The initial phase of sodium sulfite pulping of softwood : A comparison of different pulping options

Single stage and two-stage sodium sulfite cooking were carried out on either spruce, pine or pure pine heartwood chips to investigate the influence of several process parameters on the initial phase of such a cook down to about 60 % pulp yield. The cooking experiments were carried out in the laboratory with either a lab-prepared or a mill-prepared cooking acid and the temperature and time were varied. The influences of dissolved organic and inorganic components in the cooking liquor on the final pulp composition and on the extent of side reactions were investigated. Kinetic equations were developed and the activation energies for delignification and carbohydrate dissolution were calculated using the Arrhenius equation. A better understanding of the delignification mechanisms during bisulfite and acid sulfite cooking was obtained by analyzing the lignin carbohydrate complexes (LCC) present in the pulp when different cooking conditions were used. It was found that using a mill-prepared cooking acid beneficial effect with respect to side reactions, extractives removal and higher stability in pH during the cook were observed compared to a lab-prepared cooking acid. However, no significant difference in degrees of delignification or carbohydrate degradation was seen.  The cellulose yield was not affected in the initial phase of the cook however; temperature had an influence on the rates of both delignification and hemicellulose removal. It was also found that the  corresponding activation energies increased in the order:  xylan, glucomannan, lignin and cellulose. The cooking temperature could thus be used to control the cook to a given carbohydrate composition in the final pulp. Lignin condensation reactions were observed during acid sulfite cooking, especially at higher temperatures. The LCC studies indicated the existence of covalent bonds between lignin and hemicellulose components with respect to xylan and glucomannan. LCC in native wood showed the presence of phenyl glycosides, ϒ-esters and α-ethers; whereas the α-ethers  were affected during sulfite pulping. The existence of covalent bonds between lignin and wood polysaccharides might be the rate-limiting factor in sulfite pulping.

Multi-objective optimization of material model parameters of an adhesive layer by using SPEA2

The usage of multi material structures in industry, especially in the automotive industry are increasing. To overcome the difficulties in joining these structures, adhesives have several benefits over traditional joining methods. Therefore, accurate simulations of the entire process of fracture including the adhesive layer is crucial. In this paper, material parameters of a previously developed meso mechanical finite element (FE) model of a thin adhesive layer are optimized using the Strength Pareto Evolutionary Algorithm (SPEA2). Objective functions are defined as the error between experimental data and simulation data. The experimental data is provided by previously performed experiments where an adhesive layer was loaded in monotonically increasing peel and shear. Two objective functions are dependent on 9 model parameters (decision variables) in total and are evaluated by running two FEsimulations, one is loading the adhesive layer in peel and the other in shear. The original study converted the two objective functions into one function that resulted in one optimal solution. In this study, however, a Pareto frontis obtained by employing the SPEA2 algorithm. Thus, more insight into the material model, objective functions, optimal solutions and decision space is acquired using the Pareto front. We compare the results and show good agreement with the experimental data.

Climate variability of the last 1000 years in the NW Pacific: high resolution, multi-biomarker records from Lake Toyoni

