Viscosity and glass transition in amorphous oxides

An overview is given of amorphous oxide materials viscosity and glass-liquid transition phenomena. The viscosity is a continuous function of temperature, whereas the glass-liquid transition is accompanied by explicit discontinuities in the derivative parameters such as the specific heat or thermal expansion coefficient. A compendium of viscosity models is given including recent data on viscous flow model based on network defects in which thermodynamic parameters of configurons—elementary excitations resulting from broken bonds—are found from viscosity-temperature relationships. Glass-liquid transition phenomena are described including the configuron model of glass transition which shows a reduction of Hausdorff dimension of bonds at glass-liquid transition

The shape of two-dimensional space

Genomics, so fashionable today, is only half of the secret of life. The other half of the secret is shape, form, morphogenesis and metamorphosis. The gene may prescribe what is synthesised, but the proteins appear and operate in a pre-existing environment which they then change. The first step towards life is the appearance of a micelle, a spherical membrane, a surface which separates the world into inside and outside. We are here concerned with surfaces, with a particular subset of two-dimensional manifolds embedded in three-dimensional Euclidean space, namely the non-self-intersecting, periodic minimal surfaces of cubic symmetry, which separate the world into two regions as an infinite plane would do, but with much more complex topologies. Like the Platonic solids , these cubic surfaces are geometrical absolutes and have distinctive topologies but entail no arbitrary parameters . The objective is to enumerate at least some of these surfaces, for probably an infinite number answer to this description, to draw attention to their geometry and to point to some of their applications and occurrences on various scales between mega-engineering and nano-technology. These objects are solutions looking for problems

Topologically disordered systems at the glass transition

The thermodynamic approach to the viscosity and fragility of amorphous oxides was used to determine the topological characteristics of the disordered network-forming systems. Instead of the disordered system of atoms we considered the congruent disordered system of interconnecting bonds. The Gibbs free energy of network-breaking defects (configurons) was found based on available viscosity data. Amorphous silica and germania were used as reference disordered systems for which we found an excellent agreement of calculated and measured glass transition temperatures. We reveal that the Hausdorff dimension of the system of bonds changes from Euclidian three-dimensional below to fractal 2.55 ± 0.05-dimensional geometry above the glass transition temperature

Molecular Dynamic Simulation of Structures and Interfaces in Amorphous/Ordered Composites.

This thesis describes molecular dynamics simulation studies of the structure-property relationships of molecular network systems, including inorganic and organic bulk amorphous systems, as well as two different amorphous polymers at the interface with ordered substrates. A series of soda lime silicate glasses were simulated, with up to 50% total modification and varying ratios of sodium and calcium. The clustering of cations and second-neighbor connectivity affect vibrational modes and the compressibility vs. pressure behavior. Mean-field theory is unable to account for mixed modifier effects in soda lime silicates. The structure and tensile behavior of a dynamically reacted bulk epoxy network were studied, demonstrating an improved polymerization method for continuously monitoring properties as a function of network growth, including volumetric shrinkage and internal stresses. A bifunctional epoxy resin is reacted with two aliphatic amines at room temperature, comparing simulation size, amine functionality, and stoichiometry. The elastic properties change by only 1-2 GPa during the growth of the network within the achieved degree of conversion. Tensile strength increases by ~100 MPa. Systems with surplus amine hardener reach higher degrees of epoxide conversion, but lag in formation of an infinite network. As a simple model system for amorphous/ordered interfaces, a thin alkane film was placed onto a metallic substrate. The ordered substrate creates a layered polymer configuration within the adjacent 10 Å, as shown by density profiles, pair correlation functions, and monomer orientation statistics. This structural change also affects the mechanical properties, as the elastic moduli of nanoconfined alkane systems are higher than would be expected for a simple laminate composite, based on extrapolating from the bulk properties of the two materials. Lastly, epoxy/carbon laminate systems were investigated, comparing different epoxy layer thicknesses and amine functionality. The cure and shrinkage behavior mimic the bulk epoxy, though the percolation of an infinite cluster is delayed. Post-annealed structures show a nearly uniform decrease in both the elastic modulus and tensile strength. Local heterogeneity is important in predicting nanoscale mechanics for all systems investigated. Larger system size provides better accuracy in determining mechanical properties of simulated highly cross-linked network polymers.PHDMaterials Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111417/1/kabeck_1.pd

Visual Analytics and Modeling of Materials Property Data

Due to significant advancements in experimental and computational techniques, materials data are abundant. To facilitate data-driven research, it calls for a system for managing and sharing data and supporting a set of tools for effective data analysis and modeling. Generally, a given material property M can be considered as a multivariate data problem. The dimensions of M are the values of the property itself, the conditions (pressure P, temperature T, and multi-component composition X) that control the concerned property, and relevant metadata I (source, date). Here we present a comprehensive database considering both experimental and computational sources and an innovative visual analytics system for melt viscosity (η), which can be represented by M (η, P, T, X1, X2, …, I1, I2, …). We implemented the parallel coordinates plot (PCP) method by introducing new non-standard features, such as derived axes/sub-axes, dimension merging, binary scaling, and nested plots. Thus enhanced PCP offers many insights of relevance to underlying physics, data modeling, and guiding future experiments/computations. The construction of viscosity models is a non-trivial process, and extant models are often limited to a sub-parameter space, such as the ambient pressure conditions. To develop a generalized model which applies to wider parameter space, we trained various machine learning models, including neural network, Decision Tree, Random Forest, and XGBoost. We evaluated model performance based on loss function, error distribution, and model continuity. Our results show that neural network models outperformed the physics-based models as well as all tree-based models. A small neural network with two hidden layers, each containing 64 nodes, was found to be sufficient to model both the ambient pressure and complete dataset. Despite a marginal decrease in RMSE, a larger neural network consisting of four hidden layers with 128 nodes in each layer could provide an even better fit for the complete dataset in terms of model continuity and error distribution. Tree-based models could follow the training data, but the model results show high variations with small changes in parameter space, making them less applicable for continuous numerical data. Our data visualization and modeling approach is expected to be useful to researchers who explore and model material data, for instance, the density property can be incorporated as a new attribute in our system