Promising sensors for pharmaceutical pollutant adsorption using Clar's goblet-based 2D membranes

Area of Science:

• Materials Science
• Computational Chemistry
• Environmental Science

Background:

• Pharmaceutical pollutants pose environmental and health risks.
• Development of sensitive and selective sensors is crucial for monitoring these contaminants.
• Clar's Goblet structures offer unique electronic and chemical properties for novel material design.

Purpose of the Study:

• To design and investigate 2D Clar's Goblet membranes (CGMs) as potential sensors for pharmaceutical pollutants.
• To explore the electronic, optical, and interaction properties of CGMs with aspirin, paracetamol, ibuprofen, and diclofenac.
• To computationally characterize the adsorption mechanisms and sensing capabilities of CGMs.

Main Methods:

• Density Functional Theory (DFT) calculations were employed to investigate CGMs.
• Electronic properties, including energy gap and density of states, were computed.
• Molecular electrostatic potential (ESP), adsorption energies, UV-Vis spectra, and hole/electron distribution were analyzed.

Main Results:

• CGMs were identified as semiconductors with an energy gap of approximately 1.5 eV.
• ESP analysis indicated suitable sites for interaction with pharmaceutical pollutants.
• Diclofenac exhibited the strongest chemical adsorption, with significant charge transfer observed.
• UV-Vis spectra showed redshifts upon drug adsorption, confirming interaction.

Conclusions:

• CGMs demonstrate significant potential as highly sensitive sensors for pharmaceutical pollutants.
• The computational findings support the use of CGMs in developing novel sensing technologies.
• Understanding the interaction mechanisms provides a basis for sensor optimization.