Synthesis and metal complexes of C2 symmetric ligands obtained from (R)-(+)-Betti and dialdehydes for asymmetric induction reactions

The aim of this master’s research thesis was the employment of an enantiopure 1,3-aminoalcohol, the 1-(α-aminobenzyl)-2-naphthol, known as Betti base, for the synthesis of some novel compounds which show a C2 symmetry. Some of these compounds, after derivatization, were used as ligands in association with transition metals to prepare some catalysts for enantioselective catalytic reactions. Some aminoalcohol (Salan-type) derivatives of these compounds were obtained upon reduction and in some cases it was possible to obtain complexes with transition metals such as Mn, Ni, Co and Cu. Furthermore a novel 6-membered analogue bisoxazoline ligand, 2,6-bis((R)-1-Phenyl-1H-naphtho[1,2-e][1,3]oxazin-3-yl)pyridine, was obtained and from it two Cu-complexes were prepared. The metal complexes were employed in some reactions to test the asymmetric induction, which was in some cases up to discrete values.

Dynamic mechanical-thermal, microstructural and mechanical analysis of ultra-light polymer-metal composites: influence of forming

A really particular and innovative metal-polymer sandwich material is Hybrix. Hybrix is a product developed and manufactured by Lamera AB, Gothenburg, Sweden. This innovative hybrid material is composed by two relatively thin metal layers if compared to the core thickness. The most used metals are aluminum and stainless steel and are separated by a core of nylon fibres oriented perpendicularly to the metal plates. The core is then completed by adhesive layers applied at the PA66-metal interface that once cured maintain the nylon fibres in position. This special material is very light and formable. Moreover Hybrix, depending on the specific metal which is used, can achieve a good corrosion resistance and it can be cut and punched easily. Hybrix architecture itself provides extremely good bending stiffness, damping properties, insulation capability, etc., which again, of course, change in magnitude depending in the metal alloy which is used, its thickness and core thickness. For these reasons nowadays it shows potential for all the applications which have the above mentioned characteristic as a requirement. Finally Hybrix can be processed with tools used in regular metal sheet industry and can be handled as solid metal sheets. In this master thesis project, pre-formed parts of Hybrix were studied and characterized. Previous work on Hybrix was focused on analyze its market potential and different adhesive to be used in the core. All the tests were carried out on flat unformed specimens. However, in order to have a complete description of this material also the effect of the forming process must be taken into account. Thus the main activities of the present master thesis are the following: Dynamic Mechanical-Thermal Analysis (DMTA) on unformed Hybrix samples of different thickness and on pre-strained Hybrix samples, pure epoxy adhesive samples analysis and finally moisture effects evaluation on Hybrix composite structure.

Analysis and improvements of an existing industrial hot stamping machine

The importance of product presentation in the marketing industry is well known. Labels are crucial for providing information to the buyer, but at a modest additional expense, a beautiful label with exquisite embellishments may also give the goods a sensation of high quality and elegance. Enhancing the capabilities of stamping machines is required to keep up with the increasing velocity of the production lines in the modern manufacturing industry and to offer new opportunities for customization. It’s in this context of improvements and refinements that this work takes place. The thesis was developed during an internship at Studio D, the firm that designs the mechanics of the machines produced by Cartes. The The aim of this work is to study possible upgrades for the existing hot stamping machines. The main focus of this work is centred on two objectives: first, evaluating the pressing forces generated by this machine and characterising how the mat used in the stamping process reacts to such forces. Second, propose a new conformation for the press mechanism in order to improve the rigidity and performance of the machines. The first objective is reached through a combined approach: the mat is crudely characterized with experimental data, while the frame of the machine is studied through FEM analysis. The results obtained are combined and used to upgrade a worksheet that allows to estimate the forces exerted by the machines. The second objective is reached with the proposal of new, improved designs for the main components of the machines.

