Characterizing Triboelectrification Size Effects Amongst Insulating Materials

Abstract

Triboelectrification is a phenomenon known to civilization in many forms: accumulation of static electricity when one rubs against a carpet, appearance of lightning during bad weather, and explosions in industry due to charge build up that ignite vapors in the environment. Despite triboelectrification being ubiquitous in our daily lives, our understanding of it is severely lacking. Triboelectrification occurs when two surfaces exchange electrons, ions, or even pieces of charged matter. Unfortunately, the exact mechanism of how charge is transferred and which charge species is transferred across a wide variety of materials, especially insulators, eludes us. Some open questions still remain, such as what drives charge segregation amongst chemically identical dielectric granular material that vary in size. Computational models have attempted to consolidate theory and phenomenological observations to address this open question and others. As a result, a concept known as an effective work function (EWF) was developed to describe a material's propensity to exchange charge. Using a well-known riboelectrification model coupled with computational fluid dynamic discrete element method (CFD-DEM) simulations, this thesis studies the charging behavior in a vibrated bed, where glass particles are shaken in polycarbonate and acrylic square prisms for a period of time before their charge is measured. The robustness of the model was tested by characterizing its ability to predict the observed charging behavior in our experiments. Simultaneously, the model was used to deduce whether EWF has an intrinsic dependency on particle size when dielectric insulator-insulator triboelectrification is studied. We discover that the model is robust and that there is a strong correlation between particle size and the magnitude of the EWF, noticing that larger particles possessed EWF values smaller in magnitude.