  Selective removal of heavy metals from water is a complex topic. We present a
theoretical computational approach, supported by experimental evidences, to
design a functionalized nanomaterial that is able to selectively capture
metallic ions from water in a self-assembling process. A theoretical model is
used to map an experimental mixture of Ag nanoparticles and either Co$^{2+}$ or
Ni$^{2+}$ onto an additive highly asymmetric attractive Lennard Jones binary
mixture. Extensive NVT (constant number of particles, volume, and temperature)
Monte Carlo simulations are performed to derive a set of parameters that first
induce aggregation among the two species in solution and then affect the
morphology of the aggregates. The computational predictions are thus compared
with the experimental results. The gathered insights can be used as guidelines
for the prediction of an optimal design of a new generation of selective
nanoparticles to be used for metallic ion adsorption and hence for maximizing
the trapping of ions in an aqueous solution.
