Unraveling surface and bulk dynamics of iron(III) molybdate during oxidative dehydrogenation using operando and transient spectroscopies.

Iron(III) molybdate (Fe2(MoO4)3) is a commercial catalyst for the oxidative dehydrogenation (ODH) of methanol, but it has recently been shown to be relevant for other substrates as well. Despite its commercial use, a detailed mechanistic understanding of Fe2(MoO4)3 catalysts at the surface and in the bulk has been lacking, largely hampered by the lack of suitable spectroscopic methods, directly applicable under reaction conditions. Using propane ODH as an example, we highlight the potential of operando Raman and impedance spectroscopy combined with transient IR spectroscopy, to identify surface active sites and monitor the hydrogen transfer and oxygen dynamics. By comparison with the behavior of reference compounds (MoO3, MoOx/Fe2O3) a mechanistic model is proposed. The presence of iron greatly influences the reactivity behavior via oxygen diffusion but is moderated in its oxidative capacity by surface MoOx. Our approach directly elucidates fundamental properties of Fe2(MoO4)3 of general importance to selective oxidation catalysis.

MXene Aerogel Derived Ultra-Active Vanadia Catalyst for Selective Conversion of Sustainable Alcohols to Base Chemicals.

Selective oxidation reactions are an important class of the current chemical industry and will be highly important for future sustainable chemical production. Especially, the selective oxidation of primary alcohols is expected to be of high future interest, as alcohols can be obtained on technical scales from biomass fermentation. The oxidation of primary alcohols produces aldehydes, which are important intermediates. While selective methanol oxidation is industrially established, the commercial catalyst suffers from deactivation. Ethanol selective oxidation is not commercialized but would give access to sustainable acetaldehyde production when using renewable ethanol. In this work, it is shown that employing 2D MXenes as building blocks allows one to design a nanostructured oxide catalyst composed of mixed valence vanadium oxides, which outperforms on both reactions known materials by nearly an order of magnitude in activity, while showing high selectivity and stability. The study shows that the synthesis route employing 2D materials is key to obtain these attractive catalysts. V4C3Tx MXene structured as an aerogel precursor needs to be employed and mildly oxidized in an alcohol and oxygen atmosphere to result in the aspired nanostructured catalyst composed of mixed valence VO2, V6O13, and V3O7. Very likely, the bulk stable reduced valence state of the material together coupled with the nanorod arrangement allows for unprecedented oxygen mobility as well as active sites and results in an ultra-active catalyst.

Unraveling the Active Vanadium Sites and Adsorbate Dynamics in VOx/CeO2 Oxidation Catalysts Using Transient IR Spectroscopy.

The oxidative dehydrogenation (ODH) of propane over supported vanadia catalysts is an attractive route toward propene (propylene) with the potential of industrial application and has been extensively studied over decades. Despite numerous mechanistic studies, the active vanadyl site of the reaction has not been elucidated. In this work, we unravel the ODH reaction mechanism, including the nuclearity-dependent vanadyl and surface dynamics, over ceria-supported vanadia (VOx/CeO2) catalysts by applying (isotopic) modulation excitation IR spectroscopy supported by operando Raman and UV-vis spectroscopies. Based on our loading-dependent analysis, we were able to identify two different mechanisms leading to propylene, which are characterized by isopropyl- and acrylate-like intermediates. The modulation excitation IR approach also allows for the determination of the time evolution of the vanadia, hydroxyl, and adsorbate dynamics, underlining the intimate interplay between the surface vanadia species and the ceria support. Our results highlight the potential of transient IR spectroscopy to provide a detailed understanding of reaction mechanisms in oxidation catalysis and the dynamics of surface catalytic processes in general.

Elucidating CO2 Hydrogenation over In2 O3 Nanoparticles using Operando UV/Vis and Impedance Spectroscopies.

In2 O3 has emerged as a promising catalyst for CO2 activation, but a fundamental understanding of its mode of operation in CO2 hydrogenation is still missing, as the application of operando vibrational spectroscopy is challenging due to absorption effects. In this mechanistic study, we systematically address the redox processes related to the reverse water-gas shift reaction (rWGSR) over In2 O3 nanoparticles, both at the surface and in the bulk. Based on temperature-dependent operando UV/Vis spectra and a novel operando impedance approach for thermal powder catalysts, we propose oxidation by CO2 as the rate-determining step for the rWGSR. The results are consistent with redox processes, whereby hydrogen-containing surface species are shown to exhibit a promoting effect. Our findings demonstrate that oxygen/hydrogen dynamics, in addition to surface processes, are important for the activity, which is expected to be of relevance not only for In2 O3 but also for other reducible oxide catalysts.

Reduction Behavior of Cubic In2O3 Nanoparticles by Combined Multiple In Situ Spectroscopy and DFT.

Indium oxide (In2O3) has emerged as a highly active catalyst for methanol synthesis by CO2 hydrogenation. In this work we elucidate the reduction behavior and oxygen dynamics of cubic In2O3 nanoparticles by in situ Raman and UV-vis spectra in combination with density functional theory (DFT) calculations. We demonstrate that application of UV and visible Raman spectroscopy enables, first, a complete description of the In2O3 vibrational structure fully consistent with theory and, second, the first theoretical identification of the nature of defect-related bands in reduced In2O3. Combining these findings with quasi in situ XPS and in situ UV-vis measurements allows the temperature-dependent structural dynamics of In2O3 to be unraveled. While the surface of a particle is not in equilibrium with its bulk at room temperature, oxygen exchange between the bulk and the surface occurs at elevated temperatures, leading to an oxidation of the surface and an increase in oxygen defects in the bulk. Our results demonstrate the potential of combining different in situ spectroscopic methods with DFT to elucidate the complex redox behavior of In2O3 nanoparticles.

Evaluating Geometric Measurement Accuracy Based on 3D Reconstruction of Automated Imagery in a Greenhouse.

Geometric dimensions of plants are significant parameters for showing plant dynamic responses to environmental variations. An image-based high-throughput phenotyping platform was developed to automatically measure geometric dimensions of plants in a greenhouse. The goal of this paper was to evaluate the accuracy in geometric measurement using the Structure from Motion (SfM) method from images acquired using the automated image-based platform. Images of nine artificial objects of different shapes were taken under 17 combinations of three different overlaps in x and y directions, respectively, and two different spatial resolutions (SRs) with three replicates. Dimensions in x, y and z of these objects were measured from 3D models reconstructed using the SfM method to evaluate the geometric accuracy. A metric power of unit (POU) was proposed to combine the effects of image overlap and SR. Results showed that measurement error of dimension in z is the least affected by overlap and SR among the three dimensions and measurement error of dimensions in x and y increased following a power function with the decrease of POU (R² = 0.78 and 0.88 for x and y respectively). POUs from 150 to 300 are a preferred range to obtain reasonable accuracy and efficiency for the developed image-based high-throughput phenotyping system. As a study case, the developed system was used to measure the height of 44 plants using an optimal POU in greenhouse environment. The results showed a good agreement (R² = 92% and Root Mean Square Error = 9.4 mm) between the manual and automated method.