BoltzTraP Materials Project Data

Effective mass and thermoelectric properties of 8924 compounds in The Materials Project database that are calculated by the BoltzTraP software package run on the GGA-PBE or GGA+U density functional theory calculation results. The properties are reported at the temperature of 300 Kelvin and the carrier concentration of 1e18 1/cm3.<br><br>Available as Monty Encoder encoded JSON and as CSV. Recommended access method is with the matminer Python package using the datasets module.<br> Note:* When doing machine learning, to avoid data leakage, one may want to only use the formula and structure data as features. For example, S_n is strongly correlated with PF_n and usually when one is available the other one is available too.<br>* It is recommended that dos and bandstructure objects are retrieved from Materials Project and then use dos, bandstructure and composition featurizers to generate input features.<br><br>Note on citations: If you found this dataset useful and would like to cite it in your work, please be sure to cite its original sources below rather than or in addition to this page.<br>Dataset described in:<br>Ricci, F. <i>et al.</i> An <i>ab initio</i> electronic transport database for inorganic materials. <i>Sci. Data</i> 4:170085 doi: 10.1038/sdata.2017.85 (2017).<br>Data converted from json files available on Dryad (see references 3-4):<br>Ricci F, Chen W, Aydemir U, Snyder J, Rignanese G, Jain A, Hautier G (2017) Data from: An ab initio electronic transport database for inorganic materials. Dryad Digital Repository. https://doi.org/10.5061/dryad.gn001

本数据集基于广义梯度近似-佩尔dew-伯克- Ernzerhof（GGA-PBE）或GGA+U密度泛函理论（density functional theory, DFT）的计算结果，通过BoltzTraP软件包对材料项目（The Materials Project）数据库中的8924种化合物进行计算，得到其有效质量（effective mass）与热电性能（thermoelectric properties）。相关物性参数均在300开尔文温度与1×10¹⁸ cm⁻³的载流子浓度下测定。

本数据集以Monty Encoder编码的JSON格式与CSV格式提供，推荐通过matminer Python包的datasets模块进行访问。

* 机器学习建模时，为避免数据泄露，建议仅将化合物化学式与结构数据用作特征。例如，S_n与PF_n存在强相关性，通常二者可同时获取。
* 建议从材料项目数据库中获取态密度（density of states, DOS）与能带结构（bandstructure）对象，随后结合态密度、能带结构与成分特征生成器构建输入特征。

引用说明：若本数据集对您的研究有所帮助并需在成果中引用，请务必引用其原始文献，而非仅引用本页面。
本数据集相关文献描述：
Ricci, F. 等. 面向无机材料的从头算（ab initio）电子输运数据库. 《Scientific Data》（Sci. Data）4:170085, doi: 10.1038/sdata.2017.85 (2017).
本数据集数据源自Dryad平台上的JSON文件（详见参考文献3-4）：
Ricci F, Chen W, Aydemir U, Snyder J, Rignanese G, Jain A, Hautier G (2017) 数据来自：面向无机材料的从头算电子输运数据库. Dryad数字知识库（Dryad Digital Repository）. https://doi.org/10.5061/dryad.gn001