Investigation of heterogeneous catalysts for the synthesis of fine chemicals

In order to match the more stringent environmental regulations, heterogenization of traditional homogeneous processes is one of the main challenges of the modern chemical industry. Great results have been achieved in the fields of petrochemicals and base chemicals, whereas in fine chemical industry most of the synthetic procedures are based on multistep processes catalyzed by homogeneous catalysts mainly used in stoichiometric amounts. In the fine chemicals manufacture not so much efforts have been devoted to the investigation of suitable solid catalysts for the development of greener processes, then this sector represent a very attractive field of research. In this context, the present work deals with the extensive investigation of the possibility to heterogenize existing processes, in particular two different classes of reactions have been studied: alkylation of aromatic and heteroaromatic compounds and selective oxidation of aromatic alcohols. Traditional solid acid catalysts, such as zeolites, clays and alumina have been tested in the gas phase alkylation of 1,2-methylendioxybenzene, core building block of many drugs, pesticides and fragrances. The observed reactivity were clarified through a deep FTIR investigation complemented by ab initio calculation. The same catalysts were tested in the gas phase isopropylation of thiophene with the aim of clearly attribute the role of the reaction parameters in the reaction proceeding and verify the possibility to enhance the selectivity of one of the two possible isomers. Finally various Au/CeO2 catalysts were tested in the synthesis of benzaldehyde and piperonal, two aldehydes largely employed in the manufacture of fine chemical products, through liquid phase oxidation of the corresponding alcohols in very mild conditions.

Photoactive Carbon Nanostructures: From Multicomponent Arrays To Nanomaterials

Carbon has a unique ability to shape networks of differently hybridized atoms that can generate various allotropes and may also exist as nanoscale materials. The emergence of carbon nanostructures initially occured through the serendipitous discovery of fullerenes and then through experimental advances which led to carbon nanotubes, nanohorns and graphene. The structural diversity of carbon nanoscopic allotropes and their unique and unprecedentend properties, give rise to countless applications and have been intensively exploited in nanotechnology, since they may address the need to create smarter optoelectronic devices, smaller in size and with better performance. The versatile properties of carbon nanomaterials are reflected in the multidisciplinary character of my doctoral research where, in particular, I take advantage of the opportunities offered by fullerenes and carbon nanotubes in constructing novel functional materials. In this work, carbon nanostructures are incorporated in novel photoactive functional systems constructed through different types of interactions – covalent bonds, ion-pairing or self-assembly. The variety of properties exhibited by carbon nanostructures is successfully explored by assigning them a different role in a specific array: fullerenes are employed as electron or energy acceptors, whereas carbon nanotubes behave like optically inert scaffolds for luminescent materials or nanoscale substrates in sonication-induced self-assembly. All the presented systems serve as a testbed for exploring the properties of carbon nanostructures in multicomponent arrays, which may be advantageous for the production of new photovoltaic or optoelectronic devices, as well as in the design and control of self-assembly processes.

Sustainable processes using heterogeneous acid catalysts. Some examples of industrial interest.

In recent years the need for the design of more sustainable processes and the development of alternative reaction routes to reduce the environmental impact of the chemical industry has gained vital importance. Main objectives especially regard the use of renewable raw materials, the exploitation of alternative energy sources, the design of inherently safe processes and of integrated reaction/separation technologies (e.g. microreactors and membranes), the process intensification, the reduction of waste and the development of new catalytic pathways. The present PhD thesis reports results derived during a three years research period at the School of Chemical Sciences of Alma Mater Studiorum-University of Bologna, Dept. of Industrial Chemistry and Materials (now Dept. of Industrial Chemistry “Toso Montanari”), under the supervision of Prof. Fabrizio Cavani (Catalytic Processes Development Group). Three research projects in the field of heterogeneous acid catalysis focused on potential industrial applications were carried out. The main project, regarding the conversion of lignocellulosic materials to produce monosaccharides (important intermediates for production of biofuels and bioplatform molecules) was financed and carried out in collaboration with the Italian oil company eni S.p.A. (Istituto eni Donegani-Research Center for non-Conventional Energies, Novara, Italy) The second and third academic projects dealt with the development of green chemical processes for fine chemicals manufacturing. In particular, (a) the condensation reaction between acetone and ammonia to give triacetoneamine (TAA), and (b) the Friedel-Crafts acylation of phenol with benzoic acid were investigated.

