溶剂对膨润土微纳米化的影响研究

以粒径分布、SEM和XRD分析为主要表征方法,从片层疏离程度和团聚体颗粒大小这两个方面综合评价水、异丙醇和二甲苯等6种溶剂对膨润土微纳米化的影响。实验表明,质量分数对水相膨润土的粒度分布影响显著,膨润土质量分数从5%下降到0.5%时,其最大粒径分布从4310nm快速下降到712nm,但即使质量分数低至0.1%,膨润土仍难以达到单片层的理想分布。不同溶剂对膨润土分散作用差别较大,水分散的膨润土颗粒结构致密,片层间隙不明显;乙醇、二甲苯、丙酮以及异丙醇分散的膨润土颗粒粒径均一,分别集中在380 nm、390nm、530nm和650 nm,且颗粒片层边缘剥离,片层间距明显,颗粒疏松;小角度XRD分析也进一步证明乙醇和异丙醇对膨润土有一定的插层作用。乙醇、二甲苯、丙酮及异丙醇对膨润土会产生明显的微纳米化效应。     

A novel SVM ensemble approach using clustering analysis

A novel Support Vector Machine （SVM） ensemble approach using clustering analysis is proposed. Firstly, the positive and negative training examples are clustered through subtractive clustering algorithm respectively. Then some representative examples are chosen from each of them to construct SVM components. At last, the outputs of the individual classifiers are fused through majority voting method to obtain the final decision. Comparisons of performance between the proposed method and other popular ensemble approaches, such as Bagging, Adaboost and k-fold cross validation, are carried out on synthetic and UCI datasets. The experimental results show that our method has higher classification accuracy since the example distribution information is considered during ensemble through clustering analysis. It further indicates that our method needs a much smaller size of training subsets than Bagging and Adaboost to obtain satisfactory classification accuracy.