Modelling Seeded Growth of Nanoparticles Far from Equilibrium

As modelling the synthesis of metallic nanoparticles leads to useful insights that guide experiments, we propose a novel numerical suite, NPGrowth, which is based on LAMMPS. NPGrowth enables us to simulate seed-mediated growth under a variety of conditions, even mimicking growth under extreme conditions. It allows one-by-one or N-by-N deposition, either when the incoming atoms are from uniformly distributed or well-defined and fixed spatial regions, onto selected targets, including those reminiscent of a chiral molecule. Moreover, NPGrowth enables the formation, through sintering, of two or more seeds, be that directional, soft-landed or through coalescence. After presenting a few toy models, we discuss the effect of directionality during the sintering of four Cu icosahedral seeds and the importance of identifying the sintering geometry following a pySNOW characterisation and classification.