Direct conversion of methane to methanol using oxygen is experiencing renewed interest owing to the availability of new natural gas resources. Copper-exchanged zeolites such as mordenite and ZSM-5 have shown encouraging results, and di- and tri-copper species have been suggested as active sites. Recently, small eight-membered ring (8MR) zeolites including SSZ-13, -16, and -39 have been shown to be active for methane oxidation, but the active sites and reaction mechanisms in these 8MR zeolites are not known. In this work, we use density functional theory (DFT) calculations to systematically evaluate monocopper species as active sites for the partial methane oxidation reaction in Cu-exchanged SSZ-13. On the basis of kinetic and thermodynamic arguments, we suggest that [CuIIOH]+ species in the 8MR are responsible for the experimentally observed activity. Our results successfully explain the available spectroscopic data and experimental observations including (i) the necessity of water for methanol extraction and (ii) the effect of Si/Al ratio on the catalyst activity. Monocopper species have not yet been suggested as an active site for the partial methane oxidation reaction, and our results suggest that [CuIIOH]+ active site may provide complementary routes for methane activation in zeolites in addition to the known [Cu–O–Cu]2+ and Cu3O3 motifs.

Development of an ideal methane activation catalyst presents a trade-off between stability and reactivity of the active site that can be achieved by tuning the transition metal cation, active site motif and the zeolite topology.

In this study, we explore the effect of light nonmetal dopants (e.g., boron, carbon, and nitrogen) on the catalytic properties of transition-metal surfaces using the recently discovered boron-doped palladium catalyst for formic acid decomposition as an example. We use periodic density functional theory (DFT) calculations to derive an understanding of how subsurface boron modifies the palladium catalyst to be more active, and we find that the effect of the boron modification of palladium is different depending on the class of an adsorbate. Our DFT calculation results are also coupled to the microkinetic model of formic acid decomposition published previously to show that the catalytic properties of boron-doped palladium can be analyzed within the same conceptual framework used for understanding the catalytic trends of (undoped) transition-metal and alloy catalysts.Transition-metal catalysts form one of the backbones of the chemical industry, 1 and it is clear that the search for renewable energy solutions will heavily depend upon their employments. The performance of a transition-metal catalyst is often boosted via the addition of a promoter 2−4 or by alloying with another element. 5−9 The promoter (or the second element of an alloy) often accounts for a minor part of the catalytic system, only slightly modifying the energetics of the reaction intermediates via shifting of the d-band center 10,11 or electrostatic interactions. 5 Another means of altering the catalytic properties of transition-metal surfaces is achieved via the incorporation of relatively small atoms, such as hydrogen, 12−14 boron, 15−20 and carbon, 21 into lattices of the metals. For example, Pd has been shown to exhibit increased catalytic selectivity for acetylene hydrogenation upon incorporation of carbon into its subsurface. 21 The boron doping of Co catalysts for the Fischer− Tropsch synthesis has also been shown to suppress the deactivation of the catalysts efficiently. 18 Recently, a borondoped Pd catalyst has been shown to produce H 2 from formic acid at a high rate, 19 a finding that is valuable for H 2 storage solutions.Formic acid, having gravimetric and volumetric H 2 capacities of 4.4 wt % and 53.4 g/L, respectively, can become a suitable H 2 storage material if we can find catalysts that can selectively decompose formic acid to H 2 and CO 2 (instead of H 2 O and CO) under mild conditions. 22,23 Previously, we have used density functional theory (DFT) calculations coupled with the development of scaling relations 24,25 and a microkinetic model in order to identify what is needed for a catalyst material to be extremely active and selective for formic acid dehydrogenation. 26 This study led to the so-called volcano plots where the catalytic activities and selectivities of transition-metal surfaces are mapped out as functions of two independent descriptors, the CO* and OH* binding energies.In this study, we present a theoretical insight into how subsurface boron modifies the Pd surface to gear it toward an active and selective catalyst f...

Infrared spectroscopic study of neutral water clusters is crucial to understanding of the hydrogen-bonding networks in liquid water and ice. Here we report infrared spectra of size-selected neutral water clusters, (H2O)n(n= 3−6), in the OH stretching vibration region, based on threshold photoionization using a tunable vacuum ultraviolet free-electron laser. Distinct OH stretch vibrational fundamentals observed in the 3,500−3,600-cm−1region of (H2O)5provide unique spectral signatures for the formation of a noncyclic pentamer, which coexists with the global-minimum cyclic structure previously identified in the gas phase. The main features of infrared spectra of the pentamer and hexamer, (H2O)n(n= 5 and 6), span the entire OH stretching band of liquid water, suggesting that they start to exhibit the richness and diversity of hydrogen-bonding networks in bulk water.

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Lithium hydride (LiH) has a strong effect on iron leading to an approximately 3 orders of magnitude increase in catalytic ammonia synthesis. The existence of lithium-iron ternary hydride species at the surface/interface of the catalyst were identified and characterized for the first time by gas-phase optical spectroscopy coupled with mass spectrometry and quantum chemical calculations. The ternary hydride species may serve as centers that readily activate and hydrogenate dinitrogen, forming Fe-(NH )-Li and LiNH moieties-possibly through a redox reaction of dinitrogen and hydridic hydrogen (LiH) that is mediated by iron-showing distinct differences from ammonia formation mediated by conventional iron or ruthenium-based catalysts. Hydrogen-associated activation and conversion of dinitrogen are discussed.

Surgical instrument detection in robot-assisted surgery videos is an import vision component for these systems. Most of the current deep learning methods focus on single-tool detection and suffer from low detection speed. To address this, the authors propose a novel frameby-frame detection method using a cascading convolutional neural network (CNN) which consists of two different CNNs for real-time multi-tool detection. An hourglass network and a modified visual geometry group (VGG) network are applied to jointly predict the localisation. The former CNN outputs detection heatmaps representing the location of tool tip areas, and the latter performs bounding-box regression for tool tip areas on these heatmaps stacked with input RGB image frames. The authors' method is tested on the publicly available EndoVis Challenge dataset and the ATLAS Dione dataset. The experimental results show that their method achieves better performance than mainstream detection methods in terms of detection accuracy and speed.

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