22 resultados para Packing for shipment


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The present Thesis reports on the various research projects to which I have contributed during my PhD period, working with several research groups, and whose results have been communicated in a number of scientific publications. The main focus of my research activity was to learn, test, exploit and extend the recently developed vdW-DFT (van der Waals corrected Density Functional Theory) methods for computing the structural, vibrational and electronic properties of ordered molecular crystals from first principles. A secondary, and more recent, research activity has been the analysis with microelectrostatic methods of Molecular Dynamics (MD) simulations of disordered molecular systems. While only very unreliable methods based on empirical models were practically usable until a few years ago, accurate calculations of the crystal energy are now possible, thanks to very fast modern computers and to the excellent performance of the best vdW-DFT methods. Accurate energies are particularly important for describing organic molecular solids, since they often exhibit several alternative crystal structures (polymorphs), with very different packing arrangements but very small energy differences. Standard DFT methods do not describe the long-range electron correlations which give rise to the vdW interactions. Although weak, these interactions are extremely sensitive to the packing arrangement, and neglecting them used to be a problem. The calculations of reliable crystal structures and vibrational frequencies has been made possible only recently, thanks to development of some good representations of the vdW contribution to the energy (known as “vdW corrections”).

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The research project is focused on the investigation of the polymorphism of crystalline molecular material for organic semiconductor applications under non-ambient conditions, and the solid-state characterization and crystal structure determination of the different polymorphic forms. In particular, this research project has tackled the investigation and characterization of the polymorphism of perylene diimides (PDIs) derivatives at high temperatures and pressures, in particular N,N’-dialkyl-3,4,9,10-perylendiimide (PDI-Cn, with n = 5, 6, 7, 8). These molecules are characterized by excellent chemical, thermal, and photostability, high electron affinity, strong absorption in the visible region, low LUMO energies, good air stability, and good charge transport properties, which can be tuned via functionalization; these features make them promising n-type organic semiconductor materials for several applications such as OFETs, OPV cells, laser dye, sensors, bioimaging, etc. The thermal characterization of PDI-Cn was carried out by a combination of differential scanning calorimetry, variable temperature X-ray diffraction, hot-stage microscopy, and in the case of PDI-C5 also variable temperature Raman spectroscopy. Whereas crystal structure determination was carried out by both Single Crystal and Powder X-ray diffraction. Moreover, high-pressure polymorphism via pressure-dependent UV-Vis absorption spectroscopy and high-pressure Single Crystal X-ray diffraction was carried out in this project. A data-driven approach based on a combination of self-organizing maps (SOM) and principal component analysis (PCA) is also reported was used to classify different π-stacking arrangements of PDI derivatives into families of similar crystal packing. Besides the main project, in the framework of structure-property analysis under non-ambient conditions, the structural investigation of the water loss in Pt- and Pd- based vapochromic potassium/lithium salts upon temperature, and the investigation of structure-mechanical property relationships in polymorphs of a thienopyrrolyldione endcapped oligothiophene (C4-NT3N) are reported.

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In the framework of industrial problems, the application of Constrained Optimization is known to have overall very good modeling capability and performance and stands as one of the most powerful, explored, and exploited tool to address prescriptive tasks. The number of applications is huge, ranging from logistics to transportation, packing, production, telecommunication, scheduling, and much more. The main reason behind this success is to be found in the remarkable effort put in the last decades by the OR community to develop realistic models and devise exact or approximate methods to solve the largest variety of constrained or combinatorial optimization problems, together with the spread of computational power and easily accessible OR software and resources. On the other hand, the technological advancements lead to a data wealth never seen before and increasingly push towards methods able to extract useful knowledge from them; among the data-driven methods, Machine Learning techniques appear to be one of the most promising, thanks to its successes in domains like Image Recognition, Natural Language Processes and playing games, but also the amount of research involved. The purpose of the present research is to study how Machine Learning and Constrained Optimization can be used together to achieve systems able to leverage the strengths of both methods: this would open the way to exploiting decades of research on resolution techniques for COPs and constructing models able to adapt and learn from available data. In the first part of this work, we survey the existing techniques and classify them according to the type, method, or scope of the integration; subsequently, we introduce a novel and general algorithm devised to inject knowledge into learning models through constraints, Moving Target. In the last part of the thesis, two applications stemming from real-world projects and done in collaboration with Optit will be presented.

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Conventional chromatographic columns are packed with porous beads by the universally employed slurry-packing method. The lack of precise control of the particle size distribution, shape and position inside the column have dramatic effects on the separation efficiency. In the first part the thesis an ordered, three-dimensional, pillar-array structure was designed by a CAD software. Several columns, characterized by different fluid distributors and bed length, were produced by a stereolithographic 3D printer and compared in terms of pressure drop and height equivalent to a theroretical plate (HETP). To prevent the release of unwanted substances and to provide a surface for immobilizing a ligand, pillars were coated with one or more of the following materials: titanium dioxide, nanofibrillated cellulose (NFC) and polystyrene. The external NFC layer was functionalized with Cibacron Blue and the dynamic binding capacity of the column was measured by performing three chromatographic cycles, using bovine serum albumin (BSA) as target molecule. The second part of the thesis deals with Covid-19 pandemic related research activities. In early 2020, due to the pandemic outbreak, surgical face masks became an essential non-pharmaceutical intervention to limit the spread. To address the consequent shortage and to support the reconversion of the Italian industry, in late March 2020 a multidisciplinary group of the University of Bologna created the first Italian laboratory able to perform all the tests required for the evaluation and certification of surgical masks. More than 1200 tests were performed on about 350 prototypes, according to the standard EN 14683:2019. The results were analyzed to define the best material properties and masks composition for the production of masks with excellent efficiency. To optimize the usage of surgical masks and to reduce their environmental burden, the variation of their performance over time of usage were investigated as to determine the maximum lifetime.

