Dyeing behavior and mechanism of Crocein Orange G on carboxymethyl cotton fabric

Cellulose - Traditional cotton fiber dyeing requires an abundance of salt, which leads to environmental pollution. Consequently, decreasing or eliminating the use of salt has become the primary...     

基于快速热释放功能的相变偶氮苯/织物复合材料

针对偶氮基光敏分子存在放热速率慢和温度难以控制的难点,在分子结构设计基础上,采用氧化偶合法制备了具有固-液相变功能的4,4′-对-二正己基偶氮苯(AZO-L6).由于分子间作用力较低,偶氮苯分子呈现低熔、快异构化的特点,在发生反-顺异构化转变时大幅降低分子的熔点.固-液相变过程实现了光热能和相变焓的存储,在结构回复时同时放出储存的能量(231.8 kJ/kg),并将相变偶氮苯应用于可穿戴聚合物复合织物中.结果显示储能后的相变偶氮苯分子在蓝光(440 nm)刺激下在60 s内可将材料温度提升0.8℃,获得了具有自加热功能的可穿戴复合织物,为探索多功能自保温可穿戴装置提供了研究思路.     

Organocatalytic asymmetric [3 + 3] annulation of isatin N,N'-cyclic azomethine imines with enals: Efficient approach to functionalized spiro N-heterocyclic oxindoles

An unprecedented chiral secondary amine-catalyzed [3 + 3] annulation of isatin N,N'-cyclic azomethine imines with α,β-unsaturated aldehydes was developed. This strategy allowed the construction of structurally novel spiro N-heterocyclic oxindole derivatives in good yields (up to 91%) and good to excellent enantioselectivities (up to >99% ee), albeit with modest diastereoselectivities (up to 3.1:1 dr).     

Year Discrimination of Mild Aroma Chinese Liquors Using Three-Dimensional Fluorescence Spectroscopy Combined with Parallel Factor and Neural NetworkSCIEI北大核心CSCD

Three-dimensional fluorescence spectroscopy coupled with parallel factor analysis and neural network was applied to the year discrimination of mild aroma Chinese liquors. The excitation-emission fluorescence matrices (EEMs) of 120 samples with various years were measured by FLS920 fluorescence spectrometer. The trilinear decomposition of the data array was performed and the loading scores of and the excitation-emission profiles of four components were also obtained. The scores were employed as the inputs of the BP neural networks and the PARAFAC-BP identification model was constructed. 10 samples were collected from 10, 20 and 30 years of liquors respectively, and 30 samples were selected as the test sets. The remaining 90 samples were used as the training sets to build the training model. The year prediction of unknown samples was also carried out, and the prediction accuracy was 90%, 100% and 100%, respectively. Meanwhile, the discrimination analysis method and the multi way partial least squares discriminant analysis were compared, namely PARAFAC-BP and NPLS-DA. The results indicated that parallel factor combined with the neural network (PARAFAC-BP) has higher prediction accuracy. The proposed method can effectively extract the spectral characteristics, and also reduce the dimension of the input variables of neural network. A good year discrimination result was finally achieved.