Inorganic
upconversion nanoparticles used in biological and medical
applications are typically coated with materials to make these particles
biocompatible, colloidally stable in aqueous media, and bioactive.
However, the design of the molecules used in this coating must be
carefully tuned to achieve these desired properties, and the molecular-scale
design rules required for this are not known. In this work, a molecular
dynamics simulation strategy is introduced to predict the structures
and properties of a family of diblock copolymers that are used to
coat the surface of upconversion nanoparticles in liquid water. These
polymers comprise blocks of poly(oligo (ethylene glycol) methyl ether
acrylate) and monoacryloxy ethyl phosphate, where the length of the
former block is varied to have 6, 13, 35, and 55 units. The optimal
polymer size for a range of properties is identified by modeling their
interactions with the aqueous NaGdF4 interface. The simulations
suggest that interparticle aggregation is likely for the smaller polymers
and that intrachain folding effects in the larger polymers strongly
influence the polymer/inorganic interaction. This in turn affects
the structure of the polymer/solvent interface and consequently governs
the efficiency of bioconjugation for these coated nanoparticles. The
outward presentation of carboxylate groups to the solvent is crucial
to the antibody binding efficiency, and this was predicted to be significantly
reduced for larger chains, consistent with recent experimental data.
Informed by this, mathematical models are formulated to predict the
relation between polymer sizes and three key properties: surface charge,
maximum loading, and maximum thickness of the coatings. This molecular
simulation strategy is generally applicable to determine the optimal
properties of polymer coatings prior to experiment.