Stability of bimetallic Pd-Zn catalysts for the steam reforming of methanol

ZnO-supported palladium-based catalysts have been shown in recent years to be both active and selective towards the steam reforming of methanol, although they are still considered to be less active than traditional copper-based catalysts. The activity of PdZn catalysts can be significantly improved by supporting them on alumina. Here we show that the Pd/ZnO/Al2O3 catalysts have better long-term stability when compared with commercial Cu/ZnO/Al2O3 catalysts, and that they are also stable under redox cycling. The Pd/ZnO/Al2O3 catalysts can be easily regenerated by oxidation in air at 420 °C followed by re-exposure to reaction conditions at 250 °C, while the Cu/ZnO based catalysts do not recover their activity after oxidation. Reduction at high temperatures (>420 °C) leads to Zn loss from the alloy nanoparticle surface resulting in a reduced catalyst activity. However, even after such extreme treatment, the catalyst activity is regained with time on stream under reaction conditions alone, leading to highly stable catalysts. These findings illustrate that the nanoparticle surface is dynamic and changes drastically depending on the environment, and that elevated reduction temperatures are not necessary to achieve high CO2 selectivity

Familiarity Differentially Affects Right Hemisphere Contributions to Processing Metaphors and Literals

The role of the two hemispheres in processing metaphoric language is controversial. While some studies have reported a special role of the right hemisphere (RH) in processing metaphors, others indicate no difference in laterality relative to literal language. Some studies have found a role of the RH for novel/unfamiliar metaphors, but not conventional/familiar metaphors. It is not clear, however, whether the role of the RH is specific to metaphor novelty, or whether it reflects processing, reinterpretation or reanalysis of novel/unfamiliar language in general. Here we used functional magnetic resonance imaging (fMRI) to examine the effects of familiarity in both metaphoric and non-metaphoric sentences. A left lateralized network containing the middle and inferior frontal gyri, posterior temporal regions in the left hemisphere (LH), and inferior frontal regions in the RH, was engaged across both metaphoric and non-metaphoric sentences; engagement of this network decreased as familiarity decreased. No region was engaged selectively for greater metaphoric unfamiliarity. An analysis of laterality, however, showed that the contribution of the RH relative to that of LH does increase in a metaphor-specific manner as familiarity decreases. These results show that RH regions, taken by themselves, including commonly reported regions such as the right inferior frontal gyrus (IFG), are responsive to increased cognitive demands of processing unfamiliar stimuli, rather than being metaphor-selective. The division of labor between the two hemispheres, however, does shift towards the right for metaphoric processing. The shift results not because the RH contributes more to metaphoric processing. Rather, relative to its contribution for processing literals, the LH contributes less

Aerosol–cloud drop concentration closure in warm cumulus

Our understanding of the activation of aerosol particles into cloud drops during the formation of warm cumulus clouds presently has a limited observational foundation. Detailed observations of aerosol size and composition, cloud microphysics and dynamics, and atmospheric thermodynamic state were collected in a systematic study of 21 cumulus clouds by the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft during NASA's Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE). An “aerosol-cloud” closure study was carried out in which a detailed cloud activation parcel model, which predicts cloud drop concentration using observed aerosol concentration, size distribution, cloud updraft velocity, and thermodynamic state, is evaluated against observations. On average, measured droplet concentration in adiabatic cloud regions is within 15% of the predictions. This agreement is corroborated by independent measurements of aerosol activation carried out by two cloud condensation nucleus (CCN) counters on the aircraft. Variations in aerosol concentration, which ranged from 300 to 3300 cm^(−3), drives large microphysical differences (250–2300 cm^(−3)) observed among continental and maritime clouds in the South Florida region. This is the first known study in which a cloud parcel model is evaluated in a closure study using a constraining set of data collected from a single platform. Likewise, this is the first known study in which relationships among aerosol size distribution, CCN spectrum, and cloud droplet concentration are all found to be consistent with theory within experimental uncertainties much less than 50%. Vertical profiles of cloud microphysical properties (effective radius, droplet concentration, dispersion) clearly demonstrate the boundary layer aerosol's effect on cloud microphysics throughout the lowest 1 km of cloud depth. Onboard measurements of aerosol hygroscopic growth and the organic to sulfate mass ratio are related to CCN properties. These chemical data are used to quantify the range of uncertainty associated with the simplified treatment of aerosol composition assumed in the closure study

Dynamic Time-Warping Correction for Shifts in Ultrahigh Resolving Power Ion Mobility Spectrometry and Structures for Lossless Ion Manipulations

Detection of arrival time shifts between ion mobility spectrometry (IMS) separations can limit achievable resolving power (Rp), particularly when multiple separations are summed or averaged, as commonly practiced in IMS. Such variations can be apparent in higher Rp measurements and are particularly evident in long path length traveling wave structures for lossless ion manipulations (SLIM) IMS due to their typically much longer separation times. Here, we explore data processing approaches employing single value alignment (SVA) and nonlinear dynamic time warping (DTW) to correct for variations between IMS separations, such as due to pressure fluctuations, to enable more effective spectrum summation for improving Rp and detection of low-intensity species. For multipass SLIM IMS separations, where narrow mobility range measurements have arrival times that can extend to several seconds, the SVA approach effectively corrected for such variations and significantly improved Rp for summed separations. However, SVA was much less effective for broad mobility range separations, such as obtained with multilevel SLIM IMS. Changes in ions’ arrival times were observed to be correlated with small pressure changes, with approximately 0.6% relative arrival time shifts being common, sufficient to result in a loss of Rp for summed separations. Comparison of the approaches showed that DTW alignment performed similarly to SVA when used over a narrow mobility range but was significantly better (providing narrower peaks and higher signal intensities) for wide mobility range data. We found that the DTW approach increased Rp by as much as 115% for measurements in which 50 IMS separations over 2 s were summed. We conclude that DTW is superior to SVA for ultra-high-resolution broad mobility range SLIM IMS separations and leads to a large improvement in effective Rp, correcting for ion arrival time shifts regardless of the cause, as well as improving the detectability of low-abundance species. Our tool is publicly available for use with universal ion mobility format (.UIMF) and text (.txt) files