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Researchers in Texas have created an enzyme variant that can break down plastics that would typically take hundreds of years to dissolve in a matter of hours or days.
The creation by officials at The University of Texas at Austin could solve the problem of how to rid the world of billions of tons of plastic piling up in landfills and polluting natural lands and water.
“The possibilities are endless across industries to leverage this leading-edge recycling process,” Hal Alper, professor in the McKetta Department of Chemical Engineering at UT Austin said in a statement. “Beyond the obvious waste management industry, this also provides corporations from every sector the opportunity to take a lead in recycling their products. Through these more sustainable enzyme approaches, we can begin to envision a true circular plastics economy.”
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Researchers at the schools Cockrell School of Engineering and College of Natural Sciences used a machine learning model to generate mutations to a natural enzyme called PETase that allows bacteria to degrade PET plastics.
Researchers studied 51 different plastic containers, five polyester fibers and fabrics and water bottles made from PET. Globally, less than 10% of all plastic has been recycled, the university said. The most common method involves throwing it in a landfill and burning it, which is costly and generates toxic gas into the air, the school said.
Annually, the world produces 400 million tons of plastic waste, the United Nations Environment Program (UNEP) said. Cigarette butts, whose filters contain tiny plastic fibres, are the most common type of plastic waste found in the environment. Food wrappers, items made from plastic like bottles, bottle caps, grocery bags, straws and stirrers are the next most common items, the UN said.
The researchers said using enzymes makes solutions for plastic disposal more portable and affordable on a large industrial scale. The FAST-PETase can perform the process at less than 122 degrees Fahrenheit.
“This work really demonstrates the power of bringing together different disciplines, from synthetic biology to chemical engineering to artificial intelligence,” said Andrew Ellington, professor in the Center for Systems and Synthetic Biology, whose team led the development of the machine learning model.
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Next up, the research team plans to scale up the enzyme for industrial and environmental applications. They have already filed a patent application for the technology. The team is exploring other possibilities for the technology, including cleaning up landfills and polluted areas.