Dataset Information

Novel Quinoline-Based Thiazole Derivatives for Selective Detection of Fe3+, Fe2+, and Cu2+ Ions.

ABSTRACT: New quinoline-based thiazole derivatives QPT and QBT were synthesized and characterized by various spectroscopic and single-crystal X-ray crystallographic studies. The metal-sensing properties of the probes were further examined by absorption and fluorescence spectrometry. The fluorescence intensity of QPT and QBT was remarkably quenched during the addition of Fe3+, Fe2+, and Cu2+ ions in THF/H2O (1:1) at pH = 7.4 in HEPES buffer, while the addition of other metal ions did not affect the fluorescence intensity of the ligands. The detection ability of the probes QPT and QBT was further investigated by titration with various equivalents of metal ions, optimized pH ranges for detection, and reversibility with Na2EDTA for biological applications.

SUBMITTER: Shyamsivappan S

PROVIDER: S-EPMC7594140 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Novel Quinoline-Based Thiazole Derivatives for Selective Detection of Fe3+, Fe2+, and Cu2+ Ions.

Shyamsivappan Selvaraj S Saravanan Arjunan A Vandana Nandakumar N Suresh Thangaraj T Suresh Shanmugam S Nandhakumar Raju R Mohan Palathurai Subramaniam PS

ACS omega 20201012 42

New quinoline-based thiazole derivatives QPT and QBT were synthesized and characterized by various spectroscopic and single-crystal X-ray crystallographic studies. The metal-sensing properties of the probes were further examined by absorption and fluorescence spectrometry. The fluorescence intensity of QPT and QBT was remarkably quenched during the addition of Fe3+, Fe2+, and Cu2+ ions in THF/H2O (1:1) at pH = 7.4 in HEPES b ...[more]

PMID: 33134686

Similar Datasets

Project description:Inspired by the remarkable electronic and optical properties of single walled carbon nanotubes (SWNTs), various molecular sensing devices with sensitivity down to the single molecule level have been developed. However, most sensing approaches such as field effect transistors or near infrared (NIR) fluorescence require the rigorous debundling and separation of metallic tubes and semiconducting tubes in order to reach the desired high sensitivity. Interestingly, all carbon nanomaterials including carbon nanotubes, graphite, graphene, and even amorphous carbon exhibit extremely strong π-plasmon absorption in the ultraviolet region. This strong absorption has been studied as an undesired optical background for applications based on visible and NIR absorptions. For the first time, we found that the strong π-plasmon absorption of SWNTs in the ultraviolet region is extremely sensitive to ion binding. It is even much more sensitive than the absorption in the visible and NIR regions. Herein, we present our first exploration into using the extremely strong plasmon absorption of SWNTs to develop a new sensing platform for the detection of metallic ions. The detection selectivity is realized by modifying the surface of SWNTs with molecular ligands that have a high specificity for metal ions. As a demonstration, the new method is applied to selectively detect iron ions (Fe3+) by modifying the surface of the SWNTs with deferoxamine (DFO), a natural bacterial siderophore, which has a high specificity and affinity for Fe3+. The selective detection of Fe3+ in both aqueous solution and complex rain water is achieved with a pM level of sensitivity and detection limit. In situ resonant Raman spectroscopy demonstrated that the sensitive detection possibly involves electron transfer between the formed Fe-DFO complexes and the SWNTs. We envisage that it can be used to detect other metal ions when a specific binding chelator is attached to the carbon nanotube surface.

Dataset Information

Novel Quinoline-Based Thiazole Derivatives for Selective Detection of Fe3+, Fe2+, and Cu2+ Ions.

Publications

Novel Quinoline-Based Thiazole Derivatives for Selective Detection of Fe<sup>3+</sup>, Fe<sup>2+</sup>, and Cu<sup>2+</sup> Ions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets