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Journal Article

Combinatorial optimization and synthesis of multiple promoted MoVNbTe catalysts for oxidation of propane to acrylic acid


Trunschke,  Annette
Inorganic Chemistry, Fritz Haber Institute, Max Planck Society;


Schlögl,  Robert
Inorganic Chemistry, Fritz Haber Institute, Max Planck Society;

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Tompos, A., Sanchez-Sanchez, M., Végvári, L., Szijjártó, G. P., Margitfalvi, J. L., Trunschke, A., et al. (2021). Combinatorial optimization and synthesis of multiple promoted MoVNbTe catalysts for oxidation of propane to acrylic acid. Catalysis Today, 363, 45-54. doi:10.1016/j.cattod.2019.03.047.

Cite as: http://hdl.handle.net/21.11116/0000-0003-7A27-9
New MoVTeNb multi-component catalysts (so-called M1 phase) were designed and tested using combinatorial and high-throughput methods. An international team of academic institutes and industrial partners has cooperated to understand the chemistry occurring during the hydrothermal synthesis and crystallization of the M1 phase of the MoVTeNb mixed oxide. With this information, the optimization of this catalyst system could be targeted with the aim of improving catalyst performance for short chain alkane – ethane and propane - oxidation reactions. Beside the elements responsible for the formation of the M1 phase (Mo, V, Te, and Nb) and promoters found to be advantageous in our previous work (Mn, Ni, W and citric acid), the following components were added to the synthesis mixture: Ce, Cu, Co, Cr and ethylene glycol. Contrary to the previous approach in this study, the V/Mo, Te/Mo and Nb/Mo ratios were kept constant. Consequently, the experimental space had nine variables. The discrete levels of variables are established in such a way that the number of the potential experimental points in the multi-dimensional experimental space was in the range of 200 000. Five new generations were designed using an optimization platform consisting of holographic optimization algorithm and artificial neural networks. Altogether 250 catalysts were prepared and tested. A complex objective function was created consisting of two independent catalytic performance characteristics – conversion and product selectivity – as well as the expected production costs and prices of the target product acrylic acid (AA) and export steam. The AA production costs were estimated assuming a recycle scheme for such a future AA plant with standard downstream equipment. The best catalysts in the group of catalysts with low vanadium content gave acrylic acid yields of 58% in the high throughput tests after five generations. On the bases of holographic maps, correlations between the composition of the synthesis mixtures and the yields of AA were visualized allowing to see the cross effect between components. Mn and Co had a positive effect, while Cu and Ce resulted in negative effect on the yield of AA. The analysis of the correlation between conversions vs. product yields allowed figuring out the main reaction routes leading to acrylic acid and CO2 in a consecutive reaction scheme. Following this successful high throughput development, the hydrothermal method using the newly identified synthesis aids was further optimized and successfully scaled up to 40 l autoclaves using the cheapest available chemicals, the oxides. This now renders possible the large-scale production of that complex MoVNbTe mixed oxide catalyst.