The development of impedimetric, non-faradaic label-free sensors for the detection of α-amino acids constitutes a trailblazing technology for the fast and inexpensive quantification of such biomarkers. Since α-amino acids, such as glycine and sarcosine, are basic constituents in biological processes, a variation in their concentration may be an indicator of cardiovascular diseases and metabolic disorders or neurological conditions. The unique properties, including maze-like porosity along with excellent electron transfer behavior, make boron-doped carbon nanowalls (BCNW) an ideal transducer for electrochemical sensing. In order to realize a non-faradaic impedimetric sensor for the detection of α-amino acids, 1,8-diazafluoren-9-one (DFO), a fluorophore commonly used in forensic science, was dispersed into Ti-sol precursor and deposited over a BCNW substrate by spin-coating. Data mining tools have been applied to the raw impedimetric data to directly predict the glycine concentration and to support the underlying material-interface interaction. The developed sensor revealed high selectivity and reproducibility toward glycine and other α-amino acids (phenylamine, sarcosine and tryptophan) and no selectivity toward β-alanine, γ-aminobutyric acid or taurine. The application of density-functional theory (DFT) studies supported the higher affinity with the highest adsorption energy for the reaction product of DFO with glycine. A detection limit of 51 nM was found for glycine.
Authors
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1016/j.snb.2022.132459
- Category
- Publikacja w czasopiśmie
- Type
- artykuły w czasopismach
- Language
- angielski
- Publication year
- 2022
