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Nanostructured materials based on CeO2 and Pt play a fundamental role in catalyst design. However, their characterization is often challenging due to their structural complexity and the tendency of the materials to change under reaction conditions. In this work, we combine calculations based on the density functional theory, a machine-learning assisted global optimization method (GOFEE), and ab initio thermodynamics to characterize stable oxidation states of ceria-supported PtyOx particles in different environments. The collection of global minima structures for different stoichiometries resulting from the global optimisation effort is used to assess the effect of temperature, oxygen pressure, and support interactions on the phase diagrams, oxidation states, and geometries of the PtyOx particles. We thus identify favoured structural motifs and O:Pt ratios, revealing that oxidized states of free-standing and ceria-supported platinum particles are more stable than reduced ones under a wide range of conditions. These results indicate that studies rationalizing activity of ceria-supported Pt clusters must consider oxidized states, and that previous understanding of such materials obtained only with fully reduced Pt clusters may be incomplete.

Nanostructured materials based on non-inert oxides CeO2 and PtyOx play a fundamental role in catalyst design. However, their characterization is often challenging due to their structural complexity and the tendency of the materials to change under reaction conditions. In this work, we combine calculations based on the density functional theory, a machine-learning assisted global optimization method (GOFEE) and ab initio thermodynamics to characterize stable oxidation states of ceria-supported PtyOx clusters in different environments. The collection of global minima for different stoichiometries resulting from the global optimisation effort is used to assess the effect of temperature, oxygen pressure, and support interactions on the phase diagrams, oxidation states, and structural properties of the PtyOx particles. We thus identify favoured structural motifs and O/Pt ratios, revealing that oxidized states of ceria-supported particles are more stable than reduced ones under a wide range of conditions. These results indicate that studies rationalizing activity of ceria-supported Pt clusters must consider such oxidized states, and that previous understanding of such materials obtained only with fully reduced Pt clusters may be incomplete.

Nanostructured materials based on non-inert oxides CeO2 and PtyOx play a fundamental role in catalyst design. However, their characterization is often challenging due to their structural complexity and the tendency of the materials to change under reaction conditions. In this work, we combine calculations based on the density functional theory, a machine-learning assisted global optimization method (GOFEE) and ab initio thermodynamics to characterize stable oxidation states of ceria-supported PtyOx clusters in different environments. The collection of global minima for different stoichiometries resulting from the global optimisation effort is used to assess the effect of temperature, oxygen pressure, and support interactions on the phase diagrams, oxidation states, and structural properties of the PtyOx particles. We thus identify favoured structural motifs and O/Pt ratios, revealing that oxidized states of ceria-supported particles are more stable than reduced ones under a wide range of conditions. These results indicate that studies rationalizing activity of ceria-supported Pt clusters must consider such oxidized states, and that previous understanding of such materials obtained only with fully reduced Pt clusters may be incomplete.