Ultrathin covalent organic framework (COF) nanosheets are very appealing 2D materials, but the mass production of ultrathin COF nanosheets remains a great challenge. Here, by using cage‐like bicyclocalix[2]arene[2]triazines tri‐aldehyde (BCTAL) as the building block, 2D COF Cage‐COF‐1 was estimated to have a very weak interaction between adjacent layers (around 1/50 compared to that of graphite). As a result, 1.2 nm thick trilayer COF nanosheets were facilely exfoliated from the pristine COFs with large lateral size and high thickness homogeneity. The Cage‐COF‐1 nanosheet is featured by imine linkage, but it is catalytic inactive in oxygen evolution reaction (OER). After post‐metalation with Co2+ under ambient conditions, remarkable catalysis activity and stability was observed for Cage‐COF‐1‐Ns/Co, which has lower overpotential (330 mV) and Tafel slope (56 mV/dec) in catalytic OER compared to many other Co catalysts. This work has confirmed that weakening the interlaminar interaction is an effective strategy for the production of ultra‐thin COFs nanosheets. Due to the fully exposed and accessible imine linkage, catalysis active metal site can be controllably produced via post‐synthesis from nanosheets under very mild conditions.
Atomically dispersed metal catalysts have high metal atom utilization and catalytic activity. However, the rational design and scalable synthesis of such catalysts, especially with high metal content, remains a big...
to optimize the sensor arrays which are used to classify and identify these fluids. It preliminarily screens the response performance of single sensors in the testing system using the intra-class mean square, the F value and the P value by one-way analysis of variance (one-way ANOVA) method, and then performs significance analysis of the screened sensors according to the multiple comparison analysis method, classify them by significance and then group them into three different sensor arrays. After that, this paper performs principal component analysis and cluster analysis on the signals of each sensor array, and the results show that the optimized sensor arrays all have better performance than the ones before optimization in classification and identification of samples, and that in particular, the optimized array I consisting of Au, Pt, Pd and W has the best performance and can be applied in the classification and identification of abalone flavoring liquids.
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