Dynamic Simulations On Particle Aggregation Process

Since the geometric parameters(sizes,structures,morphologies and so on)of nanomaterials are the key factors to determine their unique physical and chemical properties,investigations on the processes and mechanisms of nanostructure formation are significant for the development of nanoscience and the wide applications of nanomaterials.The traditional kinetic theory of crystallization proposes that the particles are formed through monomer-by-monomer addition,in which two steps are included,nucleation and growth.A series of classical crystallization mechanisms have been built up,like LaMer mechanism,Ostwald ripening,Lifshitz-Slyozov-Wagner mechanism and Watzky-Finke mechanism.In spite of the great success of the nucleation-growth theory,it is found that more and more crystallization phenomena cannot be interpreted and predicted by those classical mechanisms accompanying with numerous nanostructures being produced.In contrast to the conventional models,another category of crystallization by nanoparticle/cluster aggregation have been identified,which is called non-classical crystallization.Therefore,the classical theory is no more suitable due to the changes in precursors and precursor scales,and some novel mechanisms,such as oriented attachment,has been put forward and lots of techniques are being developed to characterize the features of non-classical crystallization.However,owing to the limitations on the temporal and spatial resolution of apparatuses,the dynamic process of agglomeration and interaction between aggregation building blocks cannot be accessed and thus it is difficult to achieve the principles of non-classical crystallization in depth from experimental aspects.Fortunately,the fast development of computers,especially the emergence of super calculation centers,combined with simulation algorithm and models,enables us to compensate the experimental shortages by numerical protocols.Over decades,material scientists were aware of the significance of kinetic processes for shape evolution.It was realized that the reaction process and diffusion process involved in the growth of materials are the two most representative kinetic processes.In this thesis,a combination of Brownian dynamics based DLVO methods and molecular dynamics was employed to simulate the aggregation behaviors of silver nanoparticles on the sub-nano and nano scales.Numerical models were built up to trace the crystalline alignment on microscale and the particle-to-particle interaction on mesoscale,and a systematic investigation was carried out on that how particles aggregated and what the decisive factors were.The main findings and achievements are shown as follows:(1)Construction of the basic frameworks for particle aggregation models.With the consideration for the computational scale and time scale,two simulation scales,sub-nano and nano scales were chosen to simulate the aggregation behavior of particles in different aggregation-diffusion systems.To observe the aggregation process of nanoparticles in real-time and quantify the influence of external factors like solvent viscosity and ionic strength by using the Brownian dynamic method and molecular dynamic method based on atom/molecule scale.As for the aggregation on the nanoscale,the DLVO potential was applied.DLVO potential contains Van der Waals attractive potential and double electic layer repulsive potential,which is suitable for describing the interaction of nanoparticles in solution.Meanwhile,every concerned parameter was normalized by the units of length,time and mass to accelerate the computional speed.However,the classical DLVO potential is employed to deal with building blocks as spheres and it has limitations in reflecting the oriented attachment of particles.Thus,the all atom model at sub-nano scale was proposed.The particle of all-atom model is polyhedron and it can present the interaction of different facets as facets appeared.The interaction between atoms was calculated by the embedded atom method and considering the stability of particles during simulations,icosahedrons and truncated octahedrons were selected as the building blocks.Icosahedrons were applied to explore the aggregation rules between isotropic units due icosahedral particles surrounded by pure(111)facets,while truncated octahedrons with different proportions of(111)and(100)facets were used to study the effects of anisotropic units on aggregate structures.(2)Aggregation processes simulated by Brownian dynamics based DLVO method on the nanoscale.The effects of building block sizes,aggregation(solution ion strength,surface potentials)and diffusion(solvent viscosity)were concluded by analyzing the aggregation rate of particles(temporal evolution of single nanoparticle),growth rate of aggregates(temporal evolution of average sizes,maximum sizes)and aggregates number.It was found that the larger was the building block,the slower was the random movement,so the more difficult was it to overcome the agglomeration barrier.For small particles,the Brownian motion was quite vigorous,so the aggregation probability was much higher than that of big particles.Due to the decline of agglomeration degrees,average and maximum sizes decreased with increasing build block sizes.Simultaneously,the energy barrier also depended on the surface potential and solution ion strength.Higher surface potentials and smaller ion strength(thicker double layers)resulted in higher energy barriers and gave rise to lower collision probability between particles.Therefore,both aggregation rates and aggregate sizes were reduced.Moreover,since the friction force employed on particles by solvents was proportional to both the particle size and solvent viscosity,the viscous effects were more significant for larger particles.Collision probability,aggregation rates and consequent aggregate sizes were obviously diminished.(3)Aggregation processes simulated by molecular dynamics on the sub-nanoscale.Via capturing the aggregate evolution from icosahedral and truncated octahedral building blocks,it is found that the particle aggregation started with the contact between edge atoms.Centering on the contact point,two particles completed crystalline alignment by free rotation and fusion of matched facets.With regard to agglomeration degrees,truncated octahedrons aggregated together more easily than icosahedrons,and truncated octahedral aggregates contained more building blocks and thus had bigger sizes,while icosahedral aggregates possessed more symmetrically geometric shapes.Through analysis of the aggregation pathways,the main reason accounting for above distinctions was the differences of surface energy,which depended on the surface areas of specific facets.Attachment preferred to occurred on those facets with large areas for that process was more thermodynamically favored because of more reduction of system energy after aggregation.In addition,the diffusive effects of building blocks on aggregation behaviors were investigated by adjusting the system temperature and solvent viscosity.The results indicated that ordered structures were formed under slow diffusion conditions because the random movement of building blocks was limited and they had enough relaxation time to perform lattice matching;otherwise,fast diffusion led to the increase of disorderness in aggregates.(4)Based on the simulations of particle aggregation on two scales,it is proposed that the future of the work in this thesis would be a combination of all-atom simulation and Brownian dynamics simulation into a consistently-formulated mesoscale model,in which the all-atom algorithm would be adopted when particles are close to each other,while the model would be switched into DLVO automatically when particles are mutually far away.And the feasibility of such a coupled mesoscale model would be demonstrated by calculating the interaction potential.