Doping Platinum with Germanium: An Effective Way to Mitigate the CO Poisoning

The vulnerability towards CO poisoning is a major drawback affecting the efficiency and long-term performance of platinum catalysts in fuel cells. In the present work, by a combination of density functional theory calculations and mass spectrometry experiments, we test and explain the promotional effect of Ge on Pt catalysts with higher resistance to deactivation via CO poisoning. A thorough exploration of the configurational space of gas-phase Pt_n⁺ and GePt_n−1⁺ (n=5–9) clusters using global minima search techniques and the subsequent electronic structure analysis reveals that germanium doping reduces the binding strength between Pt and CO by hindering the 2π-back-donation. Importantly, the clusters remain catalytically active towards H₂ dissociation. The ability of Ge to weaken the Pt−CO interaction was confirmed by mass spectrometry experiments. Ge can be a promising alloying agent to tune the selectivity and improve the durability of Pt particles, thus opening the way to novel catalytic alternatives for fuel cells.     

A Machine Learning Model for the Prognosis of Pulseless Electrical Activity during Out-of-Hospital Cardiac Arrest

Pulseless electrical activity (PEA) is characterized by the disassociation of the mechanical and electrical activity of the heart and appears as the initial rhythm in 20–30% of out-of-hospital cardiac arrest (OHCA) cases. Predicting whether a patient in PEA will convert to return of spontaneous circulation (ROSC) is important because different therapeutic strategies are needed depending on the type of PEA. The aim of this study was to develop a machine learning model to differentiate PEA with unfavorable (unPEA) and favorable (faPEA) evolution to ROSC. An OHCA dataset of 1921 5s PEA signal segments from defibrillator files was used, 703 faPEA segments from 107 patients with ROSC and 1218 unPEA segments from 153 patients with no ROSC. The solution consisted of a signal-processing stage of the ECG and the thoracic impedance (TI) and the extraction of the TI circulation component (ICC), which is associated with ventricular wall movement. Then, a set of 17 features was obtained from the ECG and ICC signals, and a random forest classifier was used to differentiate faPEA from unPEA. All models were trained and tested using patientwise and stratified 10-fold cross-validation partitions. The best model showed a median (interquartile range) area under the curve (AUC) of 85.7(9.8)% and a balance accuracy of 78.8(9.8)%, improving the previously available solutions at more than four points in the AUC and three points in balanced accuracy. It was demonstrated that the evolution of PEA can be predicted using the ECG and TI signals, opening the possibility of targeted PEA treatment in OHCA.     

Strain‐Enhanced Metallic Intermixing in Shape‐Controlled Multilayered Core–Shell Nanostructures: Toward Shaped Intermetallics

Controlling the surface composition of shaped bimetallic nanoparticles could offer precise tunability of geometric and electronic surface structure for new nanocatalysts. To achieve this goal, a platform for studying the intermixing process in a shaped nanoparticle was designed, using multilayered Pd‐Ni‐Pt core–shell nanocubes as precursors. Under mild conditions, the intermixing between Ni and Pt could be tuned by changing layer thickness and number, triggering intermixing while preserving nanoparticle shape. Intermixing of the two metals is monitored using transmission electron microscopy. The surface structure evolution is characterized using electrochemical methanol oxidation. DFT calculations suggest that the low‐temperature mixing is enhanced by shorter diffusion lengths and strain introduced by the layered structure. The platform and insights presented are an advance toward the realization of shape‐controlled multimetallic nanoparticles tailored to each potential application.     

A finite volume shock‐capturing solver of the fully coupled shallow water‐sediment equations

This paper describes a numerical solver of well‐balanced, 2D depth‐averaged shallow water‐sediment equations. The equations permit variable horizontal fluid density and are designed to model water‐sediment flow over a mobile bed. A Godunov‐type, Harten–Lax–van Leer contact (HLLC) finite volume scheme is used to solve the fully coupled system of hyperbolic conservation laws that describe flow hydrodynamics, suspended sediment transport, bedload transport and bed morphological change. Dependent variables are specially selected to handle the presence of the variable density property in the mathematical formulation. The model is verified against analytical and semi‐analytical solutions for bedload transport and suspended sediment transport, respectively. The well‐balanced property of the equations is verified for a variable‐density dam break flow over discontinuous bathymetry. Simulations of an idealised dam‐break flow over an erodible bed are in excellent agreement with previously published results, validating the ability of the model to capture the complex interaction between rapidly varying flow and an erodible bed and validating the eigenstructure of the system of variable‐density governing equations. Flow hydrodynamics and final bed topography of a laboratory‐based 2D partial dam breach over a mobile bed are satisfactorily reproduced by the numerical model. Comparison of the final bed topographies, computed for two distinct sediment transport methods, highlights the sensitivity of shallow water‐sediment models to the choice of closure relationships. Copyright © 2016 John Wiley & Sons, Ltd.     

Optimisation of focused ultrasound extraction (FUSE) and microwave-assisted extraction (MAE) of hydrocarbons in geological chert samples

The analysis of hydrocarbons in chert rocks provides a worthwhile source of information regarding the geochemical features of a depositional setting. Since the typical analytical procedure requires long Soxhlet extractions and the use of large quantities of sample (30-50 g), in this work we have optimised the focused ultrasound extraction (FUSE) and the microwave-assisted extraction (MAE) to make available a less severe procedure. In both cases a full experimental design including solvent mixture composition (Dichloromethane/Hexane/Acetone) and process variables (sonication time and cycles, and extraction temperature and time) by means of D-optimal designs. In the extracted fractions hydrocarbons (C₁₆-C₄₀) were analysed by gas-chromatography-mass spectrometry. In the case of FUSE the process variables were the most sensitive variables and the optimum conditions were defined at 60:40 DCM/Hex mixture and a sonication time of 30 min and 9 cycles. In the case of MAE all the variables shown a significant effect on the extraction yield and the most adequate conditions (60:30:10 DCM/Hex/Ace mixture and an irradiation time of 15 min at 110 °C) were established from the analysis of the response surface. Both methods were systematically applied with different chert samples collected in Cucho (Trebiño County, Burgos, Spain) and we were able to assure quantitative extractions (>85%) in the first extraction. Additionally, from the distribution patterns of n-alkanes obtained in the different chert samples (nodular chert, laminar chert and massive-brechoid chert) collected in Cucho, we were able to distinguish different origins and diagenetic history.     

29Si and 27Al MAS NMR assessment of the C-(A-) S–H nanomolecular structure of Ultra-High-Performance Concrete (UHPC) modified with pyrogenic oxides

Ultra-High Performance Concrete (UHPC) that contains pyrogenic oxides (Pox) and has been heat-cured with microwave energy reaches as high as 420 MPa after 1 day. The influence of microwave curing on the strength gain is much more pronounced in UHPC than in normal concrete. ²⁹Si and ²⁷Al MAS NMR nanomolecular structure investigation of Ultra-High-Performance Concrete (UHPC) modified with nanoscale pozzolans (pyrogenic oxides) reveals significant differences from other concrete types that may explain such high early strength. There is an increase in polymerization degree of C-(A) S–H (C–S–H containing Al) phase of the UHPC modified with pyrogenic oxides, followed by a trend of substitution of silicon atoms on the Q? sites of C–S–H (calcium-silicate-hydrates) through aluminum atoms. The mean chain length (MCL) and degree of connectivity (Dc) are the highest for pyrogenic oxides containing UHPC that have been cured with microwave energy. The increase of polymerization degree is more pronounced for alumina-based pyrogenic oxide containing UHPC.