Adsorption of charge-bidisperse mixtures of colloidal particles

Careful control of the microstructure of an adsorbed monolayer of colloidal particles is important for creating nanostructured devices through self-as sembly processes, and the structural and functional complexity of self-asse mbled particulate monolayers increases with the number of components in the system. Here, we perform simulations of the adsorption of binary mixtures of Brownian, colloidal particles to explore and identify combinations of pa rameters that produce technologically interesting surface structures. The s ystem contains two types of particles of identical radii but differing surf ace potentials. In one scheme, Brownian dynamics simulations begin with an evenly distributed mixture above a charged planar surface, and the particle s adsorb to the surface until the system achieves a steady state. In the se cond scheme, two different single-component suspensions are exposed to the substrate sequentially. Volume fractions in the bulk control relative surfa ce coverages, and the observed structures include isolated, high-potential particles and chains and clusters of low-potential particles. Substitutiona lly disordered lattices form for ratios of particle potential ranging from about 1.5 to 4, depending on parameters: ordered lattices are more stable t o bidispersity at higher wall potentials and higher particle potentials. Te rminal fractional bidispersities based on equivalent hard disk (EHD) radii vary from 3.6 to 10%. In sequential adsorption, small amounts of the second component adsorb only for parameter combinations with minimal repulsions f rom preadsorbed particles and sufficient attraction to the surface, since c olloidal adsorption is a kinetically frustrated process. High-potential par ticles added to a monolayer of low-potential particles create isolated dots , and in reverse, low-potential particles dope lattices of high-potential p articles. The results of the simulations are discussed in the light of latt ice models and EHD models.