Integrated analysis and design of optimization and up-scaling of inductively coupled plasma synthesis of nanoparticles

This study is focused on radio-frequency inductively coupled thermal plasma (ICP) synthesis of nanoparticles, combining experimental and modelling approaches towards process optimization and industrial scale-up, in the framework of the FP7-NMP SIMBA European project (Scaling-up of ICP technology for continuous production of Metallic nanopowders for Battery Applications). First the state of the art of nanoparticle production through conventional and plasma routes is summarized, then results for the characterization of the plasma source and on the investigation of the nanoparticle synthesis phenomenon, aiming at highlighting fundamental process parameters while adopting a design oriented modelling approach, are presented. In particular, an energy balance of the torch and of the reaction chamber, employing a calorimetric method, is presented, while results for three- and two-dimensional modelling of an ICP system are compared with calorimetric and enthalpy probe measurements to validate the temperature field predicted by the model and used to characterize the ICP system under powder-free conditions. Moreover, results from the modeling of critical phases of ICP synthesis process, such as precursor evaporation, vapour conversion in nanoparticles and nanoparticle growth, are presented, with the aim of providing useful insights both for the design and optimization of the process and on the underlying physical phenomena. Indeed, precursor evaporation, one of the phases holding the highest impact on industrial feasibility of the process, is discussed; by employing models to describe particle trajectories and thermal histories, adapted from the ones originally developed for other plasma technologies or applications, such as DC non-transferred arc torches and powder spherodization, the evaporation of micro-sized Si solid precursor in a laboratory scale ICP system is investigated. Finally, a discussion on the role of thermo-fluid dynamic fields on nano-particle formation is presented, as well as a study on the effect of the reaction chamber geometry on produced nanoparticle characteristics and process yield.

Food safety in wine: optimization of analytical controls and evaluation of production technologies

This PhD thesis has been proposed to validate and then apply innovative analytical methodologies for the determination of compounds with harmful impact on human health, such as biogenic amines and ochratoxin A in wines. Therefore, the influence of production technology (pH, amino acids precursor and use of different malolactic starters) on biogenic amines content in wines was evaluated. An HPLC method for simultaneous determination of amino acids and amines with precolumnderivatization with 9-Fluorenyl-methoxycarbonyl chloride (FMOC-Cl) and UV detection was developed. Initially, the influence of pH, time of derivatization, gradient profile were studied. In order to improve the separation of amino acids and amines and reduce the time of analysis, it was decided to study the influence of different flows and the use of different columns in the chromatographic method. Firstly, a C18 Luna column was used and later two monolithic columns Chromolith in series. It appeared to be suitable for an easy, precise and accurate determination of a relatively large number of amino acids and amines in wines. This method was then applied on different wines produced in the Emilia Romagna region. The investigation permitted to discriminate between red and white wines. Amino acids content is related to the winemaking process. Biogenic amines content in these wines does not represent a possible toxicological problem for human health. The results of the study of influence of technologies and wine composition demonstrated that pH of wines and amino acids content are the most important factors. Particularly wines with pH > 3,5 show higher concentration of biogenic amines than wines with lower pH. The enrichment of wines by nutrients also influences the content of some biogenic amines that are higher in wines added with amino acids precursors. In this study, amino acids and biogenic amines are not statistically affected by strain of lactic acid bacteria inoculated as a starter for malolactic fermentation. An evaluation of different clean-up (SPE-MycoSep; IACs and LLE) and determination methods (HPLC and ELISA) of ochratoxin A was carried out. The results obtained proved that the SPE clean-up are reliable at the same level while the LLE procedures shows lowest recovery. The ELISA method gave a lower determination and a low reproducibility than HPLC method.

