环保绝缘气体对于输配电装备绿色升级至关重要。尽管已有研究针对环保气体绝缘性能与物化性质展开预测建模,但生物安全性作为实际应用中的关键指标,其结构影响因素与其他性能参数显著不同,亟需构建独立的生物安全性预测模型来进行筛选和设计工作。为此,该研究基于经济合作与发展组织(Organization for Economic Co-operation and Development,OECD)指导原则,首次构建了碳氟类环保绝缘气体的急性吸入毒性定量-构效关系(structure-activity relationship,QSAR)模型。采用多种机器学习算法建模,并通过性能评估筛选出径向基函数核支持向量机(support vector machine with radial basis function kernel
Eco-friendly insulating gases are essential for the green upgrading of power transmission and distribution systems. Although predictive modeling of insulation performance and physicochemical properties has been widely studied
biosafety
as a critical practical indicator
is governed by distinct structural factors and requires independent predictive models. In this work
following OECD guidelines
we developed the first QSAR models for the acute inhalation toxicity of fluorocarbon-based eco-friendly insulating gases. Through performance evaluation
support vector machine with radial basis function kernel (SVM-RBF) and eXtreme gradient boosting(XGBoost) were selected as two top-performing models
which demonstrated excellent performance in training set fitting capability
cross-validation stability
and external prediction generalizability. The SHapley additive explanations(SHAP) analysis was further applied to interpret the relationships between key molecular descriptors and toxicity
revealing the core structural features influencing biosafety. The results provide a theoretical basis and analytical framework for the molecular design and risk control of fluorocarbon-based eco-friendly insulating gases.