The East Asian Monsoon (EAM) is an active component of the global climate system and has a profound social and economic impact in East Asia and its surrounding countries. Its impact on regional hydrological processes may influence society through industrial water supplies, food productivity and energy use. In order to predict future rates of climate change, reliable and accurate reconstructions of regional temperature and rainfall are required from all over the world to test climate models and better predict future climate variability. Hokkaido is a region which has limited palaeo-climate data and is sensitive to climate change. Instrumental data show that the climate in Hokkaido is influenced by the East Asian Monsoon (EAM), however, instrumental data is limited to the past ~150 years. Therefore down-core climate reconstructions, prior to instrumental records, are required to provide a better understanding of the long-term behaviour of the climate drivers (e.g. the EAM, Westerlies, and teleconnections) in this region. The present study develops multi-proxy reconstructions to determine past climatic and hydrologic variability in Japan over the past 1000 years and aid in understanding the effects of the EAM and the Westerlies independently and interactively. A 250-cm long sediment core from Lake Toyoni, Hokkaido was retrieved to investigate terrestrial and aquatic input, lake temperature and hydrological changes over the past 1000-years within Lake Toyoni and its catchment using X-Ray Fluorescence (XRF) data, alkenone palaeothermometry, the molecular and hydrogen isotopic composition of higher plant waxes (δD(HPW)). Here, we conducted the first survey for alkenone biomarkers in eight lakes in the Hokkaido, Japan. We detected the occurrence of alkenones within the sediments of Lake Toyoni. We present the first lacustrine alkenone record from Japan, including genetic analysis of the alkenone producer. C37 alkenone concentrations in surface sediments are 18µg C37 g−1 of dry sediment and the dominant alkenone is C37:4. 18S rDNA analysis revealed the presence of a single alkenone producer in Lake Toyoni and thus a single calibration is used for reconstructing lake temperature based on alkenone unsaturation patterns. Temperature reconstructions over the past 1000 years suggest that lake water temperatures varies between 8 and 19°C which is in line with water temperature changes observed in the modern Lake Toyoni. The alkenone-based temperature reconstruction provides evidence for the variability of the EAM over the past 1000 years. The δD(HPW) suggest that the large fluctuations (∼40‰) represent changes in temperature and source precipitation in this region, which is ultimately controlled by the EAM system and therefore a proxy for the EAM system. In order to complement the biomarker reconstructions, the XRF data strengthen the lake temperature and hydrological reconstructions by providing information on past productivity, which is controlled by the East Asian Summer monsoon (EASM) and wind input into Lake Toyoni, which is controlled by the East Asian Winter Monsoon (EAWM) and the Westerlies. By combining the data generated from XRF, alkenone palaeothermometry and the δD(HPW) reconstructions, we provide valuable information on the EAM and the Westerlies, including; the timing of intensification and weakening, the teleconnections influencing them and the relationship between them. During the Medieval Warm Period (MWP), we find that the EASM dominated and the EAWM was suppressed, whereas, during the Little Ice Age (LIA), the influence of the EAWM dominated with time periods of increased EASM and Westerlies intensification. The El Niño Southern Oscillation (ENSO) significantly influenced the EAM; a strong EASM occurred during El Niño conditions and a strong EAWM occurred during La Niña. The North Atlantic Oscillation, on the other hand, was a key driver of the Westerlies intensification; strengthening of the Westerlies during a positive NAO phase and weakening of the Westerlies during a negative NAO phase. A key finding from this study is that our data support an anti-phase relationship between the EASM and the EAWM (e.g. the intensification of the EASM and weakening of the EAWM and vice versa) and that the EAWM and the Westerlies vary independently from each other, rather than coincide as previously suggested in other studies.

A multi-methodological approach for the study of polymorphism in organic pigments and pharmaceuticals

The study of polymorphism has an important role in several fields of materials science, because structural differences lead to different physico-chemical properties of the system. This PhD work was dedicated to the investigation of polymorphism in Indigo, Thioindigo and Quinacridone, as case studies among the organic pigments employed as semiconductors, and in Paracetamol, Phenytoin and Nabumetone, chosen among some commonly used API. The aim of the research was to improve the understanding on the structures of bulk crystals and thin films, adopting Raman spectroscopy as the method of choice, while resorting to other experimental techniques to complement the gathered information. Different crystalline polymorphs, in fact, may be conveniently distinguished by their Raman spectra in the region of the lattice phonons (10-150 cm-1), the frequencies of which, probing the inter-molecular interactions, are very sensitive to even slight modifications in the molecular packing. In particular, we have used Confocal Raman Microscopy, which is a powerful, yet simple, technique for the investigation of crystal polymorphism in organic and inorganic materials, being capable of monitoring physical modifications, chemical transformations and phase inhomogeneities in crystal domains at the micrometre scale. In this way, we have investigated bulk crystals and thin film samples obtained with a variety of crystal growth and deposition techniques. Pure polymorphs and samples with phase mixing were found and fully characterized. Raman spectroscopy was complemented mainly by XRD measurements for bulk crystals and by AFM, GIXD and TEM for thin films. Structures and phonons of the investigated polymorphs were computed by DFT methods, and the comparison between theoretical and experimental results was used to assess the relative stability of the polymorphs and to assist the spectroscopic investigation. The Raman measurements were thus found to be able to clarify ambiguities in the phase assignments which otherwise the other methods were unable to solve.

