Tuning the electron transfer properties of entire nanodiamond ensembles

Many of the promising new biomedical applications of diamond nanoparticles are moderated by charge transfer reactions, occurring between different surface facets and the surrounding molecules and/or environment. In this context the sign and value of properties such as the ionization potential, electron affinity, electronegativity, and chemical hardness can be useful indicators of the efficiency of nanodiamonds for different reactions and can help identify new application areas. However, because nanodiamond samples cannot currently be perfectly monodispersed, it is necessary to predict these properties for polydispersed ensembles of particles and provide a statistical solution. In this study we use some simple statistical methods, in combination with electronic structure simulations, to predict the charge transfer properties of different types of ensembles where restrictions have been placed on the diversity of the structures. By predicting quality factors for a variety of cases, we find that there is a clear motivation for enriching samples with {111} facets (or suppressing the prevalence of {100} facets) to increase the selectivity and efficiency of charge transfer reactions; even if samples cannot be completely purified.