Computer vision in aseptic pharmaceutical manufacturing: a deep learning-based approach to vial inspection and pack formation during a lyophilizer loading cycle

Vision systems are powerful tools playing an increasingly important role in modern industry, to detect errors and maintain product standards. With the enlarged availability of affordable industrial cameras, computer vision algorithms have been increasingly applied in industrial manufacturing processes monitoring. Until a few years ago, industrial computer vision applications relied only on ad-hoc algorithms designed for the specific object and acquisition setup being monitored, with a strong focus on co-designing the acquisition and processing pipeline. Deep learning has overcome these limits providing greater flexibility and faster re-configuration. In this work, the process to be inspected consists in vials’ pack formation entering a freeze-dryer, which is a common scenario in pharmaceutical active ingredient packaging lines. To ensure that the machine produces proper packs, a vision system is installed at the entrance of the freeze-dryer to detect eventual anomalies with execution times compatible with the production specifications. Other constraints come from sterility and safety standards required in pharmaceutical manufacturing. This work presents an overview about the production line, with particular focus on the vision system designed, and about all trials conducted to obtain the final performance. Transfer learning, alleviating the requirement for a large number of training data, combined with data augmentation methods, consisting in the generation of synthetic images, were used to effectively increase the performances while reducing the cost of data acquisition and annotation. The proposed vision algorithm is composed by two main subtasks, designed respectively to vials counting and discrepancy detection. The first one was trained on more than 23k vials (about 300 images) and tested on 5k more (about 75 images), whereas 60 training images and 52 testing images were used for the second one.

L'utilizzo di carbonati come reagenti per la sintesi "green" di derivati fenolici: l'esempio del 2-fenossi-1-etanolo

2-Phenoxyethanol (ethylene glycol monophenyl ether) is used as solvent for cellulose acetate, dyes, inks, and resins; it is a synthetic intermediate in the production of plasticizers, pharmaceuticals, and fragrances. Phenoxyethanol is obtained industrially by reaction of phenol with ethylene oxide, in the presence of an homogeneous alkaline catalyst, typically sodium hydroxide. The yield is not higher than 95-96%, because of the formation of polyethoxylated compounds. However, the product obtained may not be acceptable for use in cosmetic preparations and fragrance formulations, due to presence of a pungent “metallic” odor which masks the pleasant odor of the ether, deriving from residual traces of the metallic catalyst. Here we report a study aimed at using ethylene carbonate in place of ethylene oxide as the reactant for phenoxyethanol synthesis; the use of carbonates as green nucleophilic reactants is an important issue in the context of a modern and sustainable chemical industry. Moreover, in the aim of developing a process which might adhere the principles of Green Chemistry, we avoided the use of solvents, and used heterogeneous basic catalysts. We carried out the reaction by using various molar ratios between phenol and ethylene carbonate, at temperatures ranging between 180 and 240°C, with a Na-mordenite catalyst. Under specific conditions, it was possible to obtain total phenol conversion with >99% yield to phenoxyethanol in few hours reaction time, using a moderate excess of ethylene carbonate. Similar results, but with longer reaction times, were obtained using a stoichiometric feed ratio of reactants. One important issue of the research was finding conditions under which the leaching of Na was avoided, and the catalyst could be separated and reused for several reaction batches.

Modeling and simulation of a synthetic genetic circuit that implements a multicelled behavior in a growing microcolony of E. coli

