Sono-synthesis of MnWO4 ceramic nanomaterials as highly efficient photocatalysts for the decomposition of toxic pollutants
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Abstract
Abstract As the subject of energy deficiency and environmental contamination has become a widespread concern, introducing green and quick procedure for synthesizing compounds with a catalyst role in solving environmental problems is followed with great interest. Herein, we offer a controllable sonochemical approach for photocatalyst synthesis. The nanostructured MnWO4 is created via a sonochemical process utilizing a green capping agent, phenylalanine. It was observed that various quantities of precursors, different sonication times, and diverse types of capping agents could modify the shape, photocatalytic yield, and scale of MnWO4 samples. The features of nanostructured MnWO4 were examined with different kinds of analyses. The activity of various MnWO4 structures as photocatalytic substances to eliminate organic contamination in water by visible radiation was also studied. Although all the various structures of manganese tungsten oxide were able to eliminate the organic contamination in the water, the photocatalytic performance of MnWO4 nanostructure was created utilizing phenylalanine via sonochemistry was superior to that of the samples made under other conditions. The optimal sample manifested remarkable yield since the removal rates of Acid Yellow 23, eosin Y, and crystal violet in 50 min under visible radiation were 98.86, 99.15, and 97.56 %, respectively. The manganese tungsten oxide nanostructure is of the paramagnetic kind. Besides, the optimal MnWO4 sample was reused as a photocatalytic substance. It manifested appropriate stability over 13 cycles, denoting its capability as a highly efficient photocatalytic substance to remedy the environment.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Photocatalysis Techniques · Luminescence Properties of Advanced Materials · Gas Sensing Nanomaterials and Sensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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