Structure sensitivity of CO2 hydrogenation on Ni revisited

Despite the large number of studies on the catalytic hydrogenation of CO2 to CO and hydrocarbons by metal nanoparticles, the nature of the active sites and the reaction mechanism have remained unresolved. This hampers the development of effective catalysts relevant to energy storage. By investigating the structure sensitivity of CO2 hydrogenation on a set of silica-supported Ni nanoparticle catalysts (2–12 nm), we found that the active sites responsible for the conversion of CO2 to CO are different from those for the subsequent hydrogenation of CO to CH4. While the former reaction step is weakly dependent on the nanoparticle size, the latter is strongly structure sensitive with particles below 5 nm losing their methanation activity. Operando X-ray diffraction and X-ray absorption spectroscopy results showed that significant oxidation or restructuring, which could be responsible for the observed differences in CO2 hydrogenation rates, was absent. Instead, the decreased methanation activity and the related higher CO selectivity on small nanoparticles was linked to a lower availability of step edges that are active for CO dissociation. Operando infrared spectroscopy coupled with (isotopic) transient experiments revealed the dynamics of surface species on the Ni surface during CO2 hydrogenation and demonstrated that direct dissociation of CO2 to CO is followed by the conversion of strongly bonded carbonyls to CH4. These findings provide essential insights into the much debated structure sensitivity of CO2 hydrogenation reactions and are key for the knowledge-driven design of highly active and selective catalysts

Data2Game: Towards an Integrated Demonstrator

The Data2Game project investigates how the efficacy of computerized training games can be enhanced by tailoring training scenarios to the individual player. The research is centered around three research innovations: (1) techniques for the automated modelling of players’ affective states, based on exhibited social signals, (2) techniques for the automated generation of in-game narratives tailored to the learning needs of the player, and (3) validated studies on the relation of the player behavior and game properties to learning performance. This paper describes the integration of the main results into a joint prototype

Structure Sensitivity of CO2_2 Hydrogenation on Ni Revisited

Despite the large number of studies on the catalytic hydrogenation of CO$_2$ to CO and hydrocarbons by metal nanoparticles, the nature of the active sites and the reaction mechanism have remained unresolved. This hampers the development of effective catalysts relevant to energy storage. By investigating the structure sensitivity of CO$_2$ hydrogenation on a set of silica-supported Ni nanoparticle catalysts (2–12 nm), we found that the active sites responsible for the conversion of CO$_2$ to CO are different from those for the subsequent hydrogenation of CO to CH$_4$. While the former reaction step is weakly dependent on the nanoparticle size, the latter is strongly structure sensitive with particles below 5 nm losing their methanation activity. Operando X-ray diffraction and X-ray absorption spectroscopy results showed that significant oxidation or restructuring, which could be responsible for the observed differences in CO$_2$ hydrogenation rates, was absent. Instead, the decreased methanation activity and the related higher CO selectivity on small nanoparticles was linked to a lower availability of step edges that are active for CO dissociation. Operando infrared spectroscopy coupled with (isotopic) transient experiments revealed the dynamics of surface species on the Ni surface during CO$_2$ hydrogenation and demonstrated that direct dissociation of CO$_2$ to CO is followed by the conversion of strongly bonded carbonyls to CH$_4$. These findings provide essential insights into the much debated structure sensitivity of CO$_2$ hydrogenation reactions and are key for the knowledge-driven design of highly active and selective catalysts

Data2Game: Towards an Integrated Demonstrator

The Data2Game project investigates how the efficacy of computerized training games can be enhanced by tailoring training scenarios to the individual player. The research is centered around three research innovations: (1) techniques for the automated modelling of players’ affective states, based on exhibited social signals, (2) techniques for the automated generation of in-game narratives tailored to the learning needs of the player, and (3) validated studies on the relation of the player behavior and game properties to learning performance. This paper describes the integration of the main results into a joint prototype

Examples of spectra including the renal parenchyma and sinus, and including only the renal parenchyma.