Synthetic Biology is a relatively new discipline, born at the beginning of the New Millennium, that brings the typical engineering approach (abstraction, modularity and standardization) to biotechnology. These principles aim to tame the extreme complexity of the various components and aid the construction of artificial biological systems with specific functions, usually by means of synthetic genetic circuits implemented in bacteria or simple eukaryotes like yeast. The cell becomes a programmable machine and its low-level programming language is made of strings of DNA. This work was performed in collaboration with researchers of the Department of Electrical Engineering of the University of Washington in Seattle and also with a student of the Corso di Laurea Magistrale in Ingegneria Biomedica at the University of Bologna: Marilisa Cortesi. During the collaboration I contributed to a Synthetic Biology project already started in the Klavins Laboratory. In particular, I modeled and subsequently simulated a synthetic genetic circuit that was ideated for the implementation of a multicelled behavior in a growing bacterial microcolony. In the first chapter the foundations of molecular biology are introduced: structure of the nucleic acids, transcription, translation and methods to regulate gene expression. An introduction to Synthetic Biology completes the section. In the second chapter is described the synthetic genetic circuit that was conceived to make spontaneously emerge, from an isogenic microcolony of bacteria, two different groups of cells, termed leaders and followers. The circuit exploits the intrinsic stochasticity of gene expression and intercellular communication via small molecules to break the symmetry in the phenotype of the microcolony. The four modules of the circuit (coin flipper, sender, receiver and follower) and their interactions are then illustrated. In the third chapter is derived the mathematical representation of the various components of the circuit and the several simplifying assumptions are made explicit. Transcription and translation are modeled as a single step and gene expression is function of the intracellular concentration of the various transcription factors that act on the different promoters of the circuit. A list of the various parameters and a justification for their value closes the chapter. In the fourth chapter are described the main characteristics of the gro simulation environment, developed by the Self Organizing Systems Laboratory of the University of Washington. Then, a sensitivity analysis performed to pinpoint the desirable characteristics of the various genetic components is detailed. The sensitivity analysis makes use of a cost function that is based on the fraction of cells in each one of the different possible states at the end of the simulation and the wanted outcome. Thanks to a particular kind of scatter plot, the parameters are ranked. Starting from an initial condition in which all the parameters assume their nominal value, the ranking suggest which parameter to tune in order to reach the goal. Obtaining a microcolony in which almost all the cells are in the follower state and only a few in the leader state seems to be the most difficult task. A small number of leader cells struggle to produce enough signal to turn the rest of the microcolony in the follower state. It is possible to obtain a microcolony in which the majority of cells are followers by increasing as much as possible the production of signal. Reaching the goal of a microcolony that is split in half between leaders and followers is comparatively easy. The best strategy seems to be increasing slightly the production of the enzyme. To end up with a majority of leaders, instead, it is advisable to increase the basal expression of the coin flipper module. At the end of the chapter, a possible future application of the leader election circuit, the spontaneous formation of spatial patterns in a microcolony, is modeled with the finite state machine formalism. The gro simulations provide insights into the genetic components that are needed to implement the behavior. In particular, since both the examples of pattern formation rely on a local version of Leader Election, a short-range communication system is essential. Moreover, new synthetic components that allow to reliably downregulate the growth rate in specific cells without side effects need to be developed. In the appendix are listed the gro code utilized to simulate the model of the circuit, a script in the Python programming language that was used to split the simulations on a Linux cluster and the Matlab code developed to analyze the data.

Analysis of retrieved shoulder prostheses

In the last years the number of shoulder arthroplasties has been increasing. Simultaneously the study of their shape, size and strength and the reasons that bring to a possible early explantation have not yet been examined in detail. The research carried out directly on explants is practically nonexistent, this means a poor understanding of the mechanisms leading the patient and so the surgeon, to their removal. The analysis of the mechanisms which are the cause of instability, dislocation, broken, fracture, etc, may lead to a change in the structure or design of the shoulder prostheses and lengthen the life of the implant in situ. The idea was to analyze 22 explants through three methods in order to find roughness, corrosion and surface wear. In the first method, the humeral heads and/or the glenospheres were examined with the interferometer, a machine that through electromagnetic waves gives information about the roughness of the surfaces under examination. The output of the device was a total profile containing both roughness and information on the waves (representing the spatial waves most characteristic on the surface). The most important value is called "roughness average" and brings the average value of the peaks found in the local defects of the surfaces. It was found that 42% of the prostheses had considerable peak values in the area where the damage was caused by the implant and not only by external events, such as possibly the surgeon's hand. One of the problems of interest in the use of metallic biomaterials is their resistance to corrosion. The clinical significance of the degradation of metal implants has been the purpose of the second method; the interaction between human body and metal components is critical to understand how and why they arrive to corrosion. The percentage of damage in the joints of the prosthetic components has been calculated via high resolution photos and the software ImageJ. The 40% and 50% of the area appeared to have scratches or multiple lines due to mechanical artifacts. The third method of analysis has been made through the use of electron microscopy to quantify the wear surface in polyethylene components. Different joint movements correspond to different mechanisms of damage, which were imprinted in the parts of polyethylene examined. The most affected area was located mainly in the side edges. The results could help the manufacturers to modify the design of the prostheses and thus reduce the number of explants. It could also help surgeons in choosing the model of the prosthesis to be implanted in the patient.