Towards the Development of Global Nano-Quantitative Structure-Property Relationship Models: Zeta Potentials of Metal Oxide Nanoparticles.

Andrey Toropov,Natalia Sizochenko,Alla Toropova,Jerzy Leszczynski

doi:10.3390/nano8040243

Abstract

Zeta potential indirectly reflects a charge of the surface of nanoparticles in solutions and could be used to represent the stability of the colloidal solution. As processes of synthesis, testing and evaluation of new nanomaterials are expensive and time-consuming, so it would be helpful to estimate an approximate range of properties for untested nanomaterials using computational modeling. We collected the largest dataset of zeta potential measurements of bare metal oxide nanoparticles in water (87 data points). The dataset was used to develop quantitative structure–property relationship (QSPR) models. Essential features of nanoparticles were represented using a modified simplified molecular input line entry system (SMILES). SMILES strings reflected the size-dependent behavior of zeta potentials, as the considered quasi-SMILES modification included information about both chemical composition and the size of the nanoparticles. Three mathematical models were generated using the Monte Carlo method, and their statistical quality was evaluated (R2 for the training set varied from 0.71 to 0.87; for the validation set, from 0.67 to 0.82; root mean square errors for both training and validation sets ranged from 11.3 to 17.2 mV). The developed models were analyzed and linked to aggregation effects in aqueous solutions.

Highlights

Massive production of nanoparticle-based materials results in their release into the environment
The current study focuses on zeta potential measurements of of silicon- and metal oxide nanoparticles in water
We initially extracted more than 150 data points; after data curation, we included in the reliable dataset 87 zeta potential measurements from 12 literature sources (Table 1) [1,12,18,25,26,27,28,29,30,31,32,33]

Summary

Introduction

Massive production of nanoparticle-based materials results in their release into the environment. It is widely known that certain physical characteristics of nanoparticles, such as size, shape, charge, chemical composition, and the pH of the solution, may directly influence their toxicity [1,2,3,4]. Only three research articles have reported QSPR modeling of zeta potentials [17,18,19]. These nano-QSPR models focused only on chemical composition-dependent descriptors [17,18,19].

Methods

Results

Conclusion