Princeton Catalysis Initiative, Princeton University, Princeton, NJ, USA.
Nature. 2019 Jun;570(7760):175-181. doi: 10.1038/s41586-019-1288-y. Epub 2019 Jun 12.
Organic chemistry has largely been conducted in an ad hoc manner by academic laboratories that are funded by grants directed towards the investigation of specific goals or hypotheses. Although modern synthetic methods can provide access to molecules of considerable complexity, predicting the outcome of a single chemical reaction remains a major challenge. Improvements in the prediction of 'above-the-arrow' reaction conditions are needed to enable intelligent decision making to select an optimal synthetic sequence that is guided by metrics including efficiency, quality and yield. Methods for the communication and the sharing of data will need to evolve from traditional tools to machine-readable formats and open collaborative frameworks. This will accelerate innovation and require the creation of a chemistry commons with standardized data handling, curation and metrics.
有机化学在很大程度上是由学术实验室临时进行的，这些实验室由针对特定目标或假设进行研究的资助。虽然现代合成方法可以提供相当复杂的分子，但预测单个化学反应的结果仍然是一个主要挑战。需要改进对“箭头上方”反应条件的预测，以实现智能决策，选择由效率、质量和产量等指标指导的最佳合成序列。用于交流和共享数据的方法将需要从传统工具发展到机器可读格式和开放协作框架。这将加速创新，并需要创建一个具有标准化数据处理、策展和指标的化学公用事业。
