Increasing the efficiency of optimized v-sba-15 catalysts in the selective oxidation of methane to formaldehyde by artificial neural network modelling

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. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

Combination of chemo- and biocatalysis: Conversion of biomethane to methanol and formic acid

In the present day, methanol is mainly produced from methane via reforming processes, but research focuses on alternative production routes. Herein, we present a chemo-/biocatalytic oxidation cascade as a novel process to currently available methods. Starting from synthetic biogas, in the first step methane was oxidized to formaldehyde over a mesoporous VOx/SBA-15 catalyst. In the second step, the produced formaldehyde was disproportionated enzymatically towards methanol and formic acid in equimolar ratio by formaldehyde dismutase (FDM) obtained from Pseudomonas putida. Two processing routes were demonstrated: (a) batch wise operation using free formaldehyde dismutase after accumulating formaldehyde from the first step and (b) continuous operation with immobilized enzymes. Remarkably, the chemo-/biocatalytic oxidation cascades generate methanol in much higher productivity compared to methane monooxygenase (MMO) which, however, directly converts methane. Moreover, production steps for the generation of formic acid were reduced from four to two stages. © 2019 by the authors

Enhancement and limits of the selective oxidation of methane to formaldehyde over V-SBA-15: Influence of water cofeed and product decomposition

The possibility of a selective catalytic oxidation of methane to formaldehyde has been known for decades, and positive influences of water added to the reaction mixture and ultra-short contact times have been reported. In the present work, the complexity of interdependencies has been revealed. Specific parameter variations can increase conversion and selectivity of the target product. Surprisingly, formaldehyde formation over VOx species and its decomposition in gas phase were equally dependent on the partial pressure of the added water, so that the sweet spot can only be found by varying the residence time. © 2021 The Author(s

Methoden zur Erhöhung der Formaldehydproduktivität und -selektivität in der Methanoxidation über Silica-geträgerten VOx-Katalysatoren

Im Rahmen dieser Arbeit wurde die Möglichkeit zur Steigerung der Formaldehydproduktivität von VOx/SiO2-Katalysatoren in der Selektivoxidation von Methan durch Syntheseoptimierung, Wasserzudosierung und Modellierung untersucht

Increasing the Efficiency of Optimized V-SBA-15 Catalysts in the Selective Oxidation of Methane to Formaldehyde by Artificial Neural Network Modelling

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