Second law analysis and simulation techniques for the energy optimization of buildings

The research activity described in this thesis is focused mainly on the study of finite-element techniques applied to thermo-fluid dynamic problems of plant components and on the study of dynamic simulation techniques applied to integrated building design in order to enhance the energy performance of the building. The first part of this doctorate thesis is a broad dissertation on second law analysis of thermodynamic processes with the purpose of including the issue of the energy efficiency of buildings within a wider cultural context which is usually not considered by professionals in the energy sector. In particular, the first chapter includes, a rigorous scheme for the deduction of the expressions for molar exergy and molar flow exergy of pure chemical fuels. The study shows that molar exergy and molar flow exergy coincide when the temperature and pressure of the fuel are equal to those of the environment in which the combustion reaction takes place. A simple method to determine the Gibbs free energy for non-standard values of the temperature and pressure of the environment is then clarified. For hydrogen, carbon dioxide, and several hydrocarbons, the dependence of the molar exergy on the temperature and relative humidity of the environment is reported, together with an evaluation of molar exergy and molar flow exergy when the temperature and pressure of the fuel are different from those of the environment. As an application of second law analysis, a comparison of the thermodynamic efficiency of a condensing boiler and of a heat pump is also reported. The second chapter presents a study of borehole heat exchangers, that is, a polyethylene piping network buried in the soil which allows a ground-coupled heat pump to exchange heat with the ground. After a brief overview of low-enthalpy geothermal plants, an apparatus designed and assembled by the author to carry out thermal response tests is presented. Data obtained by means of in situ thermal response tests are reported and evaluated by means of a finite-element simulation method, implemented through the software package COMSOL Multyphysics. The simulation method allows the determination of the precise value of the effective thermal properties of the ground and of the grout, which are essential for the design of borehole heat exchangers. In addition to the study of a single plant component, namely the borehole heat exchanger, in the third chapter is presented a thorough process for the plant design of a zero carbon building complex. The plant is composed of: 1) a ground-coupled heat pump system for space heating and cooling, with electricity supplied by photovoltaic solar collectors; 2) air dehumidifiers; 3) thermal solar collectors to match 70% of domestic hot water energy use, and a wood pellet boiler for the remaining domestic hot water energy use and for exceptional winter peaks. This chapter includes the design methodology adopted: 1) dynamic simulation of the building complex with the software package TRNSYS for evaluating the energy requirements of the building complex; 2) ground-coupled heat pumps modelled by means of TRNSYS; and 3) evaluation of the total length of the borehole heat exchanger by an iterative method developed by the author. An economic feasibility and an exergy analysis of the proposed plant, compared with two other plants, are reported. The exergy analysis was performed by considering the embodied energy of the components of each plant and the exergy loss during the functioning of the plants.

Hybrid constraint programming and metaheuristic methods for large scale optimization problems

This work presents hybrid Constraint Programming (CP) and metaheuristic methods for the solution of Large Scale Optimization Problems; it aims at integrating concepts and mechanisms from the metaheuristic methods to a CP-based tree search environment in order to exploit the advantages of both approaches. The modeling and solution of large scale combinatorial optimization problem is a topic which has arisen the interest of many researcherers in the Operations Research field; combinatorial optimization problems are widely spread in everyday life and the need of solving difficult problems is more and more urgent. Metaheuristic techniques have been developed in the last decades to effectively handle the approximate solution of combinatorial optimization problems; we will examine metaheuristics in detail, focusing on the common aspects of different techniques. Each metaheuristic approach possesses its own peculiarities in designing and guiding the solution process; our work aims at recognizing components which can be extracted from metaheuristic methods and re-used in different contexts. In particular we focus on the possibility of porting metaheuristic elements to constraint programming based environments, as constraint programming is able to deal with feasibility issues of optimization problems in a very effective manner. Moreover, CP offers a general paradigm which allows to easily model any type of problem and solve it with a problem-independent framework, differently from local search and metaheuristic methods which are highly problem specific. In this work we describe the implementation of the Local Branching framework, originally developed for Mixed Integer Programming, in a CP-based environment. Constraint programming specific features are used to ease the search process, still mantaining an absolute generality of the approach. We also propose a search strategy called Sliced Neighborhood Search, SNS, that iteratively explores slices of large neighborhoods of an incumbent solution by performing CP-based tree search and encloses concepts from metaheuristic techniques. SNS can be used as a stand alone search strategy, but it can alternatively be embedded in existing strategies as intensification and diversification mechanism. In particular we show its integration within the CP-based local branching. We provide an extensive experimental evaluation of the proposed approaches on instances of the Asymmetric Traveling Salesman Problem and of the Asymmetric Traveling Salesman Problem with Time Windows. The proposed approaches achieve good results on practical size problem, thus demonstrating the benefit of integrating metaheuristic concepts in CP-based frameworks.

