What is it about?
A high-performance catalyst of nanosize was prepared via a simple route and utilised to degrade phenol from simulated wastewater containing various phenolic compounds. To optimise the degradation process, various input parameters were enhanced via the design of experiment algorithm. The effect of the optimised parameters was forecasted by artificial neural network. Interestingly, more than 95% phenol was degraded in less than 2 hrs of operation.
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Why is it important?
This research is highly necessary due to growing environmental concerns of phenolics in water resource. Long-term exposure to a tiny concentration of phenol can cause brain damage and various health related issues. Hence, this research incorporates easy, an environmentally friendly approach using freely available sunlight to degrade the phenol.
Perspectives
Personally, the idea introduced in this research is highly novel, reproducible and simple to implement by the small-scale treatment facility. The results of this research are expected to be useful in decontaminating olive-mill wastewater continuing various phenolics in such a way that the treated water can be reused for irrigation purpose.
Akeem Oladipo
British University of Nicosia
Read the Original
This page is a summary of: High-Performance Nanocatalyst for Adsorptive and Photo-Assisted Fenton-Like Degradation of Phenol: Modeling Using Artificial Neural Networks, Chemical Engineering Communications, March 2017, Taylor & Francis,
DOI: 10.1080/00986445.2017.1311253.
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