Phosphoric-Acid Retention in High-Temperature Proton-Exchange Membranes

Great efforts have been conducted to develop high temperature proton exchange membrane fuel cell (HT-PEMFC) due to its features of enhanced electrocatalyst reactivity, simplified hydrothermal management system and high CO tolerance of catalysts, and remarkable progress has been achieved. However, the easy leaching of phosphoric acid (PA) from the membranes during operation limits its commercial scale-up in complicated environments. This concept here mainly focuses on the recent developments for mitigation of PA loss in PEMs. The probable mechanisms of PA loss are proposed. The approaches to improve PA retention for example via introduction of phosphonic acid by covalent bond, using ion-pairs interaction and siphoning effect, and blending with inorganic nanoparticles are described in detail. Among these strategies, the siphoning effect from the intrinsic microporous PEMs is the most efficient and enables the cell to operate flexibly within a broad temperature range. Therefore, this concept may provide new ideas for the scientists to retain PA, to improve the cell performance and expand the potential applications of PA doped PEMs at elevated humidity and wide temperature range.     

基于快速神经网络架构搜索的鲁棒图像水印网络算法

为解决深度学习在图像水印算法中计算量大且模型冗余的问题，提高图像水印算法在抵抗噪声、旋转和剪裁等攻击时的鲁棒性，提出基于快速神经网络架构搜索（neural architecture search，NAS）的鲁棒图像水印网络算法。通过多项式分布学习快速神经网络架构搜索算法，在预设的搜索空间中搜索最优网络结构，进行图像水印的高效嵌入与鲁棒提取。首先，将子网络中线性连接的全卷积层设置为独立的神经单元结构，并参数化表示结构单元内节点的连接，预先设定结构单元内每个神经元操作的搜索空间；其次，在完成一个批次的数据集训练后，依据神经元操作中的被采样次数和平均损失函数值动态更新概率；最后，重新训练搜索完成的网络。水印网络模型的参数量较原始网络模型缩减了92%以上，大大缩短了模型训练时间。由于搜索得到的网络结构更为紧凑，本文算法具有较高的时间性能和较好的实验效果，在隐藏图像时，对空域信息的依赖比原始网络更少。对改进前后的2个网络进行了大量鲁棒性实验，对比发现，本文算法在CIFAR-10数据集上对抵抗椒盐噪声和旋转、移除像素行（列）等攻击优势显著；在ImageNet数据集上对抵抗椒盐高斯噪声、旋转、中值滤波、高斯滤波、JPEG压缩、裁剪等攻击优势显著，特别是对随机移除行（列）和椒盐噪声有较强的鲁棒性。     

微生物燃料电池阴极脱氮

微生物燃料电池(MFC)阴极电子受体的多样性可实现其阴极脱氮,从而将产生的电能合理利用,因此阴极脱氮成为了MFC的一个研究方向,同时也为实际废水中氮素的去除提供了新的可能。然而在反应过程中有众多因素会导致NOx-N与其他电子受体竞争阳极电子的现象,影响阴极反硝化过程对于电子的利用率,从而造成脱氮效率低等现实问题。目前已有许多研究通过优化MFC自身结构弥补产电的缺陷,及将与其他工艺系统耦合实现同步硝化反硝化等方法,取长补短以增加脱氮效率,降低对碳源的需求,以此解决微生物燃料电池阴极脱氮出现的问题。本文从MFC不同的脱氮历程、MFC工艺条件(pH、C/N、DO)、极室分隔材料等影响MFC阴极脱氮的因素及影响其阴极反硝化微生物群落构成等方面,进行了综述并预测未来研究方向。     

The application of metal-organic frameworks in electrocatalytic nitrogen reduction

In recent years, the research of nitrogen reduction reaction (NRR) under ambient conditions has attracted wide attention for their relatively low energy consumption, in which rational design of electrocatalysts is the key to achieve high-performance NRR. Metal-organic frameworks (MOFs), as a new kind of porous material, have been intensively studied in the past few decades owing to not only their structural versatility and tunability but also intrinsic porosity. Due to their structural features, MOFs also have potential applications in mild condition electrocatalysis of NRR. In this review, the recently experimental and theoretical studies of MOFs in NRR electrocatalysts are briefly summarized.