Water in Sugar Electrolytes and Application to Electrodeposition of Superconducting Rhenium

A systematic electrochemical study is carried out on electrolytes with superhigh concentrations of fructose. The effect of fructose concentration on the viscosity and conductivity of electrolyte are determined and analyzed using Walden rule and the theory of rate process. The diffusion rates of proton and cupric cation are calculated from the peak current in cyclic voltammogram on stationary electrode and the limiting current on rotating electrodes. Raman spectroscopy is used to characterize the hydrogen bond network in water and the effect of fructose concentration on such network. Rhenium deposition with different fructose concentrations is studied on rotating disc electrodes. X-ray fluorescence, X-ray diffraction, and four point probe measurements at cryogenic temperature are used to study the deposition rate, crystallographic structure, and superconductivity of film, respectively.

On the Chemical Heterogeneity of Austenite in Maraging Steel

The change of Ni-, Cr-, Cu- contents in maraging steel composition occurring on heating in the subcritical and intercritical interval has been studied by the X-ray spectral microanalysis. Heating in the temperature range from 490 to 550C has resulted in increasing of Ni- Cu- concentrations in the 1iquation austenite when the latter is present in the steel structure as a consequence of several reasons (the large ingot, low level of forging reduction ratio, etc.). The significant enrichment of surface layers of austenite inclusions may probably occur if there are great differences between interphase and intraphase diffusion rates. By varying the thermal treatment and thus the Ni-diffusion in austenite it is possible to create austenite layers with different Ni-contents within a grain or massive martensite and it is also possible to control the material properties.

Content-based user classifier to uncover information exchange in disaster-motivated networks

Disasters strike communities around the world, with a reduced time-frame for warning and action leaving behind high rates of damage, mortality, and years in rebuilding efforts. For the past decade, social media has indicated a positive role in communicating before, during, and after disasters. One important question that remained un-investigated is that whether social media efficiently connect affected individuals to disaster relief agencies, and if not, how AI models can use historical data from previous disasters to facilitate information exchange between the two groups. In this study, the BERT model is first fine-tuned using historical data and then it is used to classify the tweets associated with hurricanes Dorian and Harvey based on the type of information provided; and alongside, the network between users is constructed based on the retweets and replies on Twitter. Afterwards, some network metrics are used to measure the diffusion rate of each type of disaster-motivated information. The results show that the messages by disaster eyewitnesses get the least spread while the posts by governments and media have the highest diffusion rates through the network. Additionally, the “cautions and advice” messages get the most spread among other information types while “infrastructure and utilities” and “affected individuals” messages get the least diffusion even compared with “sympathy and support”. The analysis suggests that facilitating the propagation of information provided by affected individuals, using AI models, will be a valuable strategy to pursue in order to accelerate communication between affected individuals and survival groups during the disaster and aftermath.

Kinetic Monte Carlo (KMC) Algorithm for Nanocrystals

<p>This thesis uses the kinetic Monte Carlo (KMC) algorithm to examine the growth morphology and structure of nanocrystals. Crystal growth in a supersaturated gas of atoms and in an undercooled binary melt is investigated. First, in the gas phase, the interplay of the deposition and surface diffusion rates is studied. Then, the KMC algorithm is refined by including solidification events and finally, by adding diffusion in the surrounding liquid. A new algorithm is developed for modelling solidification from an undercooled melt. This algorithm combines the KMC method, which models the change in shape of the crystal during growth, with a macroscopic continuum method that tracks the diffusion of material through solution towards the crystal. For small length and time scales, this approach provides simple, effective front tracking with fully resolved atomistic detail of the crystal-melt interface. Anisotropy is included in the model as a surface diffusion process and the growth rate of the crystal is found to increase monotonically with increase in the surface anisotropy value. The method allows for the study of multiple crystal nuclei and Ostwald ripening. This method will aid researchers to explain why certain crystal shapes form under particular conditions during growth, and may enable nanotechnologists to design techniques for growing nanocrystals with specific shapes for a variety of applications, from catalysis to the medicine field and electronics industry. This will lead to a better understanding of the atomistic process of crystal growth at the nanoscale.</p>

