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| 1 | Black titanium dioxide nanomaterials for photocatalytic removal of pollutants:A review显示文摘Semiconductor photocatalysis is one of the most widely used environment-friendly technologies for removing various contaminants.As a well-developed photocatalyst,titanium dioxide(TiO_(2))still has limits in its wide bandgap and rapid recombination rate of photogenerated charge carriers.Recently,black TiO_(2)appears as a strong candidate in the improvement of sunlight harvesting,because of its excellent absorption capacity and utilization of solar radiation.Despite extensive applications in both environmental and energy fields,the use of black TiO_(2)as a photocatalyst in pollutant removal is ambiguous.The primary objective of the review is to comprehensively evaluate the applications of black TiO_(2)in photocatalytic removal of contaminants,including conventional organic contaminants,emerging contaminants,microbes,and heavy metals.The basic properties,photocatalytic mechanism,and synthesis of black TiO_(2)have been summarized and analyzed.Moreover,the stability and recoverability of black TiO_(2)have also been discussed.Finally,the perspectives of the application of black TiO_(2)in pollutant removal have been further discussed. | Ying Liang Guohe Huang Xiaying Xin Yao Yao Yongping Li Jianan Yin Xiang Li Yuwei Wu Sichen Gao | 2022 | Journal of Materials Science & Technology2022，，17： | 1 |
| 2 | Active Anomaly Detection Technology Based on Ensemble Learning显示文摘Anomaly detection is an important problem in various research and application fields.Researchers design reliable schemes to provide solutions for effectively detecting anomaly points.Most of the existing anomaly detection schemes are unsupervised methods,such as anomaly detection methods based on density,distance and clustering.In total,unsupervised anomaly detection methods have many limitations.For example,they cannot be well combined with prior knowledge in some anomaly detection tasks.For some nonlinear anomaly detection tasks,the modeling is complex and faces dimensional disasters,which are greatly affected by noise.Sometimes it is difficult to find abnormal events that users are interested in,and users need to customize model parameters before detection.With the wide application of deep learning technology,it has a good modeling ability to solve linear and nonlinear data relationships,but the application of deep learning technology in the field of anomaly detection has many challenges.If we regard exceptions as a supervised problem,exceptions are a few,and we usually face the problem of too few labels.To obtain a model that performs well in the anomaly detection task,it requires a high initial training set.Therefore,to solve the above problems,this paper proposes a supervised learning method with manual participation.We introduce the integrated learning model and train a supervised anomaly detection model with strong stability and high accuracy through active learning technology.In addition,this paper adopts certain strategies to maximize the accuracy of anomaly detection and minimize the cost of manual labeling.In the experimental link,we will show that our method is better than some traditional anomaly detection algorithms. | Weiwei Liu Shuya Lei Liangying Peng Jun Feng Sichen Pan Meng Gao | 2022 | 国际计算机前沿大会会议论文集2022，，1： | 0 |
| 3 | Solvent Effects on Kinetics and Electrochemical Performances of Rechargeable Aluminum Batteries显示文摘The rechargeable aluminum batteries(RAB)have shown great potential for energy storage applications due to their low-cost and superior volumetric capacity.However,the battery performances are far from satisfactory owing to the poor kinetics of electrode reactions,including the solid-state ionic diffusion and interfacial charge transfer.The charge transfer reaction,typically the cation desolvation at the interface(Helmholtz plane),is crucial for determining the interfacial charge transfer,which induces the solvent effect in batteries but has not been explored in RABs.Herein,we provide a comprehensive understanding of solvent effects on interface kinetics and electrochemical performance of RAB by analyzing the desolvation process and charge transfer energy barrier.The pivotal role of solvent effects is confirmed by the successful application of Al(OTF)_(3)-H_(2)O electrolyte,which displays easy desolvation,low charge transfer resistance,and thus superior Al-ion storage performance over other electrolytes in our studies.In addition,based on the strong correlation between the calculated desolvation energy and charge transfer energy barrier,the calculation of dissociation energy of ion-solvent complex is demonstrated as an efficient index for designing electrolytes.The in-depth understanding of solvent effects provides rational guidance for new electrolyte and RAB design. | Sichen Gu Yang Haoyi Yanxia Yuan Yaning Gao Na Zhu Feng Wu Ying Bai Chuan Wu | 2022 | Energy Material Advances2022，，1： | 0 |
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