Co3O4 particles grown over nanocrystalline CeO2: influence of precipitation agents and calcination temperature on the catalytic activity for methane oxidation

Crystalline cobalt oxides were prepared by a precipitation method using three different precipitation agents, IJNH4)2CO3, Na2CO3 and COIJNH2)2. Cobalt oxide nanoparticles corresponding to a Co3O4 loading of 30 wt% were also deposited over high-surface area nanocrystalline ceria by the same precipitation agents. The effect of calcination temperature, 350 or 650 °C, on the morphological and structural properties was evaluated. Characterization by BET, XRD, SEM, TEM, Raman spectroscopy, H2-TPR, XPS and NH3-TPD was performed and the catalytic properties were explored in the methane oxidation reaction. The nature of the precipitation agent strongly influenced the textural properties of Co3O4 and the Co3O4–CeO2 interface. The best control of the particle size was achieved by using COIJNH2)2 that produced small and regular crystallites of Co3O4 homogeneously deposited over the CeO2 surface. Such a Co3O4–CeO2 system precipitated by urea showed enhanced low-temperature reducibility and high surface Co3+ concentration, which were identified as the key factors for promoting methane oxidation at low temperature. Moreover, the synergic effect of cobalt oxide and nanocrystalline ceria produced stable full conversion of methane in the entire range of investigated temperature, up to 700–800 °C, at which Co3O4 deactivation usually occurs

3D printed catalytic reactors for aerobic selective oxidation of benzyl alcohol into benzaldehyde in continuous multiphase flow

In this work, novel, patterned monolithic reactors were devised to explore more efficient routes for reactant conversion in order to investigate their potential to replace the packed bed and batch reactors conventionally employed in chemical industries. Well-defined bimetallic formulations were developed to substitute platinum group metals and critical raw materials such as palladium and cobalt, at least in part, by less active, but more sustainable and cost-effective metals such as earth-abundant iron. FePd and FeCo based monoliths were 3D printed and stacked in a continuous flow tubular reactor for testing the selective oxidation of benzyl alcohol (BA) into benzaldehyde (BZ) under mild conditions (80–100 °C and atmospheric pressure). The novel monolithic reactors were evaluated against current state-of-the-art reactor technologies, conventional packed bed and batch reactors. The FeCo- and FePd-Al2O3-supported monolithic catalyst beds showed higher conversion and TOF than their packed bed counterparts under the same operating conditions, revealing the impact of the novel design on both regular geometry and composition. What is of particular interest in the catalytic measurements shown is that the combined stacking of two monoliths in a flow reactor, Al2O3-supported Fe and GO-supported FePd catalysts, can significantly improve the performance with an increase in TOF of up to 90% in comparison to their FePd analogues. Mathematical modelling was used to obtain additional insights into the physical and chemical processes governing the rate of BA conversion. It was found that due to the flow regime inside the microchannels, an axial dispersion model was appropriate, which allowed for mapping the concentration profiles of the reactants and products within the respective monolith geometries

Converting simulated total dry matter to fresh marketable yield for field vegetables at a range of nitrogen supply levels

Simultaneous analysis of economic and environmental performance of horticultural crop production requires qualified assumptions on the effect of management options, and particularly of nitrogen (N) fertilisation, on the net returns of the farm. Dynamic soil-plant-environment simulation models for agro-ecosystems are frequently applied to predict crop yield, generally as dry matter per area, and the environmental impact of production. Economic analysis requires conversion of yields to fresh marketable weight, which is not easy to calculate for vegetables, since different species have different properties and special market requirements. Furthermore, the marketable part of many vegetables is dependent on N availability during growth, which may lead to complete crop failure under sub-optimal N supply in tightly calculated N fertiliser regimes or low-input systems. In this paper we present two methods for converting simulated total dry matter to marketable fresh matter yield for various vegetables and European growth conditions, taking into consideration the effect of N supply: (i) a regression based function for vegetables sold as bulk or bunching ware and (ii) a population approach for piecewise sold row crops. For both methods, to be used in the context of a dynamic simulation model, parameter values were compiled from a literature survey. Implemented in such a model, both algorithms were tested against experimental field data, yielding an Index of Agreement of 0.80 for the regression strategy and 0.90 for the population strategy. Furthermore, the population strategy was capable of reflecting rather well the effect of crop spacing on yield and the effect of N supply on product grading