Researchers at the Institute of Nano Science and Technology (INST) Mohali, an autonomous institution under the Department of Science and Technology (DST), have developed an innovative, machine-learning-assisted filter to treat industrial wastewater. By integrating green-synthesized zinc oxide (ZnO) nanoparticles with biodegradable polylactic acid (PLA) nanofibers, the sustainable filtration membrane effectively tackles persistent organic dyes from textile and industrial effluents.
Conventional wastewater treatments often separate pollutants without destroying them, while biological methods can be slow for stable dyes. Although photocatalysis is an alternative, it faces challenges such as catalyst recovery and electron-hole recombination. To overcome this, INST Mohali used turmeric extract to green-synthesize crystalline ZnO nanoparticles—avoiding harsh chemicals—and embedded them within porous PLA nanofibers.
By combining photocatalysis and piezocatalysis using light and ultrasonic vibrations, the PLA-ZnO nanofibers achieved remarkable results, including 98.6% Methylene Blue (MB) and 96.7% Congo Red (CR) decolorization within 120 minutes. Additionally, the material exhibited strong antibacterial properties, inactivating roughly 75% of E. coli and 71% of S. aureus. Machine learning was successfully integrated to predict dye-decolorization behavior based on parameters like wavelength, time, and catalyst amount, paving the way for cleaner water and advanced environmental remediation.
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