Efficient Sensing of Selected Amino Acids as Biomarker by Green Phosphorene Monolayers: Smart Diagnosis of Viruses. Issue 10 (4th September 2022)
- Record Type:
- Journal Article
- Title:
- Efficient Sensing of Selected Amino Acids as Biomarker by Green Phosphorene Monolayers: Smart Diagnosis of Viruses. Issue 10 (4th September 2022)
- Main Title:
- Efficient Sensing of Selected Amino Acids as Biomarker by Green Phosphorene Monolayers: Smart Diagnosis of Viruses
- Authors:
- Panigrahi, Puspamitra
Pal, Yash
Panigrahi, Akshaya
Bae, Hyeonhu
Lee, Hoonkyung
Ahuja, Rajeev
Hussain, Tanveer - Abstract:
- Abstract: Effective techniques for the detection of selected viruses detection of their amino acids (AAs) constituents are highly desired, especially in the present COVID pandemic. Motivated by this, we have used density functional theory (DFT) simulations to explore the potential applications of green phosphorene monolayer (GPM) as efficient nanobio‐sensor. We have employed van der Waals induced calculations to study the ground‐state geometries, binding strength, electronic structures, and charge transfer mechanism of pristine, vacancy‐induced and metal‐doped GPM to detect the selected AAs, such as glycine, proline and aspartic, in both aqueous and non‐aqueous media. We find that the interactions of studied AAs are comparatively weak on pristine (−0.49 to −0.76 eV) and vacancy‐induced GPM as compared to the metal‐doped GPM (−0.62 to −1.22 eV). Among the considered dopants, Ag‐doping enhances the binding of AAs to the GPM stronger than the others. In addition to appropriate binding energies, significant charge transfers coupled with measurable changes in the electronic properties further authenticate the potential of GPM. Boltzmann thermodynamic analysis have been used to study the sensing mechanism under varied conditions of temperatures and pressure for the practical applications. Our findings signify the potential of GPM based sensors towards efficient detection of the selected AAs. Abstract : Density functional theory simulations are used to study GPM as efficient sensorAbstract: Effective techniques for the detection of selected viruses detection of their amino acids (AAs) constituents are highly desired, especially in the present COVID pandemic. Motivated by this, we have used density functional theory (DFT) simulations to explore the potential applications of green phosphorene monolayer (GPM) as efficient nanobio‐sensor. We have employed van der Waals induced calculations to study the ground‐state geometries, binding strength, electronic structures, and charge transfer mechanism of pristine, vacancy‐induced and metal‐doped GPM to detect the selected AAs, such as glycine, proline and aspartic, in both aqueous and non‐aqueous media. We find that the interactions of studied AAs are comparatively weak on pristine (−0.49 to −0.76 eV) and vacancy‐induced GPM as compared to the metal‐doped GPM (−0.62 to −1.22 eV). Among the considered dopants, Ag‐doping enhances the binding of AAs to the GPM stronger than the others. In addition to appropriate binding energies, significant charge transfers coupled with measurable changes in the electronic properties further authenticate the potential of GPM. Boltzmann thermodynamic analysis have been used to study the sensing mechanism under varied conditions of temperatures and pressure for the practical applications. Our findings signify the potential of GPM based sensors towards efficient detection of the selected AAs. Abstract : Density functional theory simulations are used to study GPM as efficient sensor toward selected amino acids. Sensing mechanism is studied through ground‐state geometries, binding strength, electronic structures, and charge transfer mechanism. It is found that silver doping enhances the sensitivity and selectivity of GPM. … (more)
- Is Part Of:
- Advanced theory and simulations. Volume 5:Issue 10(2022)
- Journal:
- Advanced theory and simulations
- Issue:
- Volume 5:Issue 10(2022)
- Issue Display:
- Volume 5, Issue 10 (2022)
- Year:
- 2022
- Volume:
- 5
- Issue:
- 10
- Issue Sort Value:
- 2022-0005-0010-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-09-04
- Subjects:
- binding -- dopants -- monolayer -- phosphorene -- thermodynamic analysis
Science -- Simulation methods -- Periodicals
Science -- Methodology -- Periodicals
Engineering -- Simulation methods -- Periodicals
Engineering -- Methodology -- Periodicals
507.21 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/adts.202200357 ↗
- Languages:
- English
- ISSNs:
- 2513-0390
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.935575
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24048.xml