Non-Platinum Group Metal Electrocatalysts toward Efficient Hydrogen Oxidation Reaction

Developing non-platinum group metal (non-PGM) electrocatalysts for the hydrogen oxidation reaction (HOR) represents the efforts towards the more economical use of hydrogen fuel cells and hydrogen energy, which has attracted tremendous attention recently. However, non-PGM electrocatalysts for the HOR are still in their early development stages as compared with the significant advances in those for the oxygen reduction reaction and hydrogen evolution reaction. Herein, this paper summarizes the recent progresses and highlights the key challenges for the rational design of non-PGM electrocatalysts, aiming to promote the development of non-PGM HOR electrocatalysts. Fundamental understandings of the HOR mechanism are firstly reviewed, where theoretical interpretations on the low HOR kinetics in alkaline media, including the hydrogen binding energy theory, the bifunctional mechanism, and the water molecule reorganization, are particularly discussed. Subsequently, progresses of typical non-PGM HOR electrocatalysts in acid and alkaline media are summarized separately. For the HOR under alkaline conditions, the superiorities and challenges of Ni-based catalysts are discussed with a particular focus as they are the most promising non-PGM electrocatalysts. Finally, this paper highlights the challenges and provide perspectives on the future development directions of non-PGM HOR electrocatalysts.     

Integrating coral-like morphology into cyano-containing carbon nitride towards efficient photocatalytic H2 evolution and Cr(Ⅵ) reduction

The incomplete polymerization of graphite carbon nitride (g-C₃N₄) due to the kinetic problems resulted in its high recombination rate of photo-generated electron-hole pairs. Hence, cyano-containing carbon nitride with coral-like morphology (CCCN) was prepared by the molten salt method with heptazine-based melem as precursor, which presented excellent separation rate of photo-generated electron-hole pairs. SEM exhibited that CCCN owned coral-like morphology which exposed ample active sites and enhanced the capture ability of visible light while FT-IR and XPS demonstrated that cyano groups appearing in coral-like carbon nitride enhanced the separation rate of photo-induced charge carriers. The synergistic effect of coral-like morphology and cyano groups endowed CCCN-15% with superior performance of both the photocatalytic H₂ evolution (4207 μmol h^?1 g^?1) and Cr (Ⅵ) reduction (k = 0.059 min^?1), approximately 16.8 and 6.0 times that of g-C₃N₄, which was comparable among the similar materials. Density functional theory calculation (DFT) revealed that cyano groups decreased the bandgap and strengthened the activation degree of reaction substrate, which enhanced the thermodynamic driving force and the interaction between catalyst and substrate. This work provided a potential strategy for both the renewable energy generation and environmental restoration.     

南水北调中线总干渠藻类的生态调度

南水北调中线总干渠无在线调蓄水库,对藻类生态调度过程中出现的问题开展生态调度实现策略和实施方式研究。主要实现策略包括:划定自身的调蓄区,隔离生态调度对下游的影响;采用高效的渠池运行方式,减少生态调度时蓄量的反复调整;综合考虑安全、快速、平稳等需求,设定生态调度实施进程和方式。具体实施方式包括:将总干渠划分为流速调控区、调蓄区和正常运行区,分别实施等体积、控制蓄量和闸前常水位方式运行;将生态调度过程划分为充水阶段和泄水阶段,基于流速调控目标值、持续时长和水位降幅约束条件,确定各阶段时长和各分区的闸门群调控方案等。基于2018年3月输水工况,采用明渠一维非恒定流模型,仿真总干渠上游15个渠池的藻类生态调度过程。结果表明,生态调度可在3.5 d内完成,各渠池的平均流速由0.48 m/s增至0.93 m/s,持续时间超过2 h。在整个生态调度过程中,水位变化平稳,水位变幅符合安全阈值要求,下游渠道的正常运行未受生态调度明显影响。     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

Catalysts by pyrolysis: Direct observation of transformations during re-pyrolysis of transition metal-nitrogen-carbon materials leading to state-of-the-art platinum group metal-free electrocatalyst

Transition metal-nitrogen-carbon (M-N-C) materials have been the focus of scientists’ efforts to address the rising need for earth-abundant materials solutions for energy technology and decarbonization of the economy. They are viewed as one of the most promising candidates to replace platinum group metal (PGM) catalysts in the fuel cell and energy conversion fields, including the application of oxygen reduction reaction, carbon dioxide reduction reaction, and nitrogen reduction reaction. In the effort to improve M-N-C materials properties and achieve atomic dispersity of the transition metal in the carbonaceous matrix, a re-pyrolysis process has been proposed. This secondary heat treatment process of already obtained primary pyrolysis-derived M-N-C materials has been widely reported to substantially improve the electrochemical performance and operational stability of the catalysts. Here, we report a systematic investigation of this process used on samples of templated M-N-C catalysts to obtain state-of-the-art catalysts via in situ heating X-ray photoelectron spectroscopy (XPS), scanning transmission electron microscopy (STEM), energy-dispersive X-ray spectroscopy (EDS), electron energy loss spectroscopy (EELS), X-ray diffraction (XRD), and X-ray computed tomography (CT) characterization methods. It is found that the re-pyrolysis of M-N-C materials could result in the partial amorphization of the carbonaceous substrate. It causes the rearrangement and transformation of multitudinous N moieties, leading to optimization of their morphological display and association with atomically dispersed transition metal dopants. Ultimately, the re-pyrolysis results in an increase in uniformity of the active Fe-N_x sites distribution without the formation of nano-crystalline phases (metallic or carbide) and with overall preservation of the morphology of the carbonaceous framework achieved during the first formative pyrolysis step of the templated synthesis. These observations provide confirmation that empirically established re-pyrolysis is recommended to be used on all M-N-C materials despite the different synthesis routes to obtain a practical advanced catalytic material.     