Design of experiment in drug development: optimal allocations in multi-arm clinical trials and design space for multi-step processes

In this thesis, we deal with the design of experiments in the drug development process, focusing on the design of clinical trials for treatment comparisons (Part I) and the design of preclinical laboratory experiments for proteins development and manufacturing (Part II). In Part I we propose a multi-purpose design methodology for sequential clinical trials. We derived optimal allocations of patients to treatments for testing the efficacy of several experimental groups by also taking into account ethical considerations. We first consider exponential responses for survival trials and we then present a unified framework for heteroscedastic experimental groups that encompasses the general ANOVA set-up. The very good performance of the suggested optimal allocations, in terms of both inferential and ethical characteristics, are illustrated analytically and through several numerical examples, also performing comparisons with other designs proposed in the literature. Part II concerns the planning of experiments for processes composed of multiple steps in the context of preclinical drug development and manufacturing. Following the Quality by Design paradigm, the objective of the multi-step design strategy is the definition of the manufacturing design space of the whole process and, as we consider the interactions among the subsequent steps, our proposal ensures the quality and the safety of the final product, by enabling more flexibility and process robustness in the manufacturing.

Distributed Large-scale Mixed-Integer Optimization with Application to Energy and Multi-robot Networks

Several decision and control tasks in cyber-physical networks can be formulated as large- scale optimization problems with coupling constraints. In these "constraint-coupled" problems, each agent is associated to a local decision variable, subject to individual constraints. This thesis explores the use of primal decomposition techniques to develop tailored distributed algorithms for this challenging set-up over graphs. We first develop a distributed scheme for convex problems over random time-varying graphs with non-uniform edge probabilities. The approach is then extended to unknown cost functions estimated online. Subsequently, we consider Mixed-Integer Linear Programs (MILPs), which are of great interest in smart grid control and cooperative robotics. We propose a distributed methodological framework to compute a feasible solution to the original MILP, with guaranteed suboptimality bounds, and extend it to general nonconvex problems. Monte Carlo simulations highlight that the approach represents a substantial breakthrough with respect to the state of the art, thus representing a valuable solution for new toolboxes addressing large-scale MILPs. We then propose a distributed Benders decomposition algorithm for asynchronous unreliable networks. The framework has been then used as starting point to develop distributed methodologies for a microgrid optimal control scenario. We develop an ad-hoc distributed strategy for a stochastic set-up with renewable energy sources, and show a case study with samples generated using Generative Adversarial Networks (GANs). We then introduce a software toolbox named ChoiRbot, based on the novel Robot Operating System 2, and show how it facilitates simulations and experiments in distributed multi-robot scenarios. Finally, we consider a Pickup-and-Delivery Vehicle Routing Problem for which we design a distributed method inspired to the approach of general MILPs, and show the efficacy through simulations and experiments in ChoiRbot with ground and aerial robots.

Hardware-in-the-loop implementation of single- and dual-phase shift control for dual active bridge converters in EV applications

Isolated DC-DC converters play a significant role in fast charging and maintaining the variable output voltage for EV applications. This study aims to investigate the different Isolated DC-DC converters for onboard and offboard chargers, then, once the topology is selected, study the control techniques and, finally, achieve a real-time converter model to accomplish Hardware-In-The-Loop (HIL) results. Among the different isolated DC-DC topologies, the Dual Active Bridge (DAB) converter has the advantage of allowing bidirectional power flow, which enables operating in both Grid to Vehicle (G2V) and Vehicle to Grid (V2G) modalities. Recently, DAB has been used in the offboard chargers for high voltage applications due to SiC and GaN MOSFETs; this new technology also allows the utilization of higher switching frequencies. By empowering soft switching techniques to reduce switching losses, higher switching frequency operation is possible in DAB. There are four phase shift control techniques for the DAB converter. They are Single Phase shift, Extended Phase shift, Dual Phase shift, Triple Phase shift controls. This thesis considers two control strategies; Single-Phase, and Dual-Phase shifts, to understand the circulating currents, power losses, and output capacitor size reduction in the DAB. Hardware-In-The-Loop (HIL) experiments are carried out on both controls with high switching frequencies using the PLECS software tool and the RT box supporting the PLECS. Root Mean Square Error is also calculated for steady-state values of output voltage with different sampling frequencies in both the controls to identify the achievable sampling frequency in real-time. DSP implementation is also executed to emulate the optimized DAB converter design, and final real-time simulation results are discussed for both the Single-Phase and Dual-Phase shift controls.

