RedDB

## 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}
}