Hydrogenation of levulinic acid to γ-valerolactone is a key reaction in the valorization of carbohydrates to renewable fuels and chemicals. State-of-the-art catalysts are based on supported noble metal nanoparticle catalysts. We report the utility of a bimetallic Fe-Re supported on TiO₂ for this reaction. A strong synergy was observed between Fe and Re for the hydrogenation of levulinic acid in water under mild conditions. Fe-Re/TiO₂ shows superior catalytic performance compared to monometallic Fe and Re catalysts at similar metal content. The hydrogenation activity of the bimetallic catalysts increased with Re content. H₂-TPR, XPS, XANES, EXAFS, Mössbauer spectroscopy, TEM, and low-temperature CO IR spectroscopy show that the bimetallic catalysts contain metallic Re nanoparticles covered by FeO_x species and small amounts of a Fe-Re alloy. Under reaction conditions, the partially reduced surface FeO_x species adsorb water and form Brønsted acidic OH groups, which are involved in dehydration of reaction intermediates. Under optimized conditions, nearly full conversion of levulinic acid with a 95 % yield of γ-valerolactone could be achieved at a temperature as low as 180 °C in water at a H₂ pressure of 40 bar.

The performance of a range of nanoparticulate gold catalysts in the hydrogenation of carbon dioxide to formates was investigated and a superior performance of Au/Al₂O₃ was revealed. The comparative studies with unsupported gold nanoparticles pointed to the crucial role of the metal–support interaction for the CO₂ hydrogenation activity. Cyanide leaching tests complemented by XPS and STEM studies point to the importance of metallic Au⁰ species for the catalytic activity. The Au/Al₂O₃ catalyst shows stable activity that allows reaching equilibrium formate yields in a broad temperature range. A kinetic study revealed that a near-zero apparent activation barrier for the hydrogenation reaction is an intrinsic property of the catalytic system. The reaction mechanism is proposed on the basis of the obtained reactivity and characterization data.