Development of novel multi-substituted apatite nanophases with advanced functionalities for bone regeneration

In the field of bone substitutes is highly researched an innovative material able to fill gaps with high mechanical performances and able to stimulate cell response, permitting the complete restoration of the bone portion. In this respect, the synthesis of new bioactive materials able to mimic the compositional, morphological and mechanical features of bone is considered as the elective approach for effective tissue regeneration. Hydroxyapatite (HA) is the main component of the inorganic part of bone. Additionally ionic substitution can be performed in the apatite lattice producing different effects, depending from the selected ions. Magnesium, in substitution of calcium, and carbonate, in substitution of phosphate, extensively present in the biological bones, are able to improve properties naturally present in the apatitic phase, (i.e. biomimicry, solubility e osteoinductive properties). Other ions can be used to give new useful properties, like antiresorptive or antimicrobial properties, to the apatitic phase. This thesis focused on the development of hydroxyapatite nanophases with multiple ionic substitutions including gallium, or zinc ions, in association with magnesium and carbonate, with the purpose to provide double synergistic functionality as osteogenic and antibacterial biomaterial. Were developed bioactive materials based on Sr-substituted hydroxyapatite in the form of sintered targets. The obtained targets were treated with Pulsed Plasma Deposition (PED) resulting in the deposition of thin film coatings able to improve the roughness and wettability of PEEK, enhancing its osteointegrability. Were investigated heterogeneous gas-solid reactions, addressed to the biomorphic transformations of natural 3D porous structures into bone scaffolds with biomimetic composition and hierarchical organization, for application in load-bearing sites. The kinetics of the different reactions of the process were optimized to achieve complete and controlled phase transformation, maintaining the original 3-D morphology. Massive porous scaffolds made of ion-substituted hydroxyapatite and bone-mimicking structure were developed and tested in 3-D cell culture models.

Multi-functional electrocatalysts for CO2 reduction reaction: towards the modulation of selectivity

The electrocatalytic reduction of CO2 (CO2RR) is a captivating strategy for the conversion of CO2 into fuels, to realize a carbon neutral circular economy. In the recent years, research has focused on the development of new materials and technology capable of capturing and converting CO2 into useful products. The main problem of CO2RR is given by its poor selectivity, which can lead to the formation of numerous reaction products, to the detriment of efficiencies. For this reason, the design of new electrocatalysts that selectively and efficiently reduce CO2 is a fundamental step for the future exploitation of this technology. Here we present a new class of electrocatalysts, designed with a modular approach, namely, deriving from the combination of different building blocks in a single nanostructure. With this approach it is possible to obtain materials with an innovative design and new functionalities, where the interconnections between the various components are essential to obtain a highly selective and efficient reduction of CO2, thus opening up new possibilities in the design of optimized electrocatalytic materials. By combining the unique physic-chemical properties of carbon nanostructures (CNS) with nanocrystalline metal oxides (MO), we were able to modulate the selectivity of CO2RR, with the production of formic acid and syngas at low overpotentials. The CNS have not only the task of stabilizing the MO nanoparticles, but the creation of an optimal interface between two nanostructures is able to improve the catalytic activity of the active phase of the material. While the presence of oxygen atoms in the MO creates defects that accelerate the reaction kinetics and stabilize certain reaction intermediates, selecting the reaction pathway. Finally, a part was dedicated to the study of the experimental parameters influencing the CO2RR, with the aim of improving the experimental setup in order to obtain commercial catalytic performances.

