Machine Learning Enabled Discovery of Application Dependent Design Principles for Two-dimensional Materials

19 Mar 2020Victor VenturiHolden ParksZeeshan AhmadVenkatasubramanian Viswanathan

The large-scale search for high-performing candidate 2D materials is limited to calculating a few simple descriptors, usually with first-principles density functional theory calculations. In this work, we alleviate this issue by extending and generalizing crystal graph convolutional neural networks to systems with planar periodicity, and train an ensemble of models to predict thermodynamic, mechanical, and electronic properties... (read more)

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