Predictive modeling yields promising bioplastics catalyst

September 2, 2016 |

Combining predictive modeling and experimental lab work, researchers from IBM Research and Stanford University say they were able to design a catalyst that enables cheaper biodegradable plastics from plants.

The high cost of biodegradable plastics compared to petroleum-derived counterparts is a major impediment to their wider use in disposable goods such as plastic utensils. Unlike current methods of converting plants into biodegradable plastics, the new catalyst is organic and does not impart heavy metals into the plastic, facilitating decomposition.

Xiangyi Zhang, a graduate student working in Stanford University’s chemistry department, says the “tag-team” approach between predictive modeling and experimental lab work by IBM Research and Stanford University took a lot of the “guess work” out of the process and helped accelerate the materials discover process. The work was recently published in Nature Chemistry.

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