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

Designing an Optimal Ion Adsorber at the Nanoscale: The Unusual Nucleation of AgNP/Co$^{2+}$ -- Ni$^{2+}$ Binary Mixtures