Graduate Student Literature Review: Considerations for nutritional grouping in dairy farms

Each cow in a group has different nutritional requirements even if the group is formed by cows of similar age, number of lactations, and lactation stage. Common dairy farm management setup does not support formulating a diet that accurately matches individual nutritional requirements for each cow; therefore, a proportion of cows in the group will be overfed and another proportion underfed. Overfeeding and underfeeding cows increases the risk of metabolic diseases, decreases milk production, and increases nutrient waste. Consequently, profitability of dairy farms and the environment are negatively affected. Nutritional grouping is a management strategy that aims to allocate lactating cows homogeneously according to their nutritional requirements. Groups of cows with more uniform nutritional requirements facilitates the formulation of more accurate diets for the group. Current availability of large data streams on dairy farms facilitates the design of algorithms to implement nutritional grouping. Our review summarizes important factors to consider when grouping cows, describes nutritional grouping approaches, and summarizes benefits of implementing nutritional grouping in dairy farms.     

基于多通道的ICU脑血管疾病死亡风险预测模型

死亡风险预测指根据病人临床体征监测数据来预测未来一段时间的死亡风险。对于ICU病患，通过死亡风险预测可以有针对性地对病人做出临床诊断，以及合理安排有限的医疗资源。基于临床使用的MEWS和Glasgow昏迷评分量表，针对ICU病人临床监测的17项生理参数，提出一种基于多通道的ICU脑血管疾病死亡风险预测模型。引入多通道概念应用于BiLSTM模型，用于突出每个生理参数对死亡风险预测的作用。采用Attention机制用于提高模型预测精度。实验数据来自MIMIC [Ⅲ]数据库，从中提取3?080位脑血管疾病患者的16?260条记录用于此次研究，除了六组超参数实验之外，将所提模型与LSTM、Multichannel-BiLSTM、逻辑回归（logistic regression）和支持向量机（support vector machine, SVM）四种模型进行了对比分析，准确率Accuracy、灵敏度Sensitive、特异性Specificity、AUC-ROC和AUC-PRC作为评价指标，实验结果表明，所提模型性能优于其他模型，AUC值达到94.3%。     

胶莱盆地南部大盛群、王氏群的划分与对比

胶莱盆地在胶东半岛地质构造及造山带研究中占有重要地位,其巨厚的白垩系陆相沉积是石油系统多年的研究目标。胶莱盆地南部白垩纪的岩石地层序列较其北部更为复杂,其认识几经反复,其中尤以大盛群与王氏群和莱阳群的部分单位的关系为甚。本次工作通过详细对比其沉积层序、相互关系、古生物组合、岩石学特征及同位素年龄等因素,认为大盛群与王氏群属同一沉积层序,沉积基底相同、沉积环境相似、古生物群落时代一致,二者具有同时代、同沉积相、同岩石组合的一致性,应是一套地层,建议今后使用统一地层名称。     

A Structure−Activity Relationship Study of Novel Hydroxamic Acid Inhibitors around the S1 Subsite of Human Aminopeptidase N

Aminopeptidase N (APN/CD13) is a zinc-dependent ubiquitous transmembrane ectoenzyme that is widely present in different types of cells. APN is one of the most extensively studied metalloaminopeptidases as an anti-cancer target due to its significant role in the regulation of metastasis and angiogenesis. Previously, we identified a potent and selective APN inhibitor, N-(2-(Hydroxyamino)-2-oxo-1-(3′,4′,5′-trifluoro-[1,1′-biphenyl]-4-yl)ethyl)-4-(methylsulfonamido)benzamide ( 3 ). Herein, we report the further modifications performed to explore SAR around the S1 subsite of APN and to improve the physicochemical properties. A series of hydroxamic acid analogues were synthesised, and the pharmacological activities were evaluated in vitro. N-(1-(3′-Fluoro-[1,1′-biphenyl]-4-yl)-2-(hydroxyamino)-2-oxoethyl)-4-(methylsulfonamido)benzamide ( 6 f ) was found to display an extremely potent inhibitory activity in the sub-nanomolar range.     

改进的CAGAN在虚拟试衣中的应用

针对CAGAN（Conditional Analogy GAN）换衣后效果模糊，在目标衣服与原始衣服长短不一致时效果一般，相对目标衣服保留过少的细节等问题做了相关研究并对CAGAN进行了改进，提出了新的虚拟试衣方式。经过改进的CAGAN生成一个粗糙的结果，由该结果得到目标衣服穿在模特身上改变形状后的mask，接下来利用mask对目标衣服进行变形，综合变形的衣服和第一步的结果便得到最终的试衣图像。实验结果表明，该方法解决了前面存在的问题，而且取得了非常好的效果。