Ahmed S. Saad

Computational chemistry induced several fast, cost-effective revolutionary solutions for chemistry laboratories. The reliability of such solutions has been questioned in several studies. The current work introduces an experimental validation for the computational selection of an ionophore during potentiometric sensor optimization. We studied the correlation of the experimental sensor performance parameters to the computational binding scores of the embedded ionophores and the drug (loperamide hydrochloride). The study included eight sensors of different PVC-membrane compositions. The PVC-membrane containing phosphotungstic acid, dioctyl phthalate, and carboxymethyl-β-cyclodextrin developed a Nernstian slope of 59.69 mV/decade and a detection limit of 2.95×10-7 mol L-1. The sensor demonstrated a fast and stable response within a linear range of 2.99×10-6-9.09×10-3 mol L-1. We examined the drug-ionophore binding using molecular modeling and docking. The docking scores (binding energy) of the cyclodextrin derivatives strongly correlate to the studied sensors experimental performance parameters (Nernstian slope). Performance and validation parameters were computed, and the results were statistically comparable to those of the reported method. Practically, the absence of sample preparation, chromatographic separation, high-purity solvents, and costly instrumentation are incomparable advantages of the developed method relative to the reported ones.

Microbial biodegradation employs non-hazardous microbes to detoxify or eliminate toxic chemicals. Direct Red-81 (DR81) is a toxic and carcinogenic dye discharged in textile-industry wastewater and contaminates water resources. The offline spectrophotometric methods commonly used to monitor biodegradation require sampling and sample preparation. They do not consider the change in the medium composition and the generated products that may perturb the method selectivity. Potentiometric sensors introduce a simple direct, inline, portable, and real-time analysis tool. To our knowledge, no potentiometric sensor was reported for online monitoring of an ongoing microbial-biodegradation process. Recent work reports the biodegradation of DR81 using Candida albicans, where the researchers withdrew samples frequently to monitor the change in the UV–visible spectrum of DR81. This study optimizes and validates a portable and selective solid-state potentiometric sensor to monitor the microbial biodegradation of DR81 in the dilute mineral salt medium. The optimized sensor composition includes 1.61% tetra-dodecyl ammonium chloride, 66.47% dioctyl phthalate, 1.61% Calix-[4]-arene and 30.31% polyvinyl chloride matrix. The sensor results conform with our previous work results; however, the portable sensor monitored the ongoing microbial degradation inline without sampling and in real-time. The sensor assists microbiologists and environmentalists in comprehending the process and optimizing the conditions for DR81 microbial biodegradation.