In this study, we employ molecular statics to construct the structure of amorphous zinc oxide. First, we find out the first number of higher energy structures in all local stable structures by Basin-Hopping algorithm, which are separated into different ratio of crystalline/amorphous zinc oxide structures, and then we judge the type of zinc oxide structure by radial distribution function. In addition, we use coordination number to analyse the interatomic bond length and bond angle in the structures. Furthermore, we employ molecular dynamics to increase the temperature of amorphous zinc oxide structures, and then use the distribution of coordination number, bond length and bond angle between zinc and oxygen atom to analyse the change of the local structure of amorphous zinc oxide during the heating process.

Stainless steels are very important engineering materials in a variety of applications such as in the food industry and nuclear power plants due to their combination of good mechanical properties and high corrosion resistance. However, ferrite-containing stainless steels are sensitive to the so-called ‘475°C embrittlement’, which is induced by phase separation of the ferrite phase, where it decomposes into Fe-rich ferrite (α) and Cr-rich ferrite (α'). The phase separation is accompanied with a severe loss of toughness. Therefore, the upper service temperature of ferrite-containing stainless steels in industrial applications has been limited to around 250°. In the present work, Fe-Cr based steels were mainly investigated by atom probe tomography. A new method based on the radial distribution function (RDF) was proposed to quantitatively evaluate both the wavelength and amplitude of phase separation in Fe-Cr alloys from the atom probe tomography data. Moreover, a simplified equation was derived to calculate the amplitude of phase separation. The wavelength and amplitude was compared with evaluations using the auto-correlation function (ACF) and Langer-Bar-on-Miller (LBM) method, respectively. The results show that the commonly used LBM method underestimates the amplitude of phase separation and the wavelengths obtained by RDF shows a good exponential relation with aging time which is expected from the theory. The RDF is also an effective method in detecting the phenomena of clustering and elemental partitioning. Furthermore, atom probe tomography and the developed quantitative analysis method have been applied to investigate the influence of different factors on the phase separation in Fe-Cr based alloys by the help of mainly mechanical property tests and atom probe tomography analysis. The study shows that: (1) the external tensile stress during aging enhances the phase separation in ferrite. (2) Phase separation in weld bead metals decomposes more rapidly than both the heat-affected-zone metals and the base metals mainly due to the high density of dislocations in the welding bead metals which could facilitate the diffusion. (3) The results show that Ni and Mn can enhance the phase separation comparing to the binary Fe-Cr alloy whereas Cu forms clusters during aging. (4) Initial clustering of Cr atoms was found after homogenization. Two factors, namely, clustering of Cr above the miscibility gap and clustering during quenching was suggested as the two responsible mechanisms. (5) The homogenization temperatures significantly influence the evolution of phase separation in Fe-46.5at.%Cr. / <p>QC 20140910</p> / Spinodal Project

No description available.

Duplex stainless steels (DSSs) are important engineering materials due to their combination of good mechanical properties and corrosion resistance. However, as a consequence of their ferrite content, DSSs are sensitive to the so-called ‘475°C embrittlement’, which is induced by phase separation, namely, the ferrite decomposed into Fe-rich ferrite (α) and Cr-rich ferrite (α'), respectively. The phase separation is accompanied with a severe loss of toughness. Thus, the ‘475°C embrittlement’ phenomenon limits DSSs’ upper service temperature to around 250°C. In the present work, Fe-Cr binary model alloys and commercial DSSs from weldments were investigated for the study of phase separation in ferrite. Different techniques were employed to study the phase separation in model alloys and commercial DSSs, including atom probe tomography, transmission electron microscopy and micro-hardness test. Three different model alloys, Fe-25Cr, Fe-30Cr and Fe-35Cr (wt. %) were analyzed by atom probe tomography after different aging times. A new method based on radial distribution function was developed to evaluate the wavelength and amplitude of phase separation in these Fe-Cr binary alloys. The results were compared with the wavelengths obtained from 1D auto-correlation function and amplitudes from Langer-Bar-On-Miller method. It was found that the wavelengths from 1D auto-correlation function cannot reflect the 3D nano-scaled structures as accurate as those obtained by radial distribution function. Furthermore, the Langer-Bar-On-Miller method underestimates the amplitudes of phase separation. Commercial DSSs of SAF2205, 2304, 2507 and 25.10.4L were employed to investigate the connections between phase separation and mechanical properties from different microstructures (base metal, heat-affected-zone and welding bead) in welding. Moreover, the effect of external tensile stress during aging on phase separation of ferrite was also investigated. It was found that atom probe tomography is very useful for the analysis of phase separation in ferrite and the radial distribution function (RDF) is an effective method to compare the extent of phase separation at the very early stages. RDF is even more sensitive than frequency diagrams. In addition, the results indicate that the mechanical properties are highly connected with the phase separation in ferrite and other phenomena, such as Ni-Mn-Si-Cu clusters, that can also deteriorate the mechanical properties. / <p>QC 20130308</p>

