A novel C3N4-CDot composite photocatalyst was very recently shown to be highly efficient and very stable in water splitting by solar radiation without using any sacrificial reagent (J. Liu, et al., Science, 2015, 347(6225), 970). This photocatalyst utilizes a two-electron/two-step process in which the production of H2O2 and H2 is photocatalyzed by using C3N4 in the first step and H2O2 is decomposed by using CDots in the second step. The present work is a study on the generality of this approach by application of a C3N4/MnO2 catalyst. This new catalyst indeed splits water by a two step process in a stable way, without any sacrificial agent. It was however found that though the absorbance of the new catalyst in the visible range of 500-600 nm is much larger than that of the C3N4-CDot catalyst, its water splitting efficiency is much lower. These findings add insight into and assist in the further optimization of this new class of photocatalysts to meet the requirements of commercial water splitting systems.

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With the huge growth of the Internet of Things (IoT) in manufacturing, agricultural and numerous other applications, connectivity solutions have become increasingly important especially for those covering wide remote area in the scale of kilometre squares. Although many low-power widearea network (LPWAN) technologies such as Long Range (LoRa) are supposed to support long-range low-power wireless communication, the underneath star topology limits the scalability of the networks due to the need of a central hub. To provide connectivity to a wider area, the authors propose to build the mesh topology upon these LPWAN technologies. One of the challenges of meshing these networks is the routing mechanism originally designed for star networks is not energy sensitive. In this letter, the authors address this issue by proposing a distributed as well as energy-efficient reinforcement learning (RL) based routing algorithm for the wide area wireless mesh IoT networks. They evaluate the failure rate, spectrum and power efficiencies of the proposed algorithm by simulations, which resemble the long-range IoT networks, by comparing it to that of a random routing with loop-detection algorithm and a centralised pre-programmed routing algorithm which represents the ideal-scenario. They also present a progressive study to demonstrate how the learning in the algorithm reduces the power consumption of the entire network.

1. Paeonol, the primary active component of a traditional Chinese medicine Moutan Cortex, has a wide range of pharmacological activities. In the present study, the metabolism of paeonol by cytochrome P450s (CYPs) was investigated in human liver microsomes. 2. One O-demethylated metabolite was detected in reaction catalysed by human liver microsomes, and was identified as resacetophenone by comparing the tandem mass spectra and the chromatographic retention time with that of the standard compound. 3. The study with a chemical selective inhibitor, cDNA-expressed human CYPs, a correlation assay, and a kinetics study demonstrated that CYP1A2 was the major isoform responsible for the paeonol O-demethylation in human liver microsomes.