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京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第21574号 / 理博第4481号 / 新制||理||1643(附属図書館) / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)教授 嶺重 慎, 教授 太田 耕司, 准教授 栗田 光樹夫 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

Objects can be said to be structured when their representation also contains their parts. While OWL in general can describe structured objects, description graphs are a recent, decidable extension to OWL which support the description of classes of structured objects whose parts are related in complex ways. Classes of chemical entities such as molecules, ions and groups (parts of molecules) are often characterised by the way in which the constituent atoms of their instances are connected via chemical bonds. For chemoinformatics tools and applications, this internal structure is represented using chemical graphs. We here present a chemical knowledge base based on the standard chemical graph model using description graphs, OWL and rules. We include in our ontology chemical classes, groups, and molecules, together with their structures encoded as description graphs. We show how role-safe rules can be used to determine parthood between groups and molecules based on the graph structures and to determine basic chemical properties. Finally, we investigate the scalability of the technology used through the development of an automatic utility to convert standard chemical graphs into description graphs, and converting a large number of diverse graphs obtained from a publicly available chemical database. / Computer Science (School of Computing) / M. Sc. (Computer Science)

A small-scale model of a CVD reactor was built. Axial and radial of major species concentrations and temperature profiles were obtained with a micro gas chromatograph and a fine thermocouple. Those temperature and species concentrations revealed detailed thermal and chemical structures of the CVD reactor. The concentrations of argon plus hydrogen, methane, and C2Hx (C2H2 + C2H4 + C2H6) resulting from xylene decomposition were measured along the CVD at different temperatures. Ferrocene was added to xylene to investigate the effect of a catalyst on composition profiles. The results with ferrocene indicated an increase in CH4 and C2Hx concentrations. At 1000 C and above, the increase of C2Hx concentration is higher than that for CH4. The effect of ferrocene was very minor on the concentration of the gases. Finally composition and temperature profiles were measured and plotted for the radial direction at X=75 cm and T=1200 C. The overall rate constant for the gas-phase reaction was calculated based on the measured species concentration data using the Benson and Shaw reaction mechanism. Our study showed that the Benson and Shaw mechanism could be used in the temperature range lower than 800 C. Also the effect of hydrogen in the syntheses of CNTs, in the CVD reactor using xylene and ferrocene, was studied. Both single-step and two-step methods were applied. In the single-step method, the ferrocene was dissolved in the xylene. In the two step-method the catalyst preparation step was performed first; ferrocene powder was placed in the preheater for a certain period of time and carried by a mixture of argon and hydrogen at fixed concentration to get catalyst nanoparticles deposited on the reactor wall. Xylene then was injected to the reactor. To study the effect of hydrogen, the synthesized materials were observed by SEM and TEM. The results showed that the presence of hydrogen is essential for CNTs to be synthesized by the CVD method, and also the concentration of hydrogen in the reactor has a great effect on the quality of CNTs. The yield of CNTs in the two-step method was slightly higher than that in the one-step method.

Objects can be said to be structured when their representation also contains their parts. While OWL in general can describe structured objects, description graphs are a recent, decidable extension to OWL which support the description of classes of structured objects whose parts are related in complex ways. Classes of chemical entities such as molecules, ions and groups (parts of molecules) are often characterised by the way in which the constituent atoms of their instances are connected via chemical bonds. For chemoinformatics tools and applications, this internal structure is represented using chemical graphs. We here present a chemical knowledge base based on the standard chemical graph model using description graphs, OWL and rules. We include in our ontology chemical classes, groups, and molecules, together with their structures encoded as description graphs. We show how role-safe rules can be used to determine parthood between groups and molecules based on the graph structures and to determine basic chemical properties. Finally, we investigate the scalability of the technology used through the development of an automatic utility to convert standard chemical graphs into description graphs, and converting a large number of diverse graphs obtained from a publicly available chemical database. / Computer Science (School of Computing) / M. Sc. (Computer Science)

Deciphering the activity of chemical molecules against a pathogenic organism is an essential task in drug discovery process. Virtual screening, in which few plausible molecules are selected from a large set for further processing using computational methods, has become an integral part and complements the expensive and time-consuming in vivo and in vitro experiments. To this end, it is essential to extract certain features from molecules which in the one hand are relevant to the biological activity under consideration, and on the other are suitable for designing fast and robust algorithms. The features/representations are derived either from physicochemical properties or their structures in numerical form and are known as descriptors. In this work we develop two new molecular-fragment descriptors based on the critical analysis of existing descriptors. This development is primarily guided by the notion of coding degeneracy, and the ordering induced by the descriptor on the fragments. One of these descriptors is derived based on the simple graph representation of the molecule, and attempts to encode topological feature or the connectivity pattern in a hierarchical way without discriminating atom or bond types. Second descriptor extends the first one by weighing the atoms (vertices) in consideration with the bonding pattern, valence state and type of the atom. Further, the usefulness of these indices is tested by ranking and classifying molecules in two previously studied large heterogeneous data sets with regard to their anti-tubercular and other bacterial activity. This is achieved by developing a scoring function based on clustering using these new descriptors. Clusters are obtained by ordering the descriptors of training set molecules, and identifying the regions which are (almost) exclusively coming from active/inactive molecules. To test the activity of a new molecule, overlap of its descriptors in those cluster (interpolation) is weighted. Our results are found to be superior compared to previous studies: we obtained better classification performance by using only structural information while previous studies used both structural features and some physicochemical parameters. This makes our model simple, more interpretable and less vulnerable to statistical problems like chance correlation and over fitting. With focus on predictive modeling, we have carried out rigorous statistical validation. New descriptors utilize primarily the topological information in a hierarchical way. This can have significant implications in the design of new bioactive molecules (inverse QSAR, combinatorial library design) which is plagued by combinatorial explosion due to use of large number of descriptors. While the combinatorial generation of molecules with desirable properties is still a problem to be satisfactorily solved, our model has potential to reduce the number of degrees of freedom, thereby reducing the complexity.

This thesis deals with the problem of searching of structures in large chemical compounds databases. The aim is to design and implement an efficient system that supports two basic types of search, which are identity and substructure search. This task is complicated not only by the large number of entries in databases but also by graph representation of chemical structures, for which many algorithms are hard to solve. The thesis will introduce concepts which will prove useful in solving these problems. A web service is also created as a part of the thesis in order to make the database searching available to the users.

Key words mathematical modelling, chemical principles, shape and structure of the molecules, visualisation of chemical structures, chemistry and mathematics interdisciplinarity Ivan, Matúš: Modelling students' conceptions on chemical principles using mathematics. (Ph.D. Thesis). Prague: Faculty of Science, Charles University, 2018. Abstract The primary aims of the dissertation project is identification of "contact areas" of subjects of chemistry and mathematics and creation of interventions to solve the problems of chosen areas. At first, it was necessary to analyse available literature by the authors from the field, that have mentioned the problematics of interdisciplinarity between mathematics and chemistry. A part of literature research was dedicated to a search for the expected outcomes in curricular documents in Czech Republic and in Slovak Republic. In Czech Republic these were Framework Educational Programmes (RVP ZV, 2017 a RVP G, 2007). In Slovak Republic thee documents are State Educational programme ISCED 2 - lower secondary education (2015) and State Educational programme ISCED 3A - upper secondary education (2015). After that the analysis of a sample of School educational programmes of chosen schools in Czech Republic was conducted. The sample was chosen through proportional stratified...