RedDB
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## Dataset Details ### Dataset Description RedDB: a computational database that contains 30861 molecules from two prominent classes of organic electroactive compounds, quinones and aza-aromatics, has been presented. RedDB incorporates miscellaneous physicochemical property information of the compounds that can potentially be employed as battery performance descriptors. RedDBs development steps, including: (i) chemical library generation, (ii) molecular property prediction based on quantum chemical calculations, (iii) aqueous solubility prediction using machine learning, (iv) data processing and database creation, have been described. - **Curated by:** - **License:** CC BY 4.0 ### Dataset Sources - [corresponding publication](https://doi.org/10.1038/s41597-022-01832-2) - [Data source](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/F3QFSQ) ## Citation **BibTeX:** ```bibtex @article{Elif2022, doi = {10.1021/ci300400a}, url = {https://doi.org/10.1038/s41597-022-01832-2}, year = {2022}, volume = {9}, number = {1}, author = {Elif Sorkun and Qi Zhang and Abhishek Khetan and Murat Cihan Sorkun and Suleyman Er}, journal = {Nature Scientific Data} ```
### 数据集详情 #### 数据集描述 本研究提出RedDB：这是一个收录30861个分子的计算数据库，其分子源自两类主流有机电活性化合物——醌类（quinones）与氮杂芳烃类（aza-aromatics）。RedDB包含该类化合物的各类理化性质信息，此类信息可作为电池性能的描述符使用。本文同时阐述了RedDB的构建流程，具体包括：(i) 化合物库生成；(ii) 基于量子化学计算的分子性质预测；(iii) 利用机器学习进行水溶性预测；(iv) 数据处理与数据库构建。 - **数据整理者：** - **许可协议：** CC BY 4.0 ### 数据集来源 - [相关研究论文](https://doi.org/10.1038/s41597-022-01832-2) - [原始数据来源](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/F3QFSQ) ### 引用 #### BibTeX格式引用： bibtex @article{Elif2022, doi = {10.1021/ci300400a}, url = {https://doi.org/10.1038/s41597-022-01832-2}, year = {2022}, volume = {9}, number = {1}, author = {Elif Sorkun and Qi Zhang and Abhishek Khetan and Murat Cihan Sorkun and Suleyman Er}, journal = {Nature Scientific Data} }
