热化学
启发式
集合(抽象数据类型)
理论(学习稳定性)
工作(物理)
能量(信号处理)
算法
计算机科学
化学
数学
人工智能
机器学习
热力学
物理
统计
物理化学
程序设计语言
作者
Andrew S. Lee,Sarah N. Elliott,Hassan Harb,Logan Ward,Ian Foster,Larry A. Curtiss,Rajeev S. Assary
标识
DOI:10.1021/acs.jcim.3c01583
摘要
Predicting the synthesizability of a new molecule remains an unsolved challenge that chemists have long tackled with heuristic approaches. Here, we report a new method for predicting synthesizability using a simple yet accurate thermochemical descriptor. We introduce Emin, the energy difference between a molecule and its lowest energy constitutional isomer, as a synthesizability predictor that is accurate, physically meaningful, and first-principles based. We apply Emin to 134,000 molecules in the QM9 data set and find that Emin is accurate when used alone and reduces incorrect predictions of "synthesizable" by up to 52% when used to augment commonly used prediction methods. Our work illustrates how first-principles thermochemistry and heuristic approximations for molecular stability are complementary, opening a new direction for synthesizability prediction methods.
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