Test vector generation for the phase II ATLAS event filter trigger upgrade

In the near future, the LHC experiments will continue to be upgraded as the LHC luminosity will increase from the design 1034 to 7.5 × 1034, with the HL-LHC project, to reach 3000 × f b−1 of accumulated statistics. After the end of a period of data collection, CERN will face a long shutdown to improve overall performance by upgrading the experiments and implementing more advanced technologies and infrastructures. In particular, ATLAS will upgrade parts of the detector, the trigger, and the data acquisition system. It will also implement new strategies and algorithms for processing and transferring the data to the final storage. This PhD thesis presents a study of a new pattern recognition algorithm to be used in the trigger system, which is a software designed to provide the information necessary to select physical events from background data. The idea is to use the well-known Hough Transform mathematical formula as an algorithm for detecting particle trajectories. The effectiveness of the algorithm has already been validated in the past, independently of particle physics applications, to detect generic shapes in images. Here, a software emulation tool is proposed for the hardware implementation of the Hough Transform, to reconstruct the tracks in the ATLAS Trigger and Data Acquisition system. Until now, it has never been implemented on electronics in particle physics experiments, and as a hardware implementation it would provide overall latency benefits. A comparison between the simulated data and the physical system was performed on a Xilinx UltraScale+ FPGA device.

Exact and heuristic algorithms for the integrated planning of multi-energy systems

The aim of this thesis is to present exact and heuristic algorithms for the integrated planning of multi-energy systems. The idea is to disaggregate the energy system, starting first with its core the Central Energy System, and then to proceed towards the Decentral part. Therefore, a mathematical model for the generation expansion operations to optimize the performance of a Central Energy System system is first proposed. To ensure that the proposed generation operations are compatible with the network, some extensions of the existing network are considered as well. All these decisions are evaluated both from an economic viewpoint and from an environmental perspective, as specific constraints related to greenhouse gases emissions are imposed in the formulation. Then, the thesis presents an optimization model for solar organic Rankine cycle in the context of transactive energy trading. In this study, the impact that this technology can have on the peer-to-peer trading application in renewable based community microgrids is inspected. Here the consumer becomes a prosumer and engages actively in virtual trading with other prosumers at the distribution system level. Moreover, there is an investigation of how different technological parameters of the solar Organic Rankine Cycle may affect the final solution. Finally, the thesis introduces a tactical optimization model for the maintenance operations’ scheduling phase of a Combined Heat and Power plant. Specifically, two types of cleaning operations are considered, i.e., online cleaning and offline cleaning. Furthermore, a piecewise linear representation of the electric efficiency variation curve is included. Given the challenge of solving the tactical management model, a heuristic algorithm is proposed. The heuristic works by solving the daily operational production scheduling problem, based on the final consumer’s demand and on the electricity prices. The aggregate information from the operational problem is used to derive maintenance decisions at a tactical level.

The interplay of multiplicity and effective energy for (multi) strange hadron production in pp collisions at the LHC

The enhanced production of strange hadrons in heavy-ion collisions relative to that in minimum-bias pp collisions is historically considered one of the first signatures of the formation of a deconfined quark-gluon plasma. At the LHC, the ALICE experiment observed that the ratio of strange to non-strange hadron yields increases with the charged-particle multiplicity at midrapidity, starting from pp collisions and evolving smoothly across interaction systems and energies, ultimately reaching Pb-Pb collisions. The understanding of the origin of this effect in small systems remains an open question. This thesis presents a comprehensive study of the production of $K^{0}_{S}$, $\Lambda$ ($\bar{\Lambda}$) and $\Xi^{-}$ ($\bar{\Xi}^{+}$) strange hadrons in pp collisions at $\sqrt{s}$ = 13 TeV collected in LHC Run 2 with ALICE. A novel approach is exploited, introducing, for the first time, the concept of effective energy in the study of strangeness production in hadronic collisions at the LHC. In this work, the ALICE Zero Degree Calorimeters are used to measure the energy carried by forward emitted baryons in pp collisions, which reduces the effective energy available for particle production with respect to the nominal centre-of-mass energy. The results presented in this thesis provide new insights into the interplay, for strangeness production, between the initial stages of the collision and the produced final hadronic state. Finally, the first Run 3 results on the production of $\Omega^{\pm}$ ($\bar{\Omega}^{+}$) multi-strange baryons are presented, measured in pp collisions at $\sqrt{s}$ = 13.6 TeV and 900 GeV, the highest and lowest collision energies reached so far at the LHC. This thesis also presents the development and validation of the ALICE Time-Of-Flight (TOF) data quality monitoring system for LHC Run 3. This work was fundamental to assess the performance of the TOF detector during the commissioning phase, in the Long Shutdown 2, and during the data taking period.