Design and optimization of components and processes for plasma sources in advanced material treatments

The research activities described in the present thesis have been oriented to the design and development of components and technological processes aimed at optimizing the performance of plasma sources in advanced in material treatments. Consumables components for high definition plasma arc cutting (PAC) torches were studied and developed. Experimental activities have in particular focussed on the modifications of the emissive insert with respect to the standard electrode configuration, which comprises a press fit hafnium insert in a copper body holder, to improve its durability. Based on a deep analysis of both the scientific and patent literature, different solutions were proposed and tested. First, the behaviour of Hf cathodes when operating at high current levels (250A) in oxidizing atmosphere has been experimentally investigated optimizing, with respect to expected service life, the initial shape of the electrode emissive surface. Moreover, the microstructural modifications of the Hf insert in PAC electrodes were experimentally investigated during first cycles, in order to understand those phenomena occurring on and under the Hf emissive surface and involved in the electrode erosion process. Thereafter, the research activity focussed on producing, characterizing and testing prototypes of composite inserts, combining powders of a high thermal conductibility (Cu, Ag) and high thermionic emissivity (Hf, Zr) materials The complexity of the thermal plasma torch environment required and integrated approach also involving physical modelling. Accordingly, a detailed line-by-line method was developed to compute the net emission coefficient of Ar plasmas at temperatures ranging from 3000 K to 25000 K and pressure ranging from 50 kPa to 200 kPa, for optically thin and partially autoabsorbed plasmas. Finally, prototypal electrodes were studied and realized for a newly developed plasma source, based on the plasma needle concept and devoted to the generation of atmospheric pressure non-thermal plasmas for biomedical applications.

A numerical methodology for the multi-objective optimization of the DI Diesel engine combustion

DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.

Optimization of purification procedures in organic semiconductor synthesis for improving the performances of organic field-effect transistors

The aim of the research activity focused on the investigation of the correlation between the degree of purity in terms of chemical dopants in organic small molecule semiconductors and their electrical and optoelectronic performances once introduced as active material in devices. The first step of the work was addressed to the study of the electrical performances variation of two commercial organic semiconductors after being processed by means of thermal sublimation process. In particular, the p-type 2,2′′′-Dihexyl-2,2′:5′,2′′:5′′,2′′′-quaterthiophene (DH4T) semiconductor and the n-type 2,2′′′- Perfluoro-Dihexyl-2,2′:5′,2′′:5′′,2′′′-quaterthiophene (DFH4T) semiconductor underwent several sublimation cycles, with consequent improvement of the electrical performances in terms of charge mobility and threshold voltage, highlighting the benefits brought by this treatment to the electric properties of the discussed semiconductors in OFET devices by the removal of residual impurities. The second step consisted in the provision of a metal-free synthesis of DH4T, which was successfully prepared without organometallic reagents or catalysts in collaboration with Dr. Manuela Melucci from ISOF-CNR Institute in Bologna. Indeed the experimental work demonstrated that those compounds are responsible for the electrical degradation by intentionally doping the semiconductor obtained by metal-free method by Tetrakis(triphenylphosphine)palladium(0) (Pd(PPh3)4) and Tributyltin chloride (Bu3SnCl), as well as with an organic impurity, like 5-hexyl-2,2':5',2''-terthiophene (HexT3) at, in different concentrations (1, 5 and 10% w/w). After completing the entire evaluation process loop, from fabricating OFET devices by vacuum sublimation with implemented intentionally-doped batches to the final electrical characterization in inherent-atmosphere conditions, commercial DH4T, metal-free DH4T and the intentionally-doped DH4T were systematically compared. Indeed, the fabrication of OFET based on doped DH4T clearly pointed out that the vacuum sublimation is still an inherent and efficient purification method for crude semiconductors, but also a reliable way to fabricate high performing devices.

