Descriptor for the Efficacy of Aliovalent Doping of Oxides and Its Application for the Charging of Supported Au Clusters

Abstract

We have studied aliovalent doping of oxides, which is central to many applications in technology, using density functional theory (DFT). We consider the following anionic/cationic donor/acceptor dopants in MgO: Al, F, N, P, Li, Na, and K. Not all dopants donate or accept charge to the full extent expected from their nominal oxidation state. Counterintuitively, the charge accepted/donated by a dopant is found to not scale with Δχ alone, where Δχ is the difference in electronegativities between the anion/cation dopant and the cation/anion of the host. Instead, by fitting to a database of our DFT results, we find that the appropriate descriptor is Δχ/ , where is the corresponding difference in atomic sizes. We then use to theoretically predict which systems might be most suitable for charging Au monomers or dimers positively or negatively when they are deposited on a doped MgO support. Our results show that at a doping concentration of 2.78%, we are able to tune the charge of Au monomers between −0.84 and +0.21 e and Au dimers between −0.87 and −0.16 e. This is interesting because differently charged Au clusters are optimal catalysts for different chemical reactions.

Using statistical learning to predict interactions between single metal atoms and modified MgO(100) supports

“…Ag, Nb, and Ru formed direct bonds to NO 2 during all optimization attempts, so their binding energies were excluded from the data set so that only surface-mediated effects were considered. Doping the oxide surface alters the electronic structure of the oxide in a manner similar to the adsorbates 37,39,[44][45][46] . Li, Na, B, and Al were chosen as dopants in this study, as they contain either one fewer or one additional valance electron compared to Mg.…”

“…Adsorbates from the reaction environment, or dopants present in the oxide structure, can enhance charge transfer at the metal/ support interface 31,[36][37][38][39][40] . Addou et al 41 demonstrated that adsorbed hydrogen atoms on the rutile TiO 2 (011)-(2 × 1) surface alters the binding energy of Pd atoms to the support, which stabilizes small Pd n clusters (i.e., n~1-3 atoms).…”

“…It therefore is ideal for investigating the effects of support modifications, as changes in its binding interaction with the supported metal can be attributed solely to the effects of the surface modification. Indeed, MgO has been used as a template for many investigations of metal/support interactions, such as demonstrating how the oxidation state of gold varies upon surface modification 39,66 and how linear scaling relationships can be derived for a wide variety of adsorbates at Au/oxide interfaces 67 . We modified the MgO substrate with surface dopants and adsorbates to induce electron-poor and electron-rich conditions, where we find that both lead to an enhancement of the metal binding energies due to an increase in charge transfer between the metal and the support, as expected from the irreducible nature of pristine MgO.…”

Support work function as a descriptor and predictor for the charge and morphology of deposited Au nanoparticles

“…7 Subsequently, we showed that similar wetting transitions are also observed at other cluster sizes. 59 Next, we considered the question of which dopants might be the most effective in tuning the charge of the cluster; in this previous study, 66 we expanded the chemical space to consider four kinds of dopants: anionic acceptors, cationic acceptors, anionic donors, and cationic donors. Only a single fixed dopant concentration and only the two smallest cluster sizes (Au monomers and dimers) were considered in this earlier study.…”

Ni/NiO Nanocomposites with Rich Oxygen Vacancies as High-Performance Catalysts for Nitrophenol Hydrogenation

“…No matter which strategy is adopted to tune the electronic structure of the metal nanocatalyst, the nanometals are generally supported on an oxide substrate with a large specific surface area. In this scenario, interactions with the oxide support significantly impact the electronic structures and in turn the catalytic performance of nanometals [21,22]. Recently, we have demonstrated that the electron exchange between the two phases is highly correlated with the Fermi level of the oxide support [23].…”