Data and code for target dependent cleaner production screening of end of life electric vehicle lithium ion battery recycling pathways

This dataset contains the cleaned data and reproducible code associated with the study “Target dependent cleaner production screening of recycling pathways for end of life electric vehicle lithium ion batteries using an interpretable machine learning framework”. The package provides harmonized scenario tables, deterministic target outputs, machine learning baseline inputs and results, uncertainty and robustness diagnostics, interpretability outputs, and figure source data for evaluating recycling pathways of end of life electric vehicle lithium ion batteries. The dataset supports target dependent cleaner production screening across recycling route, cathode chemistry, region, year, electricity scenario, cell basis and pack basis functional units. It is intended to allow readers to reproduce the main computational results, inspect route ranking logic, and verify the data products used for manuscript figures and supplementary analyses.本数据集包含与题为《基于可解释机器学习框架的退役电动汽车锂离子电池（end of life electric vehicle lithium ion batteries）回收路径目标依存型清洁生产筛选》的研究相关的经清洗预处理数据与可复现代码。该数据集套件提供了标准化情景表格、确定性目标输出、机器学习基准输入与结果、不确定性与鲁棒性诊断结果、可解释性输出，以及用于评估退役电动汽车锂离子电池回收路径的图片源数据。 本数据集支持针对回收路径、正极材料化学体系、区域、年份、电力情景、单体电池层级与电池包层级功能单元的目标依存型清洁生产筛选。其旨在帮助读者复现核心计算结果、核查回收路径排序逻辑，并验证用于论文配图与补充分析的数据产物。