The new system automates the ability to sort plastics, as well as environmentally responsible solvents and new chemistries.

Researchers at the University of Buffalo are developing a novel set of tools that aims to reduce plastic waste and decrease the production of plastic.

Plastic consumption is amongst the major concern thwarting the earth's sustainable growth. Plastic is the major environmental pollutant, affecting the flora and fauna equally. Despite the many measures taken by the global authorities, the surge in plastic consumption shadows sustainability.  The World Economic Forum states that every year eight million tones of plastic waste leaks into the ocean. It is estimated that by the year 2050, more plastic will be present in the ocean compared to the fish. Henceforth, to address the challenges associated with plastic consumption, the researchers have formulated a new AI-driven robotic tool for plastic recycling industry.

This new tool includes a robotic system enabled with machine learning that automates the ability to sort plastics, as well as environmentally responsible solvents and new chemistries that breaks down the plastics into feasible usage components. The research worth US$ 1.9 million is funded by the Newyork State Department of Environmental Conservation (DEC).

Amit Goyal, the Project Director and SUNY Distinguished Professor and Director of the RENEW Institute states that "The project is well-aligned with RENEW's mission to bring together teams of multidisciplinary faculty to focus on complex issues related to energy and the environment. RENEW's overall goal is to enable a regenerative economy that includes improving recycling of all materials."

This ambitious multidisciplinary approach has been taken into account after China curtailed its waste importing business in 2018.

Paschalis Alexandridis, the lead researcher and a distinguished professor in the Department of Chemical and Biological Engineering, states, "Not only is this work critically important to our planet, it also contributes to the country's advanced manufacturing capabilities. It will help meet both consumer demand for and corporate commitments to incorporating recycled plastics into commercial products."

The robotic system under development combines the sensor technology and machine learning model. The sensor technology will register the molecular signature of each piece of plastic, and machine learning will identify the specific piece of plastic, based on the molecular signatures. The researchers aim to create an advanced mixed-waste sorting process that captures and reuses materials found in plastic recycling streams such as contaminants and non-polymeric waste for easy and cost-effective recycling process.

The robotic system also aims to detect the use of environmentally responsible solvents, for segregating the desired plastics from ingrained impurities. The researchers are also aiming to develop models that will spearhead the controlled breakdown of plastic molecules into raw materials.

DEC Commissioner, Basil Seggos stated, "This partnership will evaluate sorting technologies, assess potential costs and benefits to improve recycling infrastructure with a focus on plastics, leading to greater efficiencies and less waste that will protect the environment and benefit the economy. Recycling right is the key to keeping contamination down and the quality of recyclables high."