Due to the lack of nano descriptors that can appropriately represent the wide chemical space of engineered nanomaterials (ENMs), applicability domain of nano-quantitative structure–activity relationship models are limited to certain types of ENMs, such as metal oxides, metals, carbon-based nanomaterials, or quantum dots. In this study, a size-dependent electron configuration fingerprint (SDEC FP) was introduced to estimate the quantity of electrons based on the core, doping, and coating materials of ENMs in different sizes. SDEC FP was used in prediction model development and nanostructure similarity analysis on datasets including metal and carbon-based nanomaterials with and without surface modifications. Cytotoxicity and zeta potential prediction models developed with SDEC FP achieved good prediction accuracies on test set. Nanostructure similarity analysis was performed through principal component analysis which showed that structural similarity between ENMs measured by SDEC FP was highly correlated with their properties.

由于缺乏能够恰当代表工程纳米材料（ENMs）广泛化学空间的纳米描述符，纳米定量构效关系模型的适用范围仅限于某些类型的ENMs，如金属氧化物、金属、碳-基于纳米材料或量子点。在这项研究中，引入了尺寸相关的电子配置指纹（SDEC FP）来估计基于不同尺寸 ENM 的核心、掺杂和涂层材料的电子数量。SDEC FP 用于预测模型开发和数据集的纳米结构相似性分析，包括具有和不具有表面修饰的金属和碳基纳米材料。使用 SDEC FP 开发的细胞毒性和 zeta 电位预测模型在测试集上实现了良好的预测精度。