Temperature Variation Aware Energy Optimization in Heterogeneous MPSoCs

Thermal effects are rapidly gaining importance in nanometer heterogeneous integrated systems. Increased power density, coupled with spatio-temporal variability of chip workload, cause lateral and vertical temperature non-uniformities (variations) in the chip structure. The assumption of an uniform temperature for a large circuit leads to inaccurate determination of key design parameters. To improve design quality, we need precise estimation of temperature at detailed spatial resolution which is very computationally intensive. Consequently, thermal analysis of the designs needs to be done at multiple levels of granularity. To further investigate the flow of chip/package thermal analysis we exploit the Intel Single Chip Cloud Computer (SCC) and propose a methodology for calibration of SCC on-die temperature sensors. We also develop an infrastructure for online monitoring of SCC temperature sensor readings and SCC power consumption. Having the thermal simulation tool in hand, we propose MiMAPT, an approach for analyzing delay, power and temperature in digital integrated circuits. MiMAPT integrates seamlessly into industrial Front-end and Back-end chip design flows. It accounts for temperature non-uniformities and self-heating while performing analysis. Furthermore, we extend the temperature variation aware analysis of designs to 3D MPSoCs with Wide-I/O DRAM. We improve the DRAM refresh power by considering the lateral and vertical temperature variations in the 3D structure and adapting the per-DRAM-bank refresh period accordingly. We develop an advanced virtual platform which models the performance, power, and thermal behavior of a 3D-integrated MPSoC with Wide-I/O DRAMs in detail. Moving towards real-world multi-core heterogeneous SoC designs, a reconfigurable heterogeneous platform (ZYNQ) is exploited to further study the performance and energy efficiency of various CPU-accelerator data sharing methods in heterogeneous hardware architectures. A complete hardware accelerator featuring clusters of OpenRISC CPUs, with dynamic address remapping capability is built and verified on a real hardware.

Heterogeneous Multi-core Architectures for High Performance Computing

This thesis deals with heterogeneous architectures in standard workstations. Heterogeneous architectures represent an appealing alternative to traditional supercomputers because they are based on commodity components fabricated in large quantities. Hence their price-performance ratio is unparalleled in the world of high performance computing (HPC). In particular, different aspects related to the performance and consumption of heterogeneous architectures have been explored. The thesis initially focuses on an efficient implementation of a parallel application, where the execution time is dominated by an high number of floating point instructions. Then the thesis touches the central problem of efficient management of power peaks in heterogeneous computing systems. Finally it discusses a memory-bounded problem, where the execution time is dominated by the memory latency. Specifically, the following main contributions have been carried out: A novel framework for the design and analysis of solar field for Central Receiver Systems (CRS) has been developed. The implementation based on desktop workstation equipped with multiple Graphics Processing Units (GPUs) is motivated by the need to have an accurate and fast simulation environment for studying mirror imperfection and non-planar geometries. Secondly, a power-aware scheduling algorithm on heterogeneous CPU-GPU architectures, based on an efficient distribution of the computing workload to the resources, has been realized. The scheduler manages the resources of several computing nodes with a view to reducing the peak power. The two main contributions of this work follow: the approach reduces the supply cost due to high peak power whilst having negligible impact on the parallelism of computational nodes. from another point of view the developed model allows designer to increase the number of cores without increasing the capacity of the power supply unit. Finally, an implementation for efficient graph exploration on reconfigurable architectures is presented. The purpose is to accelerate graph exploration, reducing the number of random memory accesses.

Integration of heterogeneous data sources and automated reasoning in healthcare and domotic IoT systems

In recent years, IoT technology has radically transformed many crucial industrial and service sectors such as healthcare. The multi-facets heterogeneity of the devices and the collected information provides important opportunities to develop innovative systems and services. However, the ubiquitous presence of data silos and the poor semantic interoperability in the IoT landscape constitute a significant obstacle in the pursuit of this goal. Moreover, achieving actionable knowledge from the collected data requires IoT information sources to be analysed using appropriate artificial intelligence techniques such as automated reasoning. In this thesis work, Semantic Web technologies have been investigated as an approach to address both the data integration and reasoning aspect in modern IoT systems. In particular, the contributions presented in this thesis are the following: (1) the IoT Fitness Ontology, an OWL ontology that has been developed in order to overcome the issue of data silos and enable semantic interoperability in the IoT fitness domain; (2) a Linked Open Data web portal for collecting and sharing IoT health datasets with the research community; (3) a novel methodology for embedding knowledge in rule-defined IoT smart home scenarios; and (4) a knowledge-based IoT home automation system that supports a seamless integration of heterogeneous devices and data sources.

