[May 20th 2020] LabMeeting: Towards understanding glasses with graph neural networks

Niccolò Pancino

May 20, 2020 – 11:00 AM
Conference Meeting

The glass transition is a reversible transition that occurs when an amorphous polymer material is heated or cooled in a particular temperature range. On cooling, the material becomes less flexible, like a glass, and on heating becomes soft. This characteristics dramatically affects the usefulness and processability of organic materials in many fields.
Despite decades of theoretical studies, the nature of the glass transition remains elusive and debated, while the existence of structural predictors of its dynamics is a major open question.
Recent approaches propose inferring predictors using machine learning. Here, the long-time evolution of a glassy system is determined solely from the initial particle position, using graph neural networks as a powerful model.

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