Title: | Defective GaAs nanoribbon-based biosensor for lung cancer biomarkers: a DFT study |
Author(s): | Tarun T; Singh P; Kaur H; Walia GK; Randhawa DKK; Choudhary BC; |
Address: | "Electrical and Computer Engineering Department, Concordia University, Montreal, H3G 1M8, Canada. Department of Electronics and Communication Engineering, Guru Nanak Dev University, Regional Campus, Jalandhar, Punjab, India. School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India. gurleen.24800@lpu.co.in. Applied Science Department, National Institute of Technical 'Teachers' Training and Research (NITTTR), Chandigarh, India" |
DOI: | 10.1007/s00894-021-04889-9 |
ISSN/ISBN: | 0948-5023 (Electronic) 0948-5023 (Linking) |
Abstract: | "Density functional theory-based first-principles investigation is performed on pristine and mono vacancy induced GaAs nanoribbons to detect the presence of three volatile organic compounds (VOCs), aniline, isoprene and o-toluidine, which will aid in sensing lung cancer. The study has shown that pristine nanoribbon senses all three analytes. For the pristine structure, we observe decent adsorbing parameters and the bandgap widens after the adsorption of analytes. However, the introduction of the carrier traps induced by defect causes deep energy wells that vary the electrical properties as indicated in the bandgap analysis of GaAs, wherein adsorption of aniline and o-toluidine reduces the bandgap to 0 eV, making the structure highly conductive in nature. The adsorption energies of defect-induced nanoribbon are more as compared with the pristine counterpart. Nonetheless, the introduction of defects has improved the sensitivity further" |
Keywords: | "Arsenicals Biomarkers, Tumor/*analysis *Biosensing Techniques *Computational Chemistry *Density Functional Theory Gallium Humans Lung Neoplasms/*diagnosis Nanotubes, Carbon Biomarker Biosensor Density functional theory (DFT) Gallium arsenide Lung cancer N;" |
Notes: | "MedlineTarun, Tarun Singh, Paramjot Kaur, Harmandar Walia, Gurleen Kaur Randhawa, Deep Kamal Kaur Choudhary, B C eng Germany 2021/08/31 J Mol Model. 2021 Aug 30; 27(9):270. doi: 10.1007/s00894-021-04889-9" |