Mechanochemical solvent-free synthesis of Sn-β Zeolite and Ag2O/TiO2 catalysts

Preparations of heterogeneous catalysts are usually complex processes that involve several procedures as precipitation, crystallization and hydrothermal treatments. This processes are really dependent by the operative conditions such as temperature, pH, concentration etc. Hence the resulting product is extremely affected by any possible variations in these parameters making this synthesis really fragile. With the aim to improve these operations has been decided to exploit a new possible strong environment-respectful process by mechanochemical treatment, which permits to carry out solvent free-solvent synthesis exploiting the Mixer Mill MM400 (Retsch) in order to have reproducible results. Two different systems have been studied in this kind of synthesis: a tin β -zeolite tested in a H-trasnfer reaction of cyclohexanone and a silver on titania catalyst used in the fluorination of 2,2 dimethyl glucaric acid. Each catalyst has been characterized by different techniques in order to understand the transformations involved in the mechanochemical treatment.

Influence of free-radical functionalization on non-woven filtering media for medical application

Nowadays the leukodepletion is one of the most important processes done on the blood in order to reduce the risk of transfusion diseases. It can be performed through different techniques but the most popular one is the filtration due to its simplicity and efficiency. This work aims at improving a current commercial product, by developing a new filter based on Fenton-type reaction to cross-link a hydrogel on to the base material. The filters for leukodepletion are preferably made through the melt flow technique resulting in a non-woven tissue; the functionalization should increase the stability of the filter restricting the extraction of substances to minimum amount when in contact with blood. Through the modification the filters can acquire new properties including wettability, surface charge and good resistance to the extractions. The most important for leukodepletion is the surface charge due to the nature of the filtration process. All the modified samples results have been compared to the commercial product. Three different polymers (A, B and C) have been studied for the filter modifications and every modified filter has been tested in order to determine its properties.

A membrane process to extract Citrus Lemon derived extracellular vesicles

Extra cellular vesicles are membrane bound and lipid based nano particles having the size range of 30 to 1000 nm released by a plethora of cells. Their prime function is cellular communication but in the recent studies, the potential of these vesicles to maintain physiological and pathological processes as well as their nano-sized constituents opened doors to its applications in therapeutics, and diagnostics of variety of diseases such as cancer. Their main constituents include lipids, proteins, and RNAs. They are categorized into subtypes such as exosomes, micro-vesicles and apoptotic bodies In recent studies, extracellular vesicles that are derived from plants are gaining high regard due to their variety of advantages such as safety, non-toxicity, and high availability which promotes large scale production. EVs are isolated from mammalian and plant cells using multitude of techniques such as Ultracentrifugation, SEC, Precipitation and so on. Due to the variety in the sources as well as shortcomings arising from the isolation method, a scalable and inexpensive EV isolation method is yet to be designed. This study focusses on isolation of EVs from citrus lemon juice through diafiltration. Lemon is a promising source due to its biological properties to act as antioxidant, anticancer, and anti-inflammatory agents. Lemon derived vesicles was proven to have several proteins analogous to mammalian vesicles. A diafiltration could be carried out for successful removal of impurities and it is a scalable, continuous technique with potentially lower process times. The concentration of purified product and impurities are analysed using Size Exclusion Chromatography in analytical mode. It is also considered imperative to compare the results from diafiltration with gold standard UC. BCA is proposed to evaluate total protein content and DLS for size measurements. Finally, the ideal mode of storage of EVs to protect its internals and its structure is analysed with storage tests.

A deep learning model for controlling the galvanizing process in a production line

In the industry of steelmaking, the process of galvanizing is a treatment which is applied to protect the steel from corrosion. The air knife effect (AKE) occurs when nozzles emit a steam of air on the surfaces of a steel strip to remove excess zinc from it. In our work we formalized the problem to control the AKE and we implemented, with the R&D dept.of MarcegagliaSPA, a DL model able to drive the AKE. We call it controller. It takes as input the tuple : a tuple of the physical conditions of the process line (t,h,s) with the target value of the zinc coating (c); and generates the expected tuple of (pres and dist) to drive the mechanical nozzles towards the (c). According to the requirements we designed the structure of the network. We collected and explored the data set of the historical data of the smart factory. Finally, we designed the loss function as sum of three components: the minimization between the coating addressed by the network and the target value we want to reach; and two weighted minimization components for both pressure and distance. In our solution we construct a second module, named coating net, to predict the coating of zinc resulting from the AKE when the conditions are applied to the prod. line. Its structure is made by a linear and a deep nonlinear “residual” component learned by empirical observations. The predictions made by the coating nets are used as ground truth in the loss function of the controller. By tuning the weights of the different components of the loss function, it is possible to train models with slightly different optimization purposes. In the tests we compared the regularization of different strategies with the standard one in condition of optimal estimation for both; the overall accuracy is ± 3 g/m^2 dal target for all of them. Lastly, we analyze how the controller modeled the current solutions with the new logic: the sub-optimal values of pres and dist can be optimize of 50% and 20%.

Cure Induced Residual Stresses on Thick Composite Components Manufactured by Additive Process

This study investigates the effect of an additive process in manufacturing of thick composites. Airstone 780 E epoxy resin and 785H Hardener system is used in the analysis since it is widely used wind turbine blade, namely thick components. As a fiber, fabric by SAERTEX (812 g/m2) with a 0-90 degrees layup direction is used. Temperature overshoot is a major issue during the manufacturing of thick composites. A high temperature overshoot leads to an increase in residual stresses. These residual stresses are causing warping, delamination, dimensional instability, and undesired distortion of composite structures. A coupled thermo-mechanical model capable of predicting cure induced residual stresses have been built using the commercial FE software Abaqus®. The possibility of building thick composite components by means of adding a finite number of sub-laminates has been investigated. The results have been compared against components manufactured following a standard route. The influence of pre-curing of the sub-laminates has also been addressed and results compared with standard practice. As a result of the study, it is found that introducing additive process can prevent temperature overshoot to occur and benefits the residual stresses generation during the curing process. However, the process time required increases by 50%, therefore increasing the manufacturing costs. An optimized cure cycle is required to minimize process time and cure induced defects simultaneously.

Life cycle assessment (LCA) of a bio-fuel cell fed with waste biomass: potential for scale-up and process optimization

In this Thesis, a life cycle analysis (LCA) of a biofuel cell designed by a team from the University of Bologna was done. The purpose of this study is to investigate the possible environmental impacts of the production and use of the cell and a possible optimization for an industrial scale-up. To do so, a first part of the paper was devoted to studying the present literature on biomass, and fuel cell treatments and then LCA studies on them. The experimental part presents the work done to create the Life Cycle Inventory and Life Cycle Impact Assessment. Several alternative scenarios were created to study process optimization. Reagents and energy supply were changed. To examine whether this technology can be competitive, a comparison was made with some biofuel cell use scenarios with traditional biomass treatment technologies. The result of this study is that this technology is promising from an environmental point of view in case it is possible to recover nutrients in output, without excessive energy consumption, and to minimize the use of energy used to prepare the solution.