Abstract
High-frequency vibration proves a fundamental step towards scalable growth in colloidal crystals. Various experimentally-replicable vibration mechanisms are hereby devised and exerted on randomly generated silicoid particles to explore geometric and dynamic effects on the induced crystal at equilibrium state. The Discrete Element Method is employed, with inter-particle contact idealized by a linear mass–spring–dashpot system with Coulomb sliding friction. With the vertical (Z) direction determined by gravity, the mechanisms comprise vertical, circular, and angular oscillation, with the latter realized in the plane normal to gravity. Characterization of the generated crystal is quantified by a hybrid machine-learning algorithm developed upon direct correlation between the coordinate data, crystallinity and grain-surface parameters. Parametric analysis is carried out in terms of vibration parameters (frequency, amplitude and duration) and the square-prismatic box aspect ratio. Results manifest optimum values of box aspect ratio, vibration amplitude and frequency, with crystallinity parameters mostly saturating after 2 minutes of vibration.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
