opportunities to develop new protein-based molecular diagnostic tools for research and clinical applications. Single-molecule protein sequencing would be very significant in proteomic research with important biomedical impacts. , …”
Section: Introductionmentioning
confidence: 99%
“…Since 2D nanomaterials are promising for applications in a wide range of fields due to their unique structural, electronic, and transport properties, they offer an excellent possibility for nanoelectronics-based applications too. Therefore, 2D material-based nanoscale devices are actively being investigated for single-molecule bioelectronics. Graphene as a biomolecule sensor has attracted considerable attention since it provides various sensing mechanisms such as charge transfer, charge scattering, and π–π stacking interactions . Furthermore, it is a zero-gap semiconductor capable of significantly upgrading the selectivity and sensitivity of field-effect transistor (FET) biosensors on the road to more efficient enzymatic biomolecule sensing and DNA sequencing. , In particular, the interactions between amino acids and graphene have been extensively investigated by both experimentalists and theoreticians. ,,,,,,, However, the significantly low ON/OFF current ratio limits the use of graphene in bioelectronic device applications.…”
Section: Introductionmentioning
confidence: 99%
“… 26–28 Similarly, S. J. Rodríguez and E. A. Albanesi proposed a type of field-effect transistor device based on graphene for detecting amino acids with the help of DFT calculations in combination with the non-equilibrium Green's function in the OpenMX3.844 software package. 29 In addition, M. Z. Tonel et al conducted a theoretical study and they found physisorption interaction between a pristine graphene nanosheet and doxorubicin anticancer drug with 0.49 eV binding energy and also showed a decrease in the interaction with increasing temperature by means of DFT theory with the GGA-PBE functional in SIESTA code. 30 Moreover, the C 24 nanocage has been proposed as a sensing nanostructure towards anticancer drug Melphalan by performing DFT at the B3LYP/6-31G(d) level of theory by the research group of E. S. Mirkamali et al 31 Finally, E. O. Kweitsu's research group theoretically showed that pristine C 60 is a suitable sensor for sensing phosgene gas by using DFT/LDA calculation in Quantum Espresso Software.…”
Section: Introductionmentioning
confidence: 99%