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The perquisites of organic semiconductors (OSCs) in the field of organic electronics have attracted much attention due to the advantages like cost-effectiveness, solution processibility, etc. A key property in OSCs is charge carrier mobility, which depends on molecular packing, as even the slightest changes in the packing of OSC can significantly impact the mobility. Organic molecules are constructed by weak interactions, which makes the OSCs prone to adopt multiple packing arrangements, thus giving rise to polymorphism. Therefore, polymorph screening in bulk and thin films is crucial for material development. This thesis aims to present a systematic study of polymorphism of [1]benzothieno[3,2-b]benzothiophene (BTBT) derivatives functionalized with different side chains. The role of peripheral side chains has been studied since they can promote different packing arrangements. The bulk polymorph screening of OSCs was approached with conventional solution mediated recrystallization experiments like evaporation, slurry maturation, anti-solvent precipitation, etc. Each of the polymorphs were inspected for their relative stability and the kinetics of transformation was evaluated. Polymorphism in thin films was also investigated for selected OSCs. Non-equilibrium methods like, thermal gradient and solution shearing were employed to examine the nucleation, crystal growth and morphology in controlled crystallization conditions. After careful analysis of crystal phases in bulk and thin films, OFETs have been fabricated by optimizing the manufacturing conditions and the hole mobility values were extracted. The charge transport property of the OSCs tested for OFETs was supported by the ionization potential and transfer integrals calculation. An attempt to correlate the solid-state structure to electronic properties was carried out. For some of the molecules, mechanical properties have been also investigated, as the response to mechanical stress is highly susceptible to packing arrangements and the intermolecular interaction energy contributions. Additionally, collaborative research was carried out by solving and analysing the crystal structures of six oligorylene molecules.

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This thesis deals with efficient solution of optimization problems of practical interest. The first part of the thesis deals with bin packing problems. The bin packing problem (BPP) is one of the oldest and most fundamental combinatorial optimiza- tion problems. The bin packing problem and its generalizations arise often in real-world ap- plications, from manufacturing industry, logistics and transportation of goods, and scheduling. After an introductory chapter, I will present two applications of two of the most natural extensions of the bin packing: Chapter 2 will be dedicated to an application of bin packing in two dimension to a problem of scheduling a set of computational tasks on a computer cluster, while Chapter 3 deals with the generalization of BPP in three dimensions that arise frequently in logistic and transportation, often com- plemented with additional constraints on the placement of items and characteristics of the solution, like, for example, guarantees on the stability of the items, to avoid potential damage to the transported goods, on the distribution of the total weight of the bins, and on compatibility with loading and unloading operations. The second part of the thesis, and in particular Chapter 4 considers the Trans- mission Expansion Problem (TEP), where an electrical transmission grid must be expanded so as to satisfy future energy demand at the minimum cost, while main- taining some guarantees of robustness to potential line failures. These problems are gaining importance in a world where a shift towards renewable energy can impose a significant geographical reallocation of generation capacities, resulting in the ne- cessity of expanding current power transmission grids.

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Molecular materials are made by the assembly of specifically designed molecules to obtain bulk structures with desired solid-state properties, enabling the development of materials with tunable chemical and physical properties. These properties result from the interplay of intra-molecular constituents and weak intermolecular interactions. Thus, small changes in individual molecular and electronic structure can substantially change the properties of the material in bulk. The purpose of this dissertation is, thus, to discuss and to contribute to the structure-property relationships governing the electronic, optical and charge transport properties of organic molecular materials through theoretical and computational studies. In particular, the main focus is on the interplay of intra-molecular properties and inter-molecular interactions in organic molecular materials. In my three-years of research activity, I have focused on three major areas: 1) the investigation of isolated-molecule properties for the class of conjugated chromophores displaying diradical character which are building blocks for promising functional materials; 2) the determination of intra- and intermolecular parameters governing charge transport in molecular materials and, 3) the development and application of diabatization procedures for the analysis of exciton states in molecular aggregates. The properties of diradicaloids are extensively studied both regarding their ground state (diradical character, aromatic vs quinoidal structures, spin dynamics, etc.) and the low-lying singlet excited states including the elusive double-exciton state. The efficiency of charge transport, for specific classes of organic semiconductors (including diradicaloids), is investigated by combining the effects of intra-molecular reorganization energy, inter-molecular electronic coupling and crystal packing. Finally, protocols aimed at unravelling the nature of exciton states are introduced and applied to different molecular aggregates. The role of intermolecular interactions and charge transfer contributions in determining the exciton state character and in modulating the H- to J- aggregation is also highlighted.