An Experimental and Computational Approach to the Development of ZnO Nanoparticles that are Safe by Design. Issue 26 (11th May 2016) - Le, Tu C.; Yin, Hong; Chen, Rui; Chen, Yandong; Zhao, Lin; Casey, Philip S.; Chen, Chunying; Winkler, David A.
Abstract : Zinc oxide nanoparticles have found wide application due to their unique optoelectronic and photocatalytic characteristics. However, their safety aspects remain of critical concern, prompting the use of physicochemical modifications of pristine ZnO to reduce any potential toxicity. However, the relationships between these modifications and their effects on biology are complex and still relatively unexplored. To address this knowledge gap, a library of 45 types of ZnO nanoparticles with varying particle size, aspect ratio, doping type, doping concentration, and surface coating is synthesized, and their biological effects measured. Three biological assays measuring cell damage or stress are used to study the responses of human umbilical vein endothelial cells (HUVECs) or human hepatocellular liver carcinoma cells (HepG2) to the nanoparticles. These experimental data are used to develop quantitative and predictive computational models linking nanoparticle properties to cell viability, membrane integrity, and oxidative stress. It is found that the concentration of nanoparticles the cells are exposed to, the type of surface coating, the nature and extent of doping, and the aspect ratio of the particles make significant contributions to the cell toxicity of the nanoparticles tested. Our study shows that it is feasible to generate models that could be used to design or optimize nanoparticles with commercially useful properties that are also safe to humans and the environment. Abstract : Modifying the surfaces of ZnO nanoparticles can reduce potential cell toxicity of these widely used particles . The relationship is elucidated between surface chemistry and toxicity by screening 45 modified ZnO nanoparticles for cell toxicity and generating quantitative, predictive computational models. The models can be used to design functional nanomaterials with lower adverse impacts than unmodified nanoparticles.