Ivailo Atanasov

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The surface composition of an Au-62at%Pd alloy has been studied by means of a catalytic atom probe (CAP) before and after exposures to nitric oxide (NO) at temperatures ranging from 300 to 573K for 20min. Subsequent CAP analysis at 100K revealed a considerable surface enrichment in Pd (to approximately 80at%) after exposure at 573K. This is correlated with(More)
In this work we address the challenge of furthering our understanding of the driving forces responsible for the metal-metal interactions in industrially relevant bimetallic nanocatalysts, by taking a comparative approach to the atomic scale characterization of two core-shell nanorod systems (AuPd and AuRh). Using aberration-corrected scanning transmission(More)
The nanoparticle phase diagram of an immiscible system is studied at the atomic level. Cu-Ag clusters with sizes 1000 and 2000 atoms, resulting from a global minimum search and belonging to icosahedral and crystalline structural motifs, are considered. We present the statistical analysis of the effect of temperature on the solubility of the two elements(More)
On the basis of ab initio calculations, we present a new parametrisation of the Vervisch-Mottet-Goniakowski (VMG) potential (Vervisch et al 2002 Phys. Rev. B 24 245411) for modelling the oxide-metal interaction. Applying this model to mimic the finite temperature behaviour of large platinum icosahedra deposited on the pristine MgO(1 0 0), we find the(More)
We introduce a novel empirical model for the adhesion of Pd clusters on the MgO{100} substrate. The new model corrects the known bias of previous models toward structures with large interfaces with the substrate due to the failure to account for the so-called "metal-on-top" effect, i.e., the enhancement of the adhesion due to the presence of other metal(More)
We implement and assess several statistical methods for rough surface morphology characterization, which can largely be divided into two classes. The first class is based on estimation of two-point, quadratic statistical functions and includes: estimates of the sample autocovariance function, sample height–height correlation (also, structure) function, and(More)
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