Kinetic Monte Carlo (KMC) Algorithm for Nanocrystals

<p>This thesis uses the kinetic Monte Carlo (KMC) algorithm to examine the growth morphology and structure of nanocrystals. Crystal growth in a supersaturated gas of atoms and in an undercooled binary melt is investigated. First, in the gas phase, the interplay of the deposition and surface diffusion rates is studied. Then, the KMC algorithm is refined by including solidification events and finally, by adding diffusion in the surrounding liquid. A new algorithm is developed for modelling solidification from an undercooled melt. This algorithm combines the KMC method, which models the change in shape of the crystal during growth, with a macroscopic continuum method that tracks the diffusion of material through solution towards the crystal. For small length and time scales, this approach provides simple, effective front tracking with fully resolved atomistic detail of the crystal-melt interface. Anisotropy is included in the model as a surface diffusion process and the growth rate of the crystal is found to increase monotonically with increase in the surface anisotropy value. The method allows for the study of multiple crystal nuclei and Ostwald ripening. This method will aid researchers to explain why certain crystal shapes form under particular conditions during growth, and may enable nanotechnologists to design techniques for growing nanocrystals with specific shapes for a variety of applications, from catalysis to the medicine field and electronics industry. This will lead to a better understanding of the atomistic process of crystal growth at the nanoscale.</p>

Effect of Light Irradiation on the Diffusion Rate of the Charge Carrier Hopping Mechanism in P3HT–ZnO Nanoparticles Studied by μ+SR

Blended regio-regular P3HT–ZnO nanoparticles are a hybrid material developed as an active layer for hybrid solar cells. The study of the hopping mechanisms and diffusion rates of regio-regular P3HT–ZnO nanoparticles is significant for obtaining intrinsic charge transport properties that provide helpful information for preparing high-performance solar cells. The temperature dependences of the parallel and perpendicular diffusion rates in regio-regular P3HT–ZnO nanoparticles determined from muon spin relaxation measurements were investigated by applying various longitudinal fields. We investigated the effect of light irradiation on the diffusion rates in regio-regular P3HT–ZnO nanoparticles. We found that with increasing temperature, the parallel diffusion rate decreased, while the perpendicular diffusion rate increased. The ratio of the parallel to perpendicular diffusion rate (D‖/D⊥) can be used to indicate the dominant charge carrier hopping mechanism. Without light irradiation, perpendicular diffusion dominates the charge carrier hopping, starting at 25 K, with a ratio of 1.70×104, whereas with light irradiation, the perpendicular diffusion of the charge carrier starts to dominate at the temperature of 10 K, with a ratio of 2.40×104. It is indicated that the additional energy from light irradiation affects the diffusion, especially the charge diffusion in the perpendicular direction.

Methodology for Forecasting Revenues from the Sale of Innovative Products in the Domestic Tourism Market

This article presents a methodology for forecasting the expected sales of innovative tourism products in the domestic market. The principles of the product life cycle concept and consumer behavior theory are taken as starting points for calculating the sales volumes of an innovative product as well as the rate of its penetration into the market. A method of measuring the level of consumer commitment to a travel agency and its offerings is posited, and the relationship between the structure of the target market and market activity in purchasing tourist products is demonstrated. Deep market segmentation is applied to take into account the behavioral peculiarities of individual subsegments (Loyalists Market, Sympathizers Market, Qualified Market, Finders Market, Serviced Market, Possible Market, Potential Consumers Market, Perspective Market). Formulas are proposed for calculating the volume of each of the identified markets. An improved and adapted model for the tourist market (by E. Rogers and F. Bass) is used to calculate the diffusion rates of domestic tourist products. This methodology of forecasting the expected sales of innovative tourism products in the domestic market is empirically confirmed based on data on the domestic tourism market in the region of Vinnytsiya, Ukraine.