Community Based Data of Uranium Adsorption onto Quartz

This data upload includes a compilation of experiments for quantifying uranium adsorption onto quartz. The provided .csv file has been compiled from the literature in a findable, accessible, interoperable, reusable (FAIR) data format. This was accomplished using the Lawrence Livermore National Laboratory Surface Complexation Database Converter (SCDC) code written in the R programming language (free licensing available at https://ipo.llnl.gov/technologies/software/llnl-surface-complexation-database-converter-scdc). This constitutes all current data compiled on uranium-quartz interactions in the L-SCIE (LLNL Surface Complexation/Ion Exchange) database (as of 02/28/2022). This data was used to develop surface complexation models that fit the global community dataset (https://doi.org/10.1021/acs.est.1c07109). The FAIR-formatted dataset also enables the implementation of alternative machine-learning approaches that can be explored in the future.本数据集上传内容包含一套用于量化铀在石英表面吸附行为的实验汇编。所提供的.csv文件已从公开文献中整理得到，采用可发现、可访问、可互操作、可复用（FAIR，Findable, Accessible, Interoperable, Reusable）数据格式。本数据集通过使用劳伦斯利弗莫尔国家实验室开发的表面络合数据库转换器（SCDC）代码完成整理，该代码基于R编程语言编写，其免费授权信息可访问https://ipo.llnl.gov/technologies/software/llnl-surface-complexation-database-converter-scdc。截至2022年2月28日，本数据集涵盖了L-SCIE（LLNL表面络合/离子交换）数据库中所有已整理的铀-石英相互作用相关的现有数据。本数据集曾被用于开发适配全球社区数据集的表面络合模型，相关研究的DOI标识为https://doi.org/10.1021/acs.est.1c07109。此外，采用FAIR格式的本数据集还支持后续可探索的各类替代机器学习方法的实现。