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Die fortwährende Verkleinerung der Strukturbreiten in der Mikroelektronik erfordert es, herkömmliche SiO2 Dielektrika durch Materialien mit kleinerer Dielektrizitätskonstante zu ersetzen. Dafür sind verschiedene „low-k Materialien“ entwickelt worden. Unter diesen sind die Organosilikatgläser, die aus SiO2 Netzwerken mit eingelagerten Methylgruppen bestehen wegen ihrer ausgezeichneten Eigenschaften besonders interessant als Dielektrika zwischen metallischen Leiterbahnen. In dieser Arbeit sind fünf verschiedene dieser „low-k Materialien“ untersucht worden: ein dichtes und vier poröse Materialien, die alle durch plasmagestützte chemische Gasphasenabscheidung hergestellt wurden. Die strukturellen, chemischen und dielektrischen Eigenschaften der Materialien wurden mit Hilfe der analytischen Durchstrahlungselektronenmikroskopie unter Verwendung eines abbildenden GATAN-Energiespektrometers untersucht. Die Bestimmung der radialen Verteilungsfunktion (RDF) zur Charakterisierung der atomaren Nahordnung ermöglicht uns die Ermittlung mittlerer Bindungslängen und – winkel sowie der mikroskopischen Dichte des Materials. Gegenüber SiO2 wurden in den untersuchten „low-k Materialien“ stark veränderte mittlere Si-O, O-O und Si-Si Bindungslängen gefunden. Dieses wirkt sich natürlich auch auf die mittleren Si-O-Si bzw. O-Si-O Bindungswinkel aus, und wie erwartet war auch die mikroskopische Dichte der „low-k Materialien“ kleiner als die Dichte des SiO2. Elektronen Energieverlustspektroskopie (EELS) und Photoelektronenspektroskopie (XPS) wurden zur Charakterisierung der chemischen Umgebung der Atome in den „low-k Materialien“ herangezogen. Die Energien von Ionisationskanten und die Bindungsenergien der Silizium-2p und Sauerstoff-1s Elektronen waren in den „low-k Materialien“ größer als im SiO2. Die Kohlenstoffatome kamen in den „low-k Materialien“ sowohl sp2 als auch sp3 hybridisiert vor. sp2-Hybridisierung liegt vor, wenn Bindungen wie Si=CH2 und C=C im Netzwerk vorkommen, während sp3 Hybridisierung z.B. dann vorkommt, wenn freie Si-Bindungen durch –CH3 Gruppen abgesättigt werden. Die Anteile an sp2- bzw. sp3-hybridisierten Kohlenstoffatome wurden aus der Feinstruktur der K-Energieverlustkanten des Kohlenstoffs abgeschätzt. Das ergab, daß die meisten Kohlenstoffatome in den „low-k Materialien“ sp2-hybridisiert sind. Die dielektrischen Eigenschaften wurden durch Kramers-Kronig-Transformation einer Energieverlustfunktion ermittelt, die aus dem Niedrigverlust-EELS-Spektrum im Bereich der Plasmonenanregungen gewonnen wurde. Die Bandlücke des SiO2 beträgt ungefähr 9 eV während dichte „low-k Materialien“ aufgrund der Unregelmäßigkeiten in ihrem SiO2-Netzwerk zusätzliche Zustandsdichten innerhalb der Bandlücke aufweisen. Die Erzeugung von Poren im „low-k Material“ vermindert offenbar die Zustandsdichte im Bereich der Bandlücke und erweitert diese im Vergleich zum SiO2. Eine Modellrechnung mit der Dichtefunktionaltheorie für ein Strukturmodell, das den „low-k Materialien“ nahe kommt, ist zum Vergleich mit der experimentell gefundenen kombinierten Zustandsdichte herangezogen worden und zeigt eine gute Übereinstimmung. Die im Standard-Herstellungsprozeß vorkommenden Verfahren des Plasmaätzens und der Plasmaveraschung können die Struktur des „low-k Materials“ z.B. an den Seitenwänden von Ätzgräben verändern. Die gestörten Bereiche wurden mit der energiegefilterten Elektronenmikroskopie untersucht. Dabei wurde gefunden, daß sich die Strukturveränderungen der Seitenwände bis zu einer Tiefe in der Größenordnung von ungefähr 10 Nanometern erstrecken. Diese Bereiche sind verarmt an Kohlenstoff und ähneln folglich mehr einem SiO2-Dielektrikum. Die Kohlenstoffverarmung erstreckt sich in die „low-k Schicht“ in Form eines gaussartigen Profils mit maximaler Kohlenstoffkonzentration in der Mitte der Schicht. Die Sauerstoffkonzentration und die mikroskopische Dichte steigen in der Nähe der Seitenwände.

