Here, we demonstrate how machine learning enables the prediction of comonomers reactivity ratios based on the molecular structure of monomers. We combined multi-task learning, multi-inputs, and Graph Attention Network to build a model capable of predicting reactivity ratios based on the monomers chemical structures.
翻译:在这里,我们演示机器学习是如何根据单体分子结构预测共聚物反应率的。 我们结合了多任务学习、多投入和图形关注网络,以建立一个能够预测单体化学结构反应率的模型。