<p>Unsuppressed localized renal proton spectra of triglyceride (TG) content with deliberate planning of the voxel including the renal sinus (in green) and including only the renal parenchyma (in red). Percentages TG content in this particular volunteer were 18% (renal sinus) and 0.64% (parenchyma).</p

Metabolic imaging of fatty kidney in diabesity : Validation and dietary intervention

Background Obesity and type 2 diabetes have not only been linked to fatty liver, but also to fatty kidney and chronic kidney disease. Since non-invasive tools are lacking to study fatty kidney in clinical studies, we explored agreement between proton magnetic resonance spectroscopy (1 H-MRS) and enzymatic assessment of renal triglyceride content (without and with dietary intervention). We further studied the correlation between fatty kidney and fatty liver. Methods Triglyceride content in the renal cortex was measured by 1 H-MRS on a 7-Tesla scanner in 27 pigs, among which 15 minipigs had been randomized to a 7-month control diet, cafeteria diet (CAF) or CAF with low-dose streptozocin (CAF-S) to induce insulin-independent diabetes. Renal biopsies were taken from corresponding MRS-voxel locations. Additionally, liver biopsies were taken and triglyceride content in all biopsies was measured by enzymatic assay. Results Renal triglyceride content measured by 1 H-MRS and enzymatic assay correlated positively (r = 0.86, P < 0.0001). Compared with control diet-fed minipigs, renal triglyceride content was higher in CAF-S-fed minipigs (137 ± 51 nmol/mg protein, mean ± standard error of the mean, P < 0.05), but not in CAF-fed minipigs (60 ± 10 nmol/mg protein) compared with controls (40 ± 6 nmol/mg protein). Triglyceride contents in liver and kidney biopsies were strongly correlated (r = 0.97, P < 0.001). Conclusions Non-invasive measurement of renal triglyceride content by 1 H-MRS closely predicts triglyceride content as measured enzymatically in biopsies, and fatty kidney appears to develop parallel to fatty liver. 1 H-MRS may be a valuable tool to explore the role of fatty kidney in obesity and type 2 diabetic nephropathy in humans in vivo

Metabolic Imaging of Human Kidney Triglyceride Content: Reproducibility of Proton Magnetic Resonance Spectroscopy

OBJECTIVE: To assess the feasibility of renal proton magnetic resonance spectroscopy for quantification of triglyceride content and to compare spectral quality and reproducibility without and with respiratory motion compensation in vivo. MATERIALS AND METHODS: The Institutional Review Board of our institution approved the study protocol, and written informed consent was obtained. After technical optimization, a total of 20 healthy volunteers underwent renal proton magnetic resonance spectroscopy of the renal cortex both without and with respiratory motion compensation and volume tracking. After the first session the subjects were repositioned and the protocol was repeated to assess reproducibility. Spectral quality (linewidth of the water signal) and triglyceride content were quantified. Bland-Altman analyses and a test by Pitman were performed. RESULTS: Linewidth changed from 11.5±0.4 Hz to 10.7±0.4 Hz (all data pooled, p<0.05), without and with respiratory motion compensation respectively. Mean % triglyceride content in the first and second session without respiratory motion compensation were respectively 0.58±0.12% and 0.51±0.14% (P = NS). Mean % triglyceride content in the first and second session with respiratory motion compensation were respectively 0.44±0.10% and 0.43±0.10% (P = NS between sessions and P = NS compared to measurements with respiratory motion compensation). Bland-Altman analyses showed narrower limits of agreement and a significant difference in the correlated variances (correlation of −0.59, P<0.05). CONCLUSION: Metabolic imaging of the human kidney using renal proton magnetic resonance spectroscopy is a feasible tool to assess cortical triglyceride content in humans in vivo and the use of respiratory motion compensation significantly improves spectral quality and reproducibility. Therefore, respiratory motion compensation seems a necessity for metabolic imaging of renal triglyceride content in vivo