We report the synthesis and characterization of a fan-shaped chiral nanographene 1,which is composed of 6 hexabenzocoronene subunits with 216 conjugated carbon atoms.In the dehydrocyclization reaction,38 C–C bonds ar...We report the synthesis and characterization of a fan-shaped chiral nanographene 1,which is composed of 6 hexabenzocoronene subunits with 216 conjugated carbon atoms.In the dehydrocyclization reaction,38 C–C bonds are formed simultaneously.1 exhibits strong panchromatic absorption from the ultraviolet to the near-infrared,with an absorption coefficient of 209,000 L mol^(-1)cm^(-1)at 564 nm.Optically pure samples,obtained via chiral HPLC,show distinct ECD signals(|Δε|=704 L mol^(-1)cm^(-1)at 405 nm).Upon excitation,1 emits near-infrared fluorescence at 820 nm with a quantum yield of 5.5%.These photophysical properties of 1 were analyzed with the assistance of DFT calculations.展开更多
We describe a janusarene derivative PyJ,which forms micrometer-scale one-dimensional metallo-supramolecular polymer through coordination driven self-assembly.PyJ is a well-preorganized dodecatopic pyridyl ligand built...We describe a janusarene derivative PyJ,which forms micrometer-scale one-dimensional metallo-supramolecular polymer through coordination driven self-assembly.PyJ is a well-preorganized dodecatopic pyridyl ligand built on a hexaphenylbenzene platform.The two-face structural feature of PyJ allows for a delicate control over multiple Py-Ag^(+)-Py coordination interactions,leading to assembled structure of PyJ-Ag^(+),which was characterized by dynamic light scattering,atomic force microscopy,and transmission electron microscopy.展开更多
The power equipment defect text is important data generated by the operation and maintenance of the power grid system.It is characterized by having many professional words from the power field and high complexity.Duri...The power equipment defect text is important data generated by the operation and maintenance of the power grid system.It is characterized by having many professional words from the power field and high complexity.During model training,there are some problems,such as difficulty in semantic understanding,gradient disappearance,negative information loss,and data imbalance,which hurt the text quality and defect analysis effect.To deal with these issues,this paper proposes a ULF-BI-LSTM text quality improvement algorithm integrating UCNN,LeakyRelu activation function,and Focal Loss function.Then,we correctly separate professional vocabulary,delete invalid vocabulary,and normalize the object description by text data preprocessing.Finally,we fill in missed data and correct the wrong data using the ULF-BI-LSTM algorithm.Experimental results show three improvement strategies that effectively improve the accuracy,precision,F1,and recall of the algorithm.The proposed algorithm outperforms the mainstream algorithm TextCNN,SVM,and BI-LSTM,which alleviates the above problems.展开更多
基金supported by the National Natural Science Foundation of China(Nos.21871298,91956118)。
文摘We report the synthesis and characterization of a fan-shaped chiral nanographene 1,which is composed of 6 hexabenzocoronene subunits with 216 conjugated carbon atoms.In the dehydrocyclization reaction,38 C–C bonds are formed simultaneously.1 exhibits strong panchromatic absorption from the ultraviolet to the near-infrared,with an absorption coefficient of 209,000 L mol^(-1)cm^(-1)at 564 nm.Optically pure samples,obtained via chiral HPLC,show distinct ECD signals(|Δε|=704 L mol^(-1)cm^(-1)at 405 nm).Upon excitation,1 emits near-infrared fluorescence at 820 nm with a quantum yield of 5.5%.These photophysical properties of 1 were analyzed with the assistance of DFT calculations.
基金supported by the National Natural Science Foundation of China(Nos.21871298,91956118)the Sun Yat-sen University。
文摘We describe a janusarene derivative PyJ,which forms micrometer-scale one-dimensional metallo-supramolecular polymer through coordination driven self-assembly.PyJ is a well-preorganized dodecatopic pyridyl ligand built on a hexaphenylbenzene platform.The two-face structural feature of PyJ allows for a delicate control over multiple Py-Ag^(+)-Py coordination interactions,leading to assembled structure of PyJ-Ag^(+),which was characterized by dynamic light scattering,atomic force microscopy,and transmission electron microscopy.
基金supported in part by the National Natural Science Foundation of China(No.52177110)。
文摘The power equipment defect text is important data generated by the operation and maintenance of the power grid system.It is characterized by having many professional words from the power field and high complexity.During model training,there are some problems,such as difficulty in semantic understanding,gradient disappearance,negative information loss,and data imbalance,which hurt the text quality and defect analysis effect.To deal with these issues,this paper proposes a ULF-BI-LSTM text quality improvement algorithm integrating UCNN,LeakyRelu activation function,and Focal Loss function.Then,we correctly separate professional vocabulary,delete invalid vocabulary,and normalize the object description by text data preprocessing.Finally,we fill in missed data and correct the wrong data using the ULF-BI-LSTM algorithm.Experimental results show three improvement strategies that effectively improve the accuracy,precision,F1,and recall of the algorithm.The proposed algorithm outperforms the mainstream algorithm TextCNN,SVM,and BI-LSTM,which alleviates the above problems.
