TY - JOUR A1 - Kunkel, B. A1 - Kabelitz, Anke A1 - de Oliveira Guilherme Buzanich, Ana A1 - Wohlrab, S. T1 - Increasing the Efficiency of Optimized V-SBA-15 Catalysts in the Selective Oxidation of Methane to Formaldehyde by Artificial Neural Network Modelling JF - Catalysts N2 - The present study investigates the possibility of improving the selective oxidation of methane to formaldehyde over V-SBA-15 catalysts in two different ways. In a classical approach of catalyst optimization, the in situ synthesis of V-SBA-15 catalysts was optimized with regard to the applied pH value. Among the set of catalysts synthesized, a higher amount of incorporated vanadium, a higher content of polymeric VOx species as well as a less ordered structure of the support material were observed by increasing the pH values from 2.0 to 3.0. An optimum in performance during the selective oxidation of methane to formaldehyde with respect to activity and selectivity was found over V-SBA-15 prepared at a pH value of 2.5. With this knowledge, we have now evaluated the possibilities of reaction control using this catalyst. Specifically, artificial neural network modelling was applied after the collection of 232 training samples for obtaining insight into the influence of different reaction parameters (temperature; gas hourly space velocity (GHSV); and concentration of O2, N2 and H2O) onto methane conversion and selectivity towards formaldehyde. This optimization of reaction conditions resulted in an outstanding high space-time yield of 13.6 kgCH2O∙kgcat∙h−1 KW - Artificial neural network modelling KW - Selective oxidation KW - Molecular VOx catalysts KW - Formaldehyde PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-517420 DO - https://doi.org/10.3390/catal10121411 VL - 10 IS - 12 SP - 1411 PB - MDPI AN - OPUS4-51742 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Heilmann, Maria A1 - Prinz, Carsten A1 - Bienert, Ralf A1 - Wendt, R. A1 - Kunkel, B. A1 - Radnik, Jörg A1 - Hoell, A. A1 - Wohlrab, S. A1 - de Oliveira Guilherme Buzanich, Ana A1 - Emmerling, Franziska T1 - Size-Tunable Ni–Cu Core–Shell Nanoparticles—Structure, Composition, and Catalytic Activity for the Reverse Water–Gas Shift Reaction JF - Advanced Engineering Materials N2 - A facile and efficient methodology is described for the solvothermal synthesis of size-tunable, stable, and uniform NiCu core–shell nanoparticles (NPs) for application in catalysis. The diameter of the NPs is tuned in a range from 6 nm to 30 nm and to adjust the Ni:Cu ratio from 30:1 to 1:1. Furthermore, the influence of different reaction parameters on the final NPs is studied. The NPs are structurally characterized by a method combination of transmission electron microscopy, anomalous small-angle X-ray scattering, X-ray absorption fine structure, and X-ray photoelectron spectroscopy. Using these analytical methods, it is possible to elucidate a core–shell–shell structure of all particles and their chemical composition. In all cases, a depletion from the core to the shell is observed, with the core consisting of NiCu alloy, surrounded by an inner Ni-rich shell and an outer NiO shell. The SiO2-supported NiCu core–shell NPs show pronounced selectivity of >99% for CO in the catalytic reduction of CO2 to CO using hydrogen as reactant (reverse water–gas shift reaction) independent of size and Ni:Cu ratio. KW - Nanoparticles KW - Core-shell KW - Catalysis PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-543606 DO - https://doi.org/10.1002/adem.202101308 SN - 1438-1656 SP - 1 EP - 13 PB - Wiley VCH AN - OPUS4-54360 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -