期刊
CRYSTENGCOMM
卷 17, 期 23, 页码 4272-4275出版社
ROYAL SOC CHEMISTRY
DOI: 10.1039/c4ce02403f
关键词
-
资金
- Commonwealth Scholarship Commission
- EPSRC [EP/I033459/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/I033459/1] Funding Source: researchfish
A random forest model has for the first time enabled the prediction of the crystallisability (crystals vs. no crystals) of organic molecules with similar to 70% accuracy. The predictive model is based on calculated molecular descriptors and published experimental crystallisation propensities of a library of substituted acylanilides.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据