A nano-SPR model for predicting the dissolution rate of metal and metal oxide nanomaterials in the aqueous environment

Abstract

The increasing presence of engineered nanomaterials (ENMs) in the environment has raised concerns regarding their toxicity and environmental fate. Dissolution plays a significant role in determining both the aspects. However, understanding and predicting the dissolution rate is a complex process influenced by various factors, including the nanoparticles’ properties and the surrounding environment's characteristics. This study aimed to develop a novel structure–property relationship (nano-SPR) classification model to predict the dissolution rate of metal and metal oxide ENMs by considering both the nanoparticle properties and the characteristics of the environment. The model assigns the dissolution rate to one of three classes, depending on the way of defining the dissolution rate threshold. The developed models exhibited good overall quality, with balanced accuracies ranging above 0.9 depending on the used model type. Through the analysis, we identified several important factors that significantly influenced the dissolution rate of the studied ENMs. These factors include bond dissociation enthalpy, solvation enthalpy, primary size, valence electron to core electron ratio in metals, pH of the medium, presence of light, temperature, and the initial concentration of the ENMs. The results provide valuable insights for assessing their environmental transport and fate, predicting their (eco)toxicity and grouping them.