Intermediate linguistic task fine-tuning on Multi-lingual models

State-of-the-art NLP systems are generally based on the assumption that the underlying models are provided with vast datasets to train on. However, especially when working in multi-lingual contexts, datasets are often scarce, thus more research should be carried out in this field. This thesis investigates the benefits of introducing an additional training step when fine-tuning NLP models, named Intermediate Training, which could be exploited to augment the data used for the training phase. The Intermediate Training step is applied by training models on NLP tasks that are not strictly related to the target task, aiming to verify if the models are able to leverage the learned knowledge of such tasks. Furthermore, in order to better analyze the synergies between different categories of NLP tasks, experimentations have been extended also to Multi-Task Training, in which the model is trained on multiple tasks at the same time.

Power sharing e controllo modulare di macchine elettriche multi-trifase

La costante ricerca e lo sviluppo nel campo degli azionamenti e dei motori elettrici hanno portato ad una loro sempre maggiore applicazione ed utilizzo. Tuttavia, la crescente esigenza di sistemi ad alta potenza sempre più performanti da una parte ha evidenziato i limiti di certe soluzioni, dall’altra l’affermarsi di altre. In questi sistemi, infatti, la macchina elettrica trifase non rappresenta più l’unica soluzione possibile: negli ultimi anni si è assistito ad una sempre maggiore diffusione di macchine elettriche multifase. Grazie alle maggiori potenzialità che sono in grado di offrire, per quanto alcune di queste siano ancora sconosciute, risultano già essere una valida alternativa rispetto alla tradizionale controparte trifase. Sicuramente però, fra le varie architetture multifase, quelle multi-trifase (ovvero quelle con un numero di fasi multiplo di tre) rappresentano una soluzione particolarmente vantaggiosa in ambito industriale. Infatti, se impiegate all’interno di architetture multifase, la profonda conoscenza dei tradizionali sistemi trifase consente di ridurre i costi ed i tempi legati alla loro progettazione. In questo elaborato la macchina elettrica multi-trifase analizzata è una macchina sincrona esafase con rotore a magneti permanenti superficiali. Questa particolare tipologia di macchina elettrica può essere modellizzata attraverso due approcci completamente differenti: uno esafase ed uno doppio trifase. Queste possibilità hanno portato molti ricercatori alla ricerca della migliore strategia di controllo per questa macchina. L’obiettivo di questa tesi è di effettuare un’analisi comparativa tra tre diverse strategie di controllo applicate alla stessa macchina elettrica multi-trifase, analizzandone la risposta dinamica in diverse condizioni di funzionamento.

Analysis, Design, and Hardware-in-the-Loop Validation of Multi-Active Bridge Converters

This master's thesis investigates different aspects of Dual-Active-Bridge (DAB) Converter and extends aspects further to Multi-Active-Bridges (MAB). The thesis starts with an overview of the applications of the DAB and MAB and their importance. The analytical part of the thesis includes the derivation of the peak and RMS currents, which is required for finding the losses present in the system. The power converters, considered in this thesis are DAB, Triple-Active Bridge (TAB) and Quad-Active Bridge (QAB). All the theoretical calculations are compared with the simulation results from PLECS software for identifying the correctness of the reviewed and developed theory. The Hardware-in-the-Loop (HIL) simulation is conducted for checking the control operation in real-time with the help of the RT box from the Plexim. Additionally, as in real systems digital signal processor (DSP), system-on-chip or field programmable gate array is employed for the control of the power electronic systems, and the execution of the control in the real-time simulation (RTS) conducted is performed by DSP.