Chemical Production and Microelectronic Applications of Graphene and Nano-Graphene Derivatives

Graphene and graphenic derivatives have rapidly emerged as an extremely promising system for electronic, optical, thermal, and electromechanical applications. Several approaches have been developed to produce these materials (i.e. scotch tape, CVD, chemical and solvent exfoliation). In this work we report a chemical approach to produce graphene by reducing graphene oxide (GO) via thermal or electrical methods. A morphological and electrical characterization of these systems has been performed using different techniques such as SPM, SEM, TEM, Raman and XPS. Moreover, we studied the interaction between graphene derivates and organic molecules focusing on the following aspects: - improvement of optical contrast of graphene on different substrates for rapid monolayer identification1 - supramolecular interaction with organic molecules (i.e. thiophene, pyrene etc.)4 - covalent functionalization with optically active molecules2 - preparation and characterization of organic/graphene Field Effect Transistors3-5 Graphene chemistry can potentially allow seamless integration of graphene technology in organic electronics devices to improve device performance and develop new applications for graphene-based materials. [1] E. Treossi, M. Melucci, A. Liscio, M. Gazzano, P. Samorì, and V. Palermo, J. Am. Chem. Soc., 2009, 131, 15576. [2] M. Melucci, E. Treossi, L. Ortolani, G. Giambastiani, V. Morandi, P. Klar, C. Casiraghi, P. Samorì, and V. Palermo, J. Mater. Chem., 2010, 20, 9052. [3] J.M. Mativetsky, E. Treossi, E. Orgiu, M. Melucci, G.P. Veronese, P. Samorì, and V. Palermo, J. Am. Chem. Soc., 2010, 132, 14130. [4] A. Liscio, G.P. Veronese, E. Treossi, F. Suriano, F. Rossella, V. Bellani, R. Rizzoli, P. Samorì and V. Palermo, J. Mater. Chem., 2011, 21, 2924. [5] J.M. Mativetsky, A. Liscio, E. Treossi, E. Orgiu, A. Zanelli, P. Samorì , V. Palermo, J. Am. Chem. Soc., 2011, 133, 14320

New Metal Tetrazolate Complexes: Design, Synthesis, Characterization and Applications

This final thesis is aimed at summarizing the research program I have carried out during my PhD studies, that has been dealing with the design, the preparation, characterization and applications of new Re(I), Ru(II), and Ir(III) metal complexes containing anionic ligands such as 5-aryl tetrazolates [R-CN4]- or their neutral analogues, N-alkyltetrazoles [R-CN4-R1]. Chapter 1 consists of a brief introduction on tetrazoles and metal-tetrazolato complexes, and on the photophysical properties of d6 transition metal complexes. In chapter 2, the synthesis, characterization and study of the photophysical properties of new luminescent Ir(III)-tetrazolate complexes are discussed. Moreover, the application of one of the new Ir(III)-CN complexes as emissive core in the fabrication of an OLED device is reported. In chapter 3, the study of the antimicrobial activity of new Ru(II)-alkyltetrazole complexes is reported. When the pentatomic ring was substituted with a long alkyl residue, antimicrobial activity toward Deinococcus radiodurans was observed. In chapter 4, a new family of luminescent Re(I)-tetrazolate complexes is reported. In this study, different N-alkyl tetrazoles play the role of diimine (diim) ligands in the preparation of new Re(I) tricarbonyl complexes. In addition, absorption and emission titration experiments were performed to study their interaction with Bovine Serum Albumin (BSA). In chapter 5, the synthesis and characterization of new luminescent Re(I)-tetrazolate complexes are discussed. The use of sulfonated diimine ligands in the preparation of new Re(I) tricarbonyl complexes led to the first example Re(I) complexes for the luminescent staining of proteins. In chapter 6, the synthesis, a new family of Ir(III)-NO2 tetrazole complexes displaying unexpected photophysical properties are discussed. Moreover, the possibility to tune the luminescent output of such systems upon chemical modification of the pending nitro group was verified by performing reduction tests with sodium dithionite; this represents encouraging evidence for their possible application as hypoxia-responsive luminescent probes in bioimaging.

