Zeta potential is usually measured to estimate the surface charge and the stability of nanomaterials, as changes in these characteristics directly influence the biological activity of a given nanoparticle. Nowadays, theoretical methods are commonly used for a pre-screening safety assessments of nanomaterials. At the same time, the consistency of data on zeta potential measurements in the context of environmental impact is an important challenge. The inconsistency of data measurements leads to inaccuracies in predictive modeling. In this article, we report a new curated dataset of zeta potentials measured for 208 silica- and metal oxide nanoparticles in different media. We discuss the data curation framework for zeta potentials designed to assess the quality and usefulness of the literature data for further computational modeling. We also provide an analysis of specific trends for the datapoints harvested from different literature sources. In addition to that, we present for the first time a structure-property relationship model for nanoparticles (nano-SPR) that predicts values of zeta potential values measured in different environmental conditions (i.e., biological media and pH).

通常测量 Zeta 电位以估计纳米材料的表面电荷和稳定性，因为这些特性的变化直接影响给定纳米粒子的生物活性。目前，理论方法通常用于纳米材料的预筛选安全性评估。同时，环境影响背景下 zeta 电位测量数据的一致性是一项重要挑战。数据测量的不一致导致预测建模不准确。在本文中，我们报告了在不同介质中测量 208 种二氧化硅和金属氧化物纳米粒子的新的 zeta 电位数据集。我们讨论了 zeta 电位的数据管理框架，旨在评估文献数据的质量和有用性，以进行进一步的计算建模。我们还对从不同文献来源收集的数据点的具体趋势进行了分析。除此之外，我们首次提出了一种纳米粒子（nano-SPR）的结构-性能关系模型，该模型可以预测在不同环境条件（即生物介质和 pH 值）下测量的 zeta 电位值。