Stein Helge S, Soedarmadji Edwin, Newhouse Paul F, Gregoire John M
Joint Center for Artificial Photosynthesis, California Institute of Technology, Pasadena, California, 91125, USA.
Sci Data. 2019 Mar 27;6(1):9. doi: 10.1038/s41597-019-0019-4.
Optical absorption spectroscopy is an important materials characterization for applications such as solar energy generation. This data descriptor describes the to date (Dec 2018) largest publicly available curated materials science dataset for near infrared to near UV (UV-Vis) light absorbance, composition and processing properties of metal oxides. By supplying the complete synthesis and processing history of each of the 179072 samples from 99965 unique compositions we believe the dataset will enable the community to develop predictive models for materials, such as prediction of optical properties based on composition and processing, and ultimately serve as a benchmark dataset for continued integration of machine learning in materials science. The dataset is also a resource for identifying materials composition and synthesis to attain specific optical properties.
光学吸收光谱法是一种重要的材料表征方法，适用于太阳能发电等应用。本数据描述符介绍了截至2018年12月最大的公开可用的经过整理的材料科学数据集，该数据集涉及近红外到近紫外（紫外可见）光吸收率、金属氧化物的成分和加工特性。通过提供来自99965种独特成分的179072个样品中每个样品的完整合成和加工历史，我们相信该数据集将使科学界能够开发材料预测模型，例如基于成分和加工预测光学性质，并最终作为在材料科学中持续集成机器学习的基准数据集。该数据集也是识别材料成分和合成以获得特定光学性质的资源。
