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The electrochemical CO 2 or CO reduction to chemicals and fuels using renewable energy is a promising way to reduce anthropogenic carbon emissions. The gas diffusion electrode (GDE) design enables low-carbon manufacturing of target products at a current density (e.g., 500 mA cm −2 ) relevant to industrial requirements. However, the long-term stability of the GDE is restricted by poor water management and flooding, resulting in a significant hydrogen evolution reaction (HER) within almost an hour. The optimization of water management in the GDE demands a thorough understanding of the role of the gas diffusion layer (GDL) and the catalyst layer (CL) distinctively. Herein, the hydrophobicity of the GDL and CL is independently adjusted to investigate their influence on gas transport efficiency and water management. The gas transport efficiency is more enhanced with the increase in hydrophobicity of the GDL than the CL. Direct visualization of water distribution by optical microscope and micro-computed tomography demonstrates that the water flow pattern transfers from the stable displacement to capillary fingering as GDL hydrophobicity increases. Unfortunately, only increasing the hydrophobicity is not sufficient to prevent flooding. A revolutionary change in the design of the GDE structure is essential to maintain the long-term stabilitymore »of CO 2 /CO reduction.« less

Industrial Internet of Things (IIoT) systems aim to interconnect a large number of heterogeneous industrial sensing and actuation devices through both wired and wireless communication technologies and further connect them to the Internet to achieve ubiquitous sensing, computing and control services [1]. As a representative IIoT technology, 6TiSCH [2] targets at gluing together the 802.15.4e data link layer (offering industrial performance in terms of timing, reliability and power consumption) and an IP-enabled upper layer stack to achieve both deterministic network performance and seamless integration with Internet services. In recent years, 6TiSCH has been receiving increasing attentions from both industry and academia. We have witnessed its wide deployment in many industrial domains, including advanced manufacturing, industrial process control, smart grids, and healthcare.

The past decade has witnessed the rapid development of real-time wireless technologies and their wide adoption in various industrial Internet-of-Things (IIoT) applications. Among those wireless technologies, 6TiSCH is a promising candidate as the de facto standard due to its nice feature of gluing a real-time link-layer standard (802.15.4e, for offering deterministic communication performance) together with an IP-enabled upper-layer stack (for seamlessly supporting Internet services). 6TiSCH's built-in random slot selection scheduling algorithm, however, often leads to large and unbounded transmission latency, thus can hardly meet the real-time requirements of IIoT applications. This paper proposes an adaptive partition based scheduling framework, APaS, for 6TiSCH networks. APaS introduces the concept of resource partitioning into 6TiSCH network management. Instead of allocating network resources to individual devices, APaS partitions and assigns network resources to different groups of devices based on their layers in the network so as to guarantee that the transmission latency of any end-toend flow is within one slotframe length. APaS also employs a novel online partition adjustment method to further improve its adaptability to dynamic network topology changes. The effectiveness of APaS is validated through both simulation and testbed experiments on a 122-node multi-hop 6TiSCH network.

Here we report that in situ reconstructed Cu two-dimensional (2D) defects in CuO nanowires during CO 2 RR lead to significantly enhanced activity and selectivity of C 2 H 4 compared to the CuO nanoplatelets. Specifically, the CuO nanowires achieve high faradaic efficiency of 62% for C 2 H 4 and a partial current density of 324 mA cm −2 yet at a low potential of −0.56 V versus a reversible hydrogen electrode. Structural evolution characterization and in situ Raman spectra reveal that the high yield of C 2 H 4 on CuO nanowires is attributed to the in situ reduction of CuO to Cu followed by structural reconstruction to form 2D defects, e.g. , stacking faults and twin boundaries, which improve the CO production rate and *CO adsorption strength. This finding may provide a paradigm for the rational design of nanostructured catalysts for efficient CO 2 electroreduction to C 2 H 4 .

Regulating the selectivity toward a target hydrocarbon product is still the focus of CO2 electroreduction. Here, we discover that the original surface Cu species in Cu gas-diffusion electrodes plays a more important role than the surface roughness, local pH, and facet in governing the selectivity toward C1 or C2 hydrocarbons. The selectivity toward C2H4 progressively increases, while CH4 decreases steadily upon lowering the Cu oxidation species fraction. At a relatively low electrodeposition voltage of 1.5 V, the Cu gas-diffusion electrode with the highest Cuδ+/Cu0 ratio favors the pathways of hydrogenation to form CH4 with maximum Faradaic efficiency of 65.4% and partial current density of 228 mA cm−2 at −0.83 V vs RHE. At 2.0 V, the Cu gas-diffusion electrode with the lowest Cuδ+/Cu0 ratio prefers C–C coupling to form C2+ products with Faradaic efficiency topping 80.1% at −0.75 V vs RHE, where the Faradaic efficiency of C2H4 accounts for 46.4% and the partial current density of C2H4 achieves 279 mA cm−2. This work demonstrates that the selectivity from CH4 to C2H4 is switchable by tuning surface Cu species composition of Cu gas-diffusion electrodes.