Molecular simulations of CRANADs to disclose a specific cyanide sensor in aqueous media
Computational and Theoretical Chemistry, ISSN: 2210-271X, Vol: 1217, Page: 113894
2022
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Article Description
Chemical pollutants are the major contaminants in natural water samples and can be introduced either through natural processes or as a result of human activities. Some of the cations and anions such as cyanide, lead, mercury, and arsenic are toxic even at extremely low concentrations. The fatal effects of cyanide ions on the ecosystem have led to extensive research in the advancement of methods for rapid and specific detection of cyanide. We already reported the theoretical and experimental studies on the specific cyanide sensing capacity of the curcuminoid-BF 2 complex, CRANAD-1. However, the theoretical investigation of the sensing mechanism of these types of CRANADs pointed out the key structural features which are capable of generating a better fluoroprobe for the rapid detection of cyanide in aqueous media even in trace quantities. Herein, we designed a novel selective and efficient fluorescent probe for cyanide detection based on these features. The DFT (Density Functional Theory) approach explores the significance of the probe in the quantitative detection of cyanide concentration in natural water samples. A comprehensive examination of the binding energies of the designed CRANADs in presence of various anions such as CN −, F −, Cl −, Br −, AcO −, SO 4 2− and NO 3 − were carried out using the B3LYP level of density functional theory using SDD and 6-311++G** basis sets. The λ max absorption values, FMO (Frontier Molecular Orbital), ESP (Electrostatic potential) plots and NBO (Natural Bond Orbital) analysis reveal the better cyanide sensing ability of the D–A–D (Donor-Acceptor–Donor) type CRANAD scaffold.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2210271X22003073; http://dx.doi.org/10.1016/j.comptc.2022.113894; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85141458030&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2210271X22003073; https://dx.doi.org/10.1016/j.comptc.2022.113894
Elsevier BV
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