Serverless middlewares to integrate heterogeneous and distributed services in cloud continuum environments

The application of modern ICT technologies is radically changing many fields pushing toward more open and dynamic value chains fostering the cooperation and integration of many connected partners, sensors, and devices. As a valuable example, the emerging Smart Tourism field derived from the application of ICT to Tourism so to create richer and more integrated experiences, making them more accessible and sustainable. From a technological viewpoint, a recurring challenge in these decentralized environments is the integration of heterogeneous services and data spanning multiple administrative domains, each possibly applying different security/privacy policies, device and process control mechanisms, service access, and provisioning schemes, etc. The distribution and heterogeneity of those sources exacerbate the complexity in the development of integrating solutions with consequent high effort and costs for partners seeking them. Taking a step towards addressing these issues, we propose APERTO, a decentralized and distributed architecture that aims at facilitating the blending of data and services. At its core, APERTO relies on APERTO FaaS, a Serverless platform allowing fast prototyping of the business logic, lowering the barrier of entry and development costs to newcomers, (zero) fine-grained scaling of resources servicing end-users, and reduced management overhead. APERTO FaaS infrastructure is based on asynchronous and transparent communications between the components of the architecture, allowing the development of optimized solutions that exploit the peculiarities of distributed and heterogeneous environments. In particular, APERTO addresses the provisioning of scalable and cost-efficient mechanisms targeting: i) function composition allowing the definition of complex workloads from simple, ready-to-use functions, enabling smarter management of complex tasks and improved multiplexing capabilities; ii) the creation of end-to-end differentiated QoS slices minimizing interfaces among application/service running on a shared infrastructure; i) an abstraction providing uniform and optimized access to heterogeneous data sources, iv) a decentralized approach for the verification of access rights to resources.

Protein-based nanomaterials as protein heterogeneous nucleants and structural studies on enzymes from two photosynthetic organisms

Proteins, the most essential biological macromolecules, are involved in nearly every aspect of life. The elucidation of their three-dimensional structures through X-ray analysis has significantly contributed to our understanding of fundamental mechanisms in life processes. However, the obstacle of obtaining high-resolution protein crystals remains significant. Thus, searching for materials that can effectively induce nucleation of crystals is a promising and active field. This thesis work characterizes and prepares albumin nanoparticles as heterogeneous nucleants for protein crystallization. These stable Bovine Serum Albumin nanoparticles were synthesized via the desolvation method, purified efficiently, and characterized in terms of dimension, morphology, and secondary structure. The ability of BSA-NPs to induce macromolecule nucleation was tested on three model proteins, exhibiting significant results, with larger NPs inducing more nucleation. The second part of this work focuses on the structural study, mainly through X-ray crystallography, of five chloroplast and cytosolic enzymes involved in the fundamental cellular processes of two photosynthetic organisms, Chlamydomonas reinhardtii and Arabidopsis thaliana. The structures of three enzymes involved in the Calvin-Benson-Bassham Cycle, phosphoribulokinase, troseposphatisomerase, and ribulosiophosphate epimerase from Chlamydomonas reinhardtii, were solved to investigate their catalytic and regulatory mechanisms. Additionally, the structure of nitrosylated-CrTPI made it possible to identify Cys14 as a target for nitrosylation, and the crystallographic structure of CrRPE was solved for the first time, providing insights into its catalytic and regulatory properties. Finally, the structure of S-nitrosoglutathione reductase, AtGSNOR, was compared with that of AtADH1, revealing differences in their catalytic sites. Overall, seven crystallographic structures, including partially oxidized CrPRK, CrPRK/ATP, CrPRK/ADP/Ru5P, CrTPI-nitrosylated, apo-CrRPE, apo-AtGSNOR, and AtADH1-NADH, were solved and are yet to be deposited in the PDB.

Electrochemistry of polycyclic aromatic molecules for advanced carbon nanostructures: luminescence and transistor applications