An in-depth knowledge of the structure formation process and the resulting dependency of the morphology on the reaction mechanism is a key requirement in order to design application-oriented materials. For twin polymerization, the basic idea of the reaction process is established, and important structural properties of the final nanoporous hybrid materials are known. However, the effects of changing the reaction mechanism parameters on the final morphology is still an open issue. In this work, the dependence of the morphology on the reaction mechanism is investigated based on a previously introduced lattice-based Monte Carlo method, the reactive bond fluctuation model. We analyze the effects of the model parameters, such as movability, attraction, or reaction probabilities on structural properties, like the specific surface area, the radial distribution function, the local porosity distribution, or the total fraction of percolating elements. From these examinations, we can identify key factors to adapt structural properties to fulfill desired requirements for possible applications. Hereby, we point out which implications theses parameter changes have on the underlying chemical structure.

Solubility prediction usually refers to prediction of the intrinsic aqueous solubility, which is the concentration of an unionised molecule in a saturated aqueous solution at thermodynamic equilibrium at a given temperature. Solubility is determined by structural and energetic components emanating from solid-phase structure and packing interactions, solute–solvent interactions, and structural reorganisation in solution. An overview of the most commonly used methods for solubility prediction is given in Chapter 1. In this thesis, we investigate various approaches to solubility prediction and solvation model development, based on informatics and incorporation of empirical and experimental data. These are of a knowledge-based nature, and specifically incorporate information from the Cambridge Structural Database (CSD). A common problem for solubility prediction is the computational cost associated with accurate models. This issue is usually addressed by use of machine learning and regression models, such as the General Solubility Equation (GSE). These types of models are investigated and discussed in Chapter 3, where we evaluate the reliability of the GSE for a set of structures covering a large area of chemical space. We find that molecular descriptors relating to specific atom or functional group counts in the solute molecule almost always appear in improved regression models. In accordance with the findings of Chapter 3, in Chapter 4 we investigate whether radial distribution functions (RDFs) calculated for atoms (defined according to their immediate chemical environment) with water from organic hydrate crystal structures may give a good indication of interactions applicable to the solution phase, and justify this by comparison of our own RDFs to neutron diffraction data for water and ice. We then apply our RDFs to the theory of the Reference Interaction Site Model (RISM) in Chapter 5, and produce novel models for the calculation of Hydration Free Energies (HFEs).

No description available.