Photocatalysis provides a route to convert methane into an energy-dense, liquid fuel, such as methanol, using only natural gas, sunlight, water (or oxygen), and the catalyst. In this report, we compare the photocatalytic activity and selectivity for bismuth vanadate (BiVO4) microcrystals with different morphologies to partially oxidize methane to methanol. Bipyramidal BiVO4 microcrystals comprising {102} and {012} surface facets were found to be both more active and more selective for methane to methanol conversion compared to platelet microcrystals that expose {001} facets as their top and bottom surface. The selectivity of the bipyramidal BiVO4 microcrystals for methanol production was over 85% for reaction times between 60 and 120 min with mass activity between 112 and 134 μmol h–1 g–1 during this period. These activities are among the highest reported for photocatalytic methane to methanol conversion using illumination conditions comparable to solar irradiation and without the need for sacrificial reagents. Photochemical deposition of metal salts indicates that photoexcited electrons and holes react selectivity at different facets of the platelet and bipyramidal BiVO4 microcrystals. Combining the photodeposition results with surface energy calculations, we propose that the high selectivity for methanol observed using bipyramidal BiVO4 microcrystals arises due to efficient extraction of photoexcited holes from surfaces that have intermediate reactivity for oxidation.

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This paper analyzes the communication between Kubernetes nodes and pods in Google Kubernetes Engine (GKE). Weexplore the structure and features of GKE networking, including communication between nodes, nodes, and pods, andpods themselves. We also consider the network security and performance aspects. In addition, we analyze commonnetworking issues such as latency, packet loss, and network failures and provide solutions. Through our experimentalresults, we demonstrate the effectiveness of our proposed solutions and offer insights for future research in this area.This paper provides valuable insights for developers and operators who use GKE and want to optimize their networkingconfiguration.

Container networking is a critical component of cloud computing, providing the infrastructure for the deployment andscaling of containerized applications. However, ensuring high-performance and reliable container networking can bechallenging due to the complexity of container network architectures and associated metrics. This paper proposes a newapproach to optimize container CNI (Container Network Interface) metrics to improve service level indicators (SLIs)and objectives (SLOs) in container networking. The approach involves analyzing key CNI metrics, such as networklatency, bandwidth, and packet loss, and fine-tuning them to optimize network performance and availability. This studyconducted experiments on Kubernetes clusters to validate the approach using different CNI plugins and workloads. Theresults show that optimizing CNI metrics can significantly improve network performance, reduce network downtime,and enhance the overall service level of container networking. The proposed approach provides a practical and effectivesolution for managing container network performance and availability and has the potential to benefit a wide range ofcloud-based applications.

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