Abstract
催化剂是决定聚烯烃的工业效率以及实现聚烯烃高端化的核心. 传统开发催化剂的过程, 采用试错法, 不仅实验步骤多、研发周期长, 而且需要消耗大量资源来研究催化性能. 实验分析很难挖掘出催化剂结构与聚合性能之间的内在关系. 高水平的量子化学计算可以准确地获取反应机理, 但针对宏量的实验数据，昂贵的计算成本是其局限. 大数据时代, 人工智能的发展势不可挡. 机器学习作为人工智能的核心策略表现出强大的预测能力, 并在科学、技术以及工业等各个领域获得了广泛的应用与发展. 本文主要介绍机器学习在聚烯烃催化剂中的最新研究进展, 并简要评述机器学习应用于聚烯烃催化中的机遇与挑战.
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