Computational modelling of host-guest interactions between a Ni(II) coordination complex and persistent organic pollutants.

Authors

Md Nur Hasan, Basudeb Dutta, Manas Mahapatra, Shibashis Halder

Published in

Dalton transactions (Cambridge, England : 2003). Oct 14, 2026. Epub Oct 14, 2026.

Abstract

Regulatory restrictions and controlled experimental access to numerous hazardous agrochemicals pose a growing challenge to the strategic design of advanced sensing materials for persistent organic pollutants (POPs). This study presents a comprehensive theoretical analysis of a well-characterized Ni(II)-based coordination complex, prepared by a slow diffusion process, as a possible sensing platform for the identification of several POPs. Density functional theory (DFT), time-dependent DFT, reduced density gradient, and electron localization function analyses were utilized to systematically investigate the Ni complex's interaction with representative POPs, their optical responses, non-covalent interactions, and electron localization. Depending on the molecular structure of the POPs, optimized host-guest geometries exhibit favourable binding affinities driven by a combination of van der Waals interactions, electrostatic interactions, π-interactions, etc. The recognition mechanism and relative selectivity of the Ni(II) complex towards different POPs can be observed at the molecular level through binding energies, charge transfer characteristics, frontier molecular orbital analyses, independent gradient model and non-covalent interaction studies. The outcome highlights the Ni(II) complex's potential as a sensing material via alterations in optical responses. Its electronic structure is found to be sensitively modulated upon guest binding. This study establishes a predictive computational sensing strategy for hazardous POPs that are difficult to access experimentally (sometimes banned), providing useful guidelines for the future design of coordination complex-based sensors targeting hazardous and highly regulated contaminants.

PMID:
42876270
Bibliographic data and abstract were imported from PubMed on 15 Oct 2026.

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