Adsorption of various types of amino acids on the graphene and boron-nitride nano-sheet, a DFT-D3 study

Zhiani, Rahele

doi:10.1016/j.apsusc.2017.02.243

Cited by 50 publications

(15 citation statements)

References 30 publications

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“…Similarly, several DFT based studies found that aromatic amino acids and Arg strongly bind with graphene compared to Gly, Val, and Asp. [82,83,85] These reported trends are consistent with the trends observed using the nonpolarizable force fields.…”

Section: B Free Energy Of Adsorption Of Amino Acidssupporting

confidence: 80%

“…Indirect validations can be performed by comparing the binding preferences of amino acids on graphene with the corresponding observations from ab initio, simulations, and wet-laboratory studies. [45,71,[81][82][83][84][85] The binding preferences of the amino acids on graphene estimated in our study and that reported in the literature are summarized in Fig. 4.…”

Section: B Free Energy Of Adsorption Of Amino Acidsmentioning

confidence: 98%

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Adsorption of amino acids on graphene: assessment of current force fields

2019

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Section: B Free Energy Of Adsorption Of Amino Acidssupporting

confidence: 80%

Section: B Free Energy Of Adsorption Of Amino Acidsmentioning

confidence: 98%

Adsorption of amino acids on graphene: assessment of current force fields

2019

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Section: B Free Energy Of Adsorption Of Amino Acidssupporting

confidence: 80%

Section: B Free Energy Of Adsorption Of Amino Acidsmentioning

confidence: 98%

Adsorption of Amino Acids on Graphene: Assessment of Current Force Fields

Dasetty¹,

Barrows²,

Sarupria³

2019

Preprint

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We compare the free energies of adsorption (∆A ads ) and the structural preferences of amino acids obtained using the force fields -Amberff99SB-ILDN/TIP3P, CHARMM36/modified-TIP3P, OPLS-AA/M/TIP3P, and Amber03w/TIP4P/2005. The amino acid-graphene interactions are favorable irrespective of the force field. While the magnitudes of ∆A ads differ between the force fields, the trends in the free energy of adsorption with amino acids are similar across the studied force fields. ∆A ads positively correlates with amino acid-graphene and negatively correlates with graphene-water interaction energies. Using a combination of principal component analysis and density-based clustering technique, we grouped the structures observed in the graphene adsorbed state. The resulting population of clusters, and the conformation in each cluster indicate that the structures of the amino acid in the graphene adsorbed state vary across force fields. The differences in the conformations of amino acids are more severe in the graphene adsorbed state compared to the bulk state for all the force fields. Our findings suggest that while the thermodynamics of adsorption of proteins and peptides would be described consistently across different force fields, the structural preferences of peptides and proteins on graphene will be force field dependent.

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“…However, the online version of record will be different from this version once it has been copyedited and typeset. Quantum transport models were previously used to understand the chemisorption related processes and the electron transport in complex systems similar to ours 15 . Depending on the assumptions made during the modelling of the system, one-dimensional (or a near 1D) approach based on the Landauer-Büttiker formalism, might be useful.…”

Section: Transport Data Processingmentioning

confidence: 99%

Detection of some amino acids with modulation-doped and surface-nanoengineered GaAs Schottky P-I-N diodes

Alkhidir

Jaoudé

Gater

et al. 2020

Journal of Vacuum Science &Amp; Technology B, Nanotechnology and Microelectronics: Materials, Processing, Measurement, and Phen

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Most current techniques for analyzing amino acids require substantial instrumentation and significant sample preprocessing. In this study, we designed, fabricated and tested a scalable diode-based microdevice that allows for direct sensing of amino acids. The device is based on modulation-doped GaAs heterostructure with a Schottky contact on one side. The relatively high mobility and relatively small dielectric constant of GaAs are naturally helpful in this problem. We also paid attention to a proper etching procedure allowing for substantial modification of the surface properties, thereby further boosting the sensing performance. Transport data (I-V, differential conductance) are presented for three qualitatively different classes of amino acids (i.e. non-polar with aliphatic R-group, polar uncharged R-group and charged R-group) with glycine, cysteine and histidine as specific examples, respectively. The conductance for the GaAsamino acid interface measured using scanning tunneling microscope (STM) was previously reported to have distinct spectral features. In this paper, we show that measuring the differential conductance of GaAs diode whose surface is in direct contact with an aqueous solution of amino acid, is a simple methodology to access useful information, previously available only through sophisticated and equipment-demanding STM and molecular electronics approaches. Density functional theory (DFT) calculations were used to examine which adsorption processes were likely responsible for the observed surface conductance modification. Lastly, in future and ongoing work, we illustrate how it might be possible to employ standard multivariate data analysis techniques to reliably identify distinct (95%) single amino acid specific features in near-ambient differential conductance data. Research questions we address here are: (1) is it possible to distinguish between different amino acids in contact with the same GaAs interface, based on I-V curves?; (2) how are partial charges specific to individual amino acids?; (3) what are the likely binding mechanisms (individual amino acid to GaAs)?; and (4) to what extent one can use differential conductance data? We show how it is possible to distinguish between separate aqueous solutions of the amino acids in in-This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.

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Adsorption of various types of amino acids on the graphene and boron-nitride nano-sheet, a DFT-D3 study

Cited by 50 publications

References 30 publications

Adsorption of amino acids on graphene: assessment of current force fields

Adsorption of amino acids on graphene: assessment of current force fields

Adsorption of Amino Acids on Graphene: Assessment of Current Force Fields

Detection of some amino acids with modulation-doped and surface-nanoengineered GaAs Schottky P-I-N diodes

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