Structure fusion based on graph convolutional networks for semi-supervised classification

Suffering from the multi-view data diversity and complexity for semi-supervised classification, most of existing graph convolutional networks focus on the networks architecture construction or the salient graph structure preservation, and ignore the the complete graph structure for semi-supervised classification contribution. To mine the more complete distribution structure from multi-view data with the consideration of the specificity and the commonality, we propose structure fusion based on graph convolutional networks (SF-GCN) for improving the performance of semi-supervised classification. SF-GCN can not only retain the special characteristic of each view data by spectral embedding, but also capture the common style of multi-view data by distance metric between multi-graph structures. Suppose the linear relationship between multi-graph structures, we can construct the optimization function of structure fusion model by balancing the specificity loss and the commonality loss. By solving this function, we can simultaneously obtain the fusion spectral embedding from the multi-view data and the fusion structure as adjacent matrix to input graph convolutional networks for semi-supervised classification. Experiments demonstrate that the performance of SF-GCN outperforms that of the state of the arts on three challenging datasets, which are Cora,Citeseer and Pubmed in citation networks

Oxygen-vacancy-mediated Negative Differential Resistance in La and Mg co-substituted BiFeO3 Thin Film

The conductive characteristics of Bi0.9La0.1Fe0.96Mg0.04O3(BLFM) thin film are investigated at various temperatures and a negative differential resistance (NDR) is observed in the thin film, where a leakage current peak occurs upon application of a downward electric field above 80 oC. The origin of the NDR behavior is shown to be related to the ionic defect of oxygen vacancies (VO..) present in the film. On the basis of analyzing the leakage mechanism and surface potential behavior, the NDR behavior can be understood by considering the competition between the polarized distribution and neutralization of VO..

Exemplification of catalyst design for microwave selective heating and its application to efficient in situ catalyst synthesis

The use of dielectric spectroscopy to develop an underpinning understanding of the molecular transformations involved in achieving the successful, rapid in situ synthesis of a catalytic chain transfer polymerisation (CCTP) catalyst using microwave heating is reported. The hypothesis behind the molecular design of this catalyst, such that it was tailored towards the application of microwave heating (MWH), is discussed, reviewed relative to the empirically results and compared to the performance of a benchmark preformed catalyst. The overall number/type of function group present in the catalyst, the degree of flexibility exhibited by its organic ligand system and level of solvation achieved are shown to be key factors affecting the interaction between the catalyst and the applied microwave energy. Use of microwave heating leads to fast, in situ formation of the catalyst (less than 30 second) within the polymerisation mixture, rendering prepreparation steps unnecessary and ensuring it is generated prior to the polymerisation reaction commencing. The data also suggests catalysts’ synthesis is achieved at levels of microwave power as low as 5 Watts, further adding to the efficiency and sustainability of the method and presents a potentially enormous opportunity to intensify current industrial processes

Ring opening polymerisation of ɛ-caprolactone using microwave electric and magnetic heating

The work presented in this thesis aims to highlight the differences in heating methods, which are conventional, microwave electric, and microwave magnetic heating, for the ring opening polymerisation of ɛ-caprolactone, as well as the development of an alternative catalyst that is specifically used in microwave magnetic heating to replace the current benchmark catalyst. Chapter 1 introduces the background of this thesis. There is also an overview of various types of biodegradable polymers, polymerisation techniques, and catalysts used in the polymerisation. An introduction into the basics of microwave and microwave electric and magnetic heating is also provided in this chapter. Chapter 2 goes on to explain the analytical techniques that are used to characterise the polymer and the dielectric properties. Procedures in locating the reaction vessel at the microwave electric and magnetic dominant positions in the microwave reactor are described. Experimental procedures that are used throughout this thesis are also explained. Chapter 3 investigates the dielectric properties of various types of metal complexes in both solid powder form and when dissolved in a solvent, to study the factors that affect the interaction between these complexes and the microwave electromagnetic field. Then further investigation into a series of heating experiments of solutions containing these complexes is carried out, to see if the empirical observations follow the same trend as predicted from the dielectric property results. Chapter 4 explores the first application of microwave magnetic heating to the ring opening polymerisation of ɛ-caprolactone catalysed by metal halides, and compares this to the conventional and microwave electric heating, and investigates the effects of different heating methods have on the overall polymerisation. This chapter also investigates various metal halides that experienced different response to the microwave electric and magnetic heating to see how this affects the polymerisation process. Chapter 5 describes the development of novel organometllic catalysts that can be used in the ring opening polymerisation of ɛ-caprolactone with the application of microwave magnetic heating, and possibly replace the existing benchmark catalyst Sn(Oct)2. The use of various heating methods is also investigated to see what effects they have on the overall process