Cumulative complexity meta-metrics as an efficiency measure and predictor of process mass intensity (PMI) during synthetic route design,Green Chemistry

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Cumulative complexity meta-metrics as an efficiency measure and predictor of process mass intensity (PMI) during synthetic route design
Green Chemistry ( IF 9.3 ) Pub Date : 2023-06-23 , DOI: 10.1039/d3gc00878a
Lucrezia Angelini ₁ , Charlotte E. Coomber ₁ , Gareth P. Howell ₁ , George Karageorgis ₁ , Brian A. Taylor ₁

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Functioning as a surrogate for step count, a cumulative complexity meta-metric (∑C_M*), calculated along the longest linear sequence of a synthetic route, is demonstrated to be a useful predictor of process mass intensity (PMI). In contrast, common theoretical measures of efficiency such as ideality and convergence, in this case, were found to be of limited use. A workflow and model are presented which allow prediction of PMI from ∑C_M* for small molecules (<600 Da) with good accuracy (R² > 0.9) when applied to a test dataset and a small number of literature examples. Requiring no empirical investigation, this method provides estimates of achievable, long-term PMI for synthetic routes and can be applied at the design phase. The overall procedure has been developed to be amenable to future automation, allowing rapid application across large numbers of synthetic routes.

中文翻译：

累积复杂性元指标作为合成路线设计过程中过程质量强度 (PMI) 的效率衡量和预测指标

作为步数的替代，沿着合成路线的最长线性序列计算的累积复杂性元度量 (Σ C _{M* ) 被证明是过程质量强度 (PMI) 的有用预测因子。}相比之下，在这种情况下，常见的效率理论衡量标准（例如理想性和收敛性）的用途有限。提出了一个工作流程和模型，可以根据 Σ C _M*预测小分子 (<600 Da) 的 PMI，具有良好的准确性 ( R ²> 0.9）当应用于测试数据集和少量文献示例时。该方法无需实证调查，即可提供合成路线可实现的长期 PMI 估计，并可在设计阶段应用。整个程序的开发适合未来的自动化，允许在大量合成路线中快速应用。

更新日期：2023-06-27

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