Polycyclic aromatic hydrocarbons (PAHs) are a large class of π-conjugated organic molecules with fused aromatic rings, which can be considered as fragments of 2D-graphene and have been extensively studied for their unique optical and electronic properties. The aim of this study is to understand the complex electrochemical behaviour of planar, curved, and heteroatom doped polycyclic aromatic molecules, particularly focusing on the oxidative coupling of their radical cations and the electrochemically induced cyclodehydrogenation reactions. In the first part of this thesis, the class of PAHs and aromatic nanostructures are introduced, and the reactivity of electrogenerated species is discussed, focusing on the electrochemical approach for the synthesis of extended π-conjugated structures. Subsequently, the electrochemical properties and reactivity of electrogenerated radical ions of planar and curved polyaromatics are correlated to their structures. In the third chapter, electrochemical cyclodehydrogenation of hexaphenylbenzene is used to prepare self-assembled hexabenzocoronene, directly deposited on an interdigitated electrode, which was characterised as organic electrochemical transistor. In the fourth chapter, the electrochemical behaviour of a family of azapyrene derivatives has been carefully investigated together with the electrogenerated chemiluminescence (ECL), both by ion-annihilation and co-reactant methods. Two structural azapyrene isomers with different nitrogen positions are thoroughly discussed in terms of redox and ECL properties. Interestingly, the ECL of only one of them showed a double emission with excimer formation. A detailed mechanism is discussed for the ECL by co-reactant benzoyl peroxide, to rationalise the different ECL behaviours of the two isomers on the basis of their topologically modulated electronic properties. In conclusion, the different electrochemical behaviours of PAHs were shown, focussing on the chemical reactivity of the electrogenerated species and taking advantage of it for important processes spanning from unconventional synthesis methods for carbon nanostructures to the exploitation of self-assembled nanostructured systems in organic electronics, to novel organic emitters in ECL.

Addressing challenges in heterogeneous embedded systems programming: security and performance

Embedded systems are increasingly integral to daily life, improving and facilitating the efficiency of modern Cyber-Physical Systems which provide access to sensor data, and actuators. As modern architectures become increasingly complex and heterogeneous, their optimization becomes a challenging task. Additionally, ensuring platform security is important to avoid harm to individuals and assets. This study primarily addresses challenges in contemporary Embedded Systems, focusing on platform optimization and security enforcement. The initial section of this study delves into the application of machine learning methods to efficiently determine the optimal number of cores for a parallel RISC-V cluster to minimize energy consumption using static source code analysis. Results demonstrate that automated platform configuration is not only viable but also that there is a moderate performance trade-off when relying solely on static features. The second part focuses on addressing the problem of heterogeneous device mapping, which involves assigning tasks to the most suitable computational device in a heterogeneous platform for optimal runtime. The contribution of this section lies in the introduction of novel pre-processing techniques, along with a training framework called Siamese Networks, that enhances the classification performance of DeepLLVM, an advanced approach for task mapping. Importantly, these proposed approaches are independent from the specific deep-learning model used. Finally, this research work focuses on addressing issues concerning the binary exploitation of software running in modern Embedded Systems. It proposes an architecture to implement Control-Flow Integrity in embedded platforms with a Root-of-Trust, aiming to enhance security guarantees with limited hardware modifications. The approach involves enhancing the architecture of a modern RISC-V platform for autonomous vehicles by implementing a side-channel communication mechanism that relays control-flow changes executed by the process running on the host core to the Root-of-Trust. This approach has limited impact on performance and it is effective in enhancing the security of embedded platforms.

Development of molecular-level switches and implementation into novel nanostructures and smart materials

The work presented in this thesis deals with the design, synthesis and investigation of (supra)molecular switches, and their implementation into novel nanostructures and smart devices. Part A deals with investigation of fundamental properties of Donor Acceptor Stenhouse Adducts (DASAs) as well as their implementation into polymer matrices in order to construct novel smart materials. Part B deals with the implementation of azobenzene photoswitches into pseudorotaxanes and the investigation of the effect of light-driven isomerization on the self-assembly and disassembly processes.

Investigation on the role of polymeric ligands in heterogeneous nanocatalysis towards the development of hybrid metal-polymer catalysts

The relationship between catalytic properties and the nature of the active phase is well-established, with increased presence typically leading to enhanced catalysis. However, the costs associated with acquiring and processing these metals can become economically and environmentally unsustainable for global industries. Thus, there is potential for a paradigm shift towards utilizing polymeric ligands or other polymeric systems to modulate and enhance catalytic performance. This alternative approach has the potential to reduce the requisite amount of active phase while preserving effective catalytic activity. Such a strategy could yield substantial benefits from both economic and environmental perspectives. The primary objective of this research is to examine the influence of polymeric hydro-soluble ligands on the final properties, such as size and dispersion of the active phase, as well as the catalytic activity, encompassing conversion, selectivity towards desired products, and stability, of colloidal gold nanoparticles supported on active carbon. The goal is to elucidate the impact of polymers systematically, offering a toolbox for fine-tuning catalytic performances from the initial stages of catalyst design. Moreover, investigating the potential to augment conversion and selectivity in specific reactions through tailored polymeric ligands holds promise for reshaping catalyst preparation methodologies, thereby fostering the development of more economically sustainable materials.