Optimization of molecular and crystalline forms of drugs, agrochemicals, pesticides in relation to activity, bioavailability, patentability and to the fabrication of polymorphs, solvates, co-crystals with green chemistry methods

This doctorate was funded by the Regione Emilia Romagna, within a Spinner PhD project coordinated by the University of Parma, and involving the universities of Bologna, Ferrara and Modena. The aim of the project was: - Production of polymorphs, solvates, hydrates and co-crystals of active pharmaceutical ingredients (APIs) and agrochemicals with green chemistry methods; - Optimization of molecular and crystalline forms of APIs and pesticides in relation to activity, bioavailability and patentability. In the last decades, a growing interest in the solid-state properties of drugs in addition to their solution chemistry has blossomed. The achievement of the desired and/or the more stable polymorph during the production process can be a challenge for the industry. The study of crystalline forms could be a valuable step to produce new polymorphs and/or co-crystals with better physical-chemical properties such as solubility, permeability, thermal stability, habit, bulk density, compressibility, friability, hygroscopicity and dissolution rate in order to have potential industrial applications. Selected APIs (active pharmaceutical ingredients) were studied and their relationship between crystal structure and properties investigated, both in the solid state and in solution. Polymorph screening and synthesis of solvates and molecular/ionic co-crystals were performed according to green chemistry principles. Part of this project was developed in collaboration with chemical/pharmaceutical companies such as BASF (Germany) and UCB (Belgium). We focused on on the optimization of conditions and parameters of crystallization processes (additives, concentration, temperature), and on the synthesis and characterization of ionic co-crystals. Moreover, during a four-months research period in the laboratories of Professor Nair Rodriguez-Hormedo (University of Michigan), the stability in aqueous solution at the equilibrium of ionic co-crystals (ICCs) of the API piracetam was investigated, to understand the relationship between their solid-state and solution properties, in view of future design of new crystalline drugs with predefined solid and solution properties.

Models and Algorihtm for the Optimization of Real-World Routing and Logistics Problems

Logistics involves planning, managing, and organizing the flows of goods from the point of origin to the point of destination in order to meet some requirements. Logistics and transportation aspects are very important and represent a relevant costs for producing and shipping companies, but also for public administration and private citizens. The optimization of resources and the improvement in the organization of operations is crucial for all branches of logistics, from the operation management to the transportation. As we will have the chance to see in this work, optimization techniques, models, and algorithms represent important methods to solve the always new and more complex problems arising in different segments of logistics. Many operation management and transportation problems are related to the optimization class of problems called Vehicle Routing Problems (VRPs). In this work, we consider several real-world deterministic and stochastic problems that are included in the wide class of the VRPs, and we solve them by means of exact and heuristic methods. We treat three classes of real-world routing and logistics problems. We deal with one of the most important tactical problems that arises in the managing of the bike sharing systems, that is the Bike sharing Rebalancing Problem (BRP). We propose models and algorithms for real-world earthwork optimization problems. We describe the 3DP process and we highlight several optimization issues in 3DP. Among those, we define the problem related to the tool path definition in the 3DP process, the 3D Routing Problem (3DRP), which is a generalization of the arc routing problem. We present an ILP model and several heuristic algorithms to solve the 3DRP.