Polymer electrolyte membrane fuel cells (PEMFCs) running on hydrogen are attractive alternative power supplies for a range of applications, with in situ release of the required hydrogen from a stable liquid offering one way of ensuring its safe storage and transportation before use. The use of methanol is particularly interesting in this regard, because it is inexpensive and can reform itself with water to release hydrogen with a high gravimetric density of 18.8 per cent by weight. But traditional reforming of methanol steam operates at relatively high temperatures (200-350 degrees Celsius), so the focus for vehicle and portable PEMFC applications has been on aqueous-phase reforming of methanol (APRM). This method requires less energy, and the simpler and more compact device design allows direct integration into PEMFC stacks. There remains, however, the need for an efficient APRM catalyst. Here we report that platinum (Pt) atomically dispersed on α-molybdenum carbide (α-MoC) enables low-temperature (150-190 degrees Celsius), base-free hydrogen production through APRM, with an average turnover frequency reaching 18,046 moles of hydrogen per mole of platinum per hour. We attribute this exceptional hydrogen production-which far exceeds that of previously reported low-temperature APRM catalysts-to the outstanding ability of α-MoC to induce water dissociation, and to the fact that platinum and α-MoC act in synergy to activate methanol and then to reform it.

The water-gas shift (WGS) reaction (where carbon monoxide plus water yields dihydrogen and carbon dioxide) is an essential process for hydrogen generation and carbon monoxide removal in various energy-related chemical operations. This equilibrium-limited reaction is favored at a low working temperature. Potential application in fuel cells also requires a WGS catalyst to be highly active, stable, and energy-efficient and to match the working temperature of on-site hydrogen generation and consumption units. We synthesized layered gold (Au) clusters on a molybdenum carbide (α-MoC) substrate to create an interfacial catalyst system for the ultralow-temperature WGS reaction. Water was activated over α-MoC at 303 kelvin, whereas carbon monoxide adsorbed on adjacent Au sites was apt to react with surface hydroxyl groups formed from water splitting, leading to a high WGS activity at low temperatures.

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The LHCb experiment has been taking data at the Large Hadron Collider (LHC) at CERN since the end of 2009. One of its key detector components is the Ring-Imaging Cherenkov (RICH) system. This provides charged particle identification over a wide momentum range, from 2–100 GeV/c. The operation and control, software, and online monitoring of the RICH system are described. The particle identification performance is presented, as measured using data from the LHC. Excellent separation of hadronic particle types (π, K, p) is achieved.

Distributionally robust stochastic optimization (DRSO) is an approach to optimization under uncertainty in which, instead of assuming that there is an underlying probability distribution that is known exactly, one hedges against a chosen set of distributions. In this paper we first point out that the set of distributions should be chosen to be appropriate for the application at hand, and that some of the choices that have been popular until recently are, for many applications, not good choices. We consider sets of distributions that are within a chosen Wasserstein distance from a nominal distribution, for example an empirical distribution resulting from available data. The paper argues that such a choice of sets has two advantages: (1) The resulting distributions hedged against are more reasonable than those resulting from other popular choices of sets. (2) The problem of determining the worst-case expectation over the resulting set of distributions has desirable tractability properties. We derive a dual reformulation of the corresponding DRSO problem and construct approximate worst-case distributions (or an exact worst-case distribution if it exists) explicitly via the first-order optimality conditions of the dual problem. Our contributions are five-fold. (i) We identify necessary and sufficient conditions for the existence of a worst-case distribution, which are naturally related to the growth rate of the objective function. (ii) We show that the worst-case distributions resulting from an appropriate Wasserstein distance have a concise structure and a clear interpretation. (iii) Using this structure, we show that data-driven DRSO problems can be approximated to any accuracy by robust optimization problems, and thereby many DRSO problems become tractable by using tools from robust optimization. (iv) To the best of our knowledge, our proof of strong duality is the first constructive proof for DRSO problems, and we show that the constructive proof technique is also useful in other contexts. (v) Our strong duality result holds in a very general setting, and we show that it can be applied to infinite dimensional process control problems and worst-case value-at-risk analysis.

Zn- and Na-modulated Fe catalysts were fabricated by a simple coprecipitation/washing method. Zn greatly changed the size of iron species, serving as the structural promoter, while the existence of Na on the surface of the Fe catalyst alters the electronic structure, making the catalyst very active for CO activation. Most importantly, the electronic structure of the catalyst surface suppresses the hydrogenation of double bonds and promotes desorption of products, which renders the catalyst unexpectedly reactive toward alkenes-especially C5+ alkenes (with more than 50% selectivity in hydrocarbons)-while lowering the selectivity for undesired products. This study enriches C1 chemistry and the design of highly selective new catalysts for high-value chemicals.

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Demonstrated here is the correlation between atomic configuration induced electronic density of single‐atom Co active sites and oxygen reduction reaction (ORR) performance by combining density‐functional theory (DFT) calculations and electrochemical analysis. Guided by DFT calculations, a MOF‐derived Co single‐atom catalyst with the optimal Co1‐N3PS active moiety incorporated in a hollow carbon polyhedron (Co1‐N3PS/HC) was designed and synthesized. Co1‐N3PS/HC exhibits outstanding alkaline ORR activity with a half‐wave potential of 0.920 V and superior ORR kinetics with record‐level kinetic current density and an ultralow Tafel slope of 31 mV dec−1, exceeding that of Pt/C and almost all non‐precious ORR electrocatalysts. In acidic media the ORR kinetics of Co1‐N3PS/HC still surpasses that of Pt/C. This work offers atomic‐level insight into the relationship between electronic density of the active site and catalytic properties, promoting rational design of efficient catalysts.