Oxidation and pyrolysis of methane and methyl formate in a plug flow reactor: computational and experimenal studies

Biodiesel represents a possible substitute to the fossil fuels; for this reason a good comprehension of the kinetics involved is important. Due to the complexity of the biodiesel mixture a common practice is the use of surrogate molecules to study its reactivity. In this work are presented the experimental and computational results obtained for the oxidation and pyrolysis of methane and methyl formate conducted in a plug flow reactor. The work was divided into two parts: the first one was the setup assembly whilst, in the second one, was realized a comparison between the experimental and model results; these last was obtained using models available in literature. It was started studying the methane since, a validate model was available, in this way was possible to verify the reliability of the experimental results. After this first study the attention was focused on the methyl formate investigation. All the analysis were conducted at different temperatures, pressures and, for the oxidation, at different equivalence ratios. The results shown that, a good comprehension of the kinetics is reach but efforts are necessary to better evaluate kinetics parameters such as activation energy. The results even point out that the realized setup is adapt to study the oxidation and pyrolysis and, for this reason, it will be employed to study a longer chain esters with the aim to better understand the kinetic of the molecules that are part of the biodiesel mixture.

Phage therapy: A software system for phage quantification and kinetic model inference.

One of the most serious problems of the modern medicine is the growing emergence of antibiotic resistance among pathogenic bacteria. In this circumstance, different and innovative approaches for treating infections caused by multidrug-resistant bacteria are imperatively required. Bacteriophage Therapy is one among the fascinating approaches to be taken into account. This consists of the use of bacteriophages, viruses that infect bacteria, in order to defeat specific bacterial pathogens. Phage therapy is not an innovative idea, indeed, it was widely used around the world in the 1930s and 1940s, in order to treat various infection diseases, and it is still used in Eastern Europe and the former Soviet Union. Nevertheless, Western scientists mostly lost interest in further use and study of phage therapy and abandoned it after the discovery and the spread of antibiotics. The advancement of scientific knowledge of the last years, together with the encouraging results from recent animal studies using phages to treat bacterial infections, and above all the urgent need for novel and effective antimicrobials, have given a prompt for additional rigorous researches in this field. In particular, in the laboratory of synthetic biology of the department of Life Sciences at the University of Warwick, a novel approach was adopted, starting from the original concept of phage therapy, in order to study a concrete alternative to antibiotics. The innovative idea of the project consists in the development of experimental methodologies, which allow to engineer a programmable synthetic phage system using a combination of directed evolution, automation and microfluidics. The main aim is to make “the therapeutics of tomorrow individualized, specific, and self-regulated” (Jaramillo, 2015). In this context, one of the most important key points is the Bacteriophage Quantification. Therefore, in this research work, a mathematical model describing complex dynamics occurring in biological systems involving continuous growth of bacteriophages, modulated by the performance of the host organisms, was implemented as algorithms into a working software using MATLAB. The developed program is able to predict different unknown concentrations of phages much faster than the classical overnight Plaque Assay. What is more, it gives a meaning and an explanation to the obtained data, making inference about the parameter set of the model, that are representative of the bacteriophage-host interaction.