In light of environmental concerns and energy transition, electrochemical CO 2 reduction (ECR) to value-added multicarbon (C 2+ ) fuels and chemicals, using renewable electricity, presents an elegant long-term solution to close the carbon cycle with added economic benefits as well. However, electrocatalytic C─C coupling in aqueous electrolytes is still an open challenge due to low selectivity, activity, and stability. Design of catalysts and reactors holds the key to addressing those challenges. We summarize recent progress in how to achieve efficient C─C coupling via ECR, with emphasis on strategies in electrocatalysts and electrocatalytic electrode/reactor design, and their corresponding mechanisms. In addition, current bottlenecks and future opportunities for C 2+ product generation is discussed. We aim to provide a detailed review of the state-of-the-art C─C coupling strategies to the community for further development and inspiration in both fundamental understanding and technological applications.

Single‐crystalline nanowires of Fe3O4 hydrothermally synthesized under a magnetic field are reported. The square and hexagonal crystals formed in zero applied field are shown to give way to nanowires as the magnetic field is increased. The Figure shows the situation for a 0.25 T field. The structure and magnetic properties are characterized by transmission electron microscopy, X‐ray and electron diffraction, and magnetometry.

In recent years Dynamic Time Warping (DTW) has emerged as the distance measure of choice for virtually all time series data mining applications. For example, virtually all applications that process data from wearable devices use DTW as a core sub-routine. This is the result of significant progress in improving DTW’s efficiency, together with multiple empirical studies showing that DTW-based classifiers at least equal (and generally surpass) the accuracy of all their rivals across dozens of datasets. Thus far, most of the research has considered only the one-dimensional case, with practitioners generalizing to the multi-dimensional case in one of two ways, dependent or independent warping. In general, it appears the community believes either that the two ways are equivalent, or that the choice is irrelevant. In this work, we show that this is not the case. The two most commonly used multi-dimensional DTW methods can produce different classifications, and neither one dominates over the other. This seems to suggest that one should learn the best method for a particular application. However, we will show that this is not necessary; a simple, principled rule can be used on a case-by-case basis to predict which of the two methods we should trust at the time of classification. Our method allows us to ensure that classification results are at least as accurate as the better of the two rival methods, and, in many cases, our method is significantly more accurate. We demonstrate our ideas with the most extensive set of multi-dimensional time series classification experiments ever attempted.

Accelerated ageing of Ni-Yttria Stabilized Zirconia (YSZ) anode functional layers (AFLs) in solid oxide fuel cells (SOFCs) is carried out at 1000-1200°C, the resulting morphological changes are investigated using transmission X-ray microscopy (TXM), and properties are characterized using electrochemical impedance spectroscopy (EIS). Prior to ageing, the as prepared NiO-YSZ AFLs are reduced to Ni-YSZ and then aged at 1100°C for 100 h in order to eliminate early-stage morphological changes. Measured particle size and three phase boundary (TPB) density changes with ageing time and temperature are fit reasonably well using a power-law coarsening model. This model is also used in conjunction with an electrochemical model to predict changes in the anode charge-transfer polarization resistance.

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