Multi-Phasic Growth Mechanism of Colloidal Nanoparticles by Statistical Liquid Phase TEM

Nanoparticle nucleation and growth have long been of great interest in science and industry. Despite impressive advances in nanotechnology, the thermodynamic origin of nanocluster nucleation is still a mystery, and there is no quantitative understanding of nanoparticle growth dynamics. It is because of the complexity that intrinsically exists in nanoparticle growth pathways. A comprehensive understanding of the growth mechanism requires experimental investigation of nanoparticle growth from two different aspects: individual growth trajectories and kinetics in ensemble average. To address this issue, we monitor hundreds of individual trajectories of growing nanoparticles using liquid-phase transmission-electron-microscopy. Statistical analysis of ensemble growth trajectories reveals that the growth of nanoparticles can be classified into multiple distinct types and stages. We present a microscopic model and statistical mechanical theory that provide unified, quantitative understanding of the time-dependent mean, variance, and distribution of nanoparticle size at all stages of the nanoparticle growth processes observed. We find that strongly-nonextensive free energy originating from a nanoparticle’s edge interaction, motion, and conformational degeneracy, which has received little attention so far, plays an essential role in the nanocluster nucleation and non-classical growth dynamics.