Novel hydroxystearoyl-, heterocyclic and carbocyclic derivatives: synthesis and applications in biological field

This PhD project has been mainly focused on the synthesis of novel organic compounds containing heterocyclic and/or carbocyclic scaffold and on the study of stearic acid derivatives and their applications in biological field. The synthesis of novel derivatives of 9-hydroxystearic acid (9-HSA) evidenced how the presence of substituents on C9, able to make hydrogen bonds is of crucial importance for the biological activity. Also the position of the hydroxy group along the chain of hydroxystearic acids was investigated: regioisomers with the hydroxy group bound to odd carbons resulted more active than those bearing the hydroxy group on even carbons. Further, the insertion of (R)-9-HSA in magnetic nanoparticles gave a novel material which characterization remarked its suitability for drug delivery. Structural hybrids between amino aza-heterocycles and azelaic acid have been synthesized and some of them showed a selective activity towards osteosarcoma cell line U2OS. Several Apcin analogues bearing indole, benzothiazole, benzofurazan moieties connected to tryptaminyl-, amino pyridinyl-, pyrimidinyl- and pyrazinyl ring through a 1,1,1-trichloroethyl group were synthesized. Biological tests showed the importance of both the tryptaminyl and the pyrimidinyl moieties, confirming the effectiveness against acute leukemia models. The SNAr between 2-aminothiazole derivatives and 7-chlorodinitrobenzofuroxan revealed different behaviour depending from amino substituent of the thiazole. The reaction with 2-N-piperidinyl-, 2-N-morpholinyl-, or 2-N-pyrrolidinyl thiazole gave two isomeric species derived from the attack on C-5 of thiazole ring. Thiazoles substituted with primary- or not-cyclic secondary amines reacted with the exocyclic amino nitrogen atom giving a series of compounds whose biological activity have highlighted as they might be promising candidates for further development of antitumor agents. A series of 9-fluorenylidene derivatives, of interest in medical and optoelectronic field as organic scintillators, was synthesized through Wittig or Suzuky reaction and will be analyzed to test their potential scintillatory properties.

R-loops and G4-structures: from DNA damage to innate immune response gene activation

Non-B DNA structures like R-loops and G-quadruplexes play a pivotal role in several cellular vital processes like DNA transcription regulation. Misregulation of said non-canonical DNA structures can often lead to genome instability, DNA damage, and, eventually, to the activation of an innate immune response. For such reasons they have been studied as adjuvants in anticancer therapies. Here we studied drugs targeting R-loops (Top1 poisons) and G4s (hydrazone derivatives) in order to observe their effects in terms of DNA damage induction and, subsequently, activation of innate immune response. We studied how non-cytotoxic doses of ampthotecin and LMP-776 impact on genome instability, are capable to induce DNA damage and micronuclei, and, eventually lead to an innate immune gene response via the cGAS/STING pathway. G-quadruplexes are another ubiquitous, non-canonical DNA structure, more abundant in telomeric regions, demonstrating a marked relation with the impairment of telomerase and the regulation of DNA replication and transcription. Furthermore, we investigated the properties of new-synthesized molecules belonging to the highly promising class of hydrazone derivatives, in terms of cytotoxicity, ability to stabilize G4-structures, induce DNA damage, and activate interferon-B production. Both Top1 poisons and G4-stabilizers possess several features that can be very useful in clinical applications, in light of their ability to stimulate innate immune response factors and exert a certain cell-killing power, plus they offer a broad and diverse range of treatment options in order to face a variety of patient treatment needs. It is for these very reasons that it is of uttermost importance that further studies are conducted on these compounds, in order to synthesize new and increasingly powerful and flexible ones, with fewer side effects to customize therapies on specific cancers’ and patients’ features.

Development of unsupervised learning methods with applications to life sciences data

Machine Learning makes computers capable of performing tasks typically requiring human intelligence. A domain where it is having a considerable impact is the life sciences, allowing to devise new biological analysis protocols, develop patients’ treatments efficiently and faster, and reduce healthcare costs. This Thesis work presents new Machine Learning methods and pipelines for the life sciences focusing on the unsupervised field. At a methodological level, two methods are presented. The first is an “Ab Initio Local Principal Path” and it is a revised and improved version of a pre-existing algorithm in the manifold learning realm. The second contribution is an improvement over the Import Vector Domain Description (one-class learning) through the Kullback-Leibler divergence. It hybridizes kernel methods to Deep Learning obtaining a scalable solution, an improved probabilistic model, and state-of-the-art performances. Both methods are tested through several experiments, with a central focus on their relevance in life sciences. Results show that they improve the performances achieved by their previous versions. At the applicative level, two pipelines are presented. The first one is for the analysis of RNA-Seq datasets, both transcriptomic and single-cell data, and is aimed at identifying genes that may be involved in biological processes (e.g., the transition of tissues from normal to cancer). In this project, an R package is released on CRAN to make the pipeline accessible to the bioinformatic Community through high-level APIs. The second pipeline is in the drug discovery domain and is useful for identifying druggable pockets, namely regions of a protein with a high probability of accepting a small molecule (a drug). Both these pipelines achieve remarkable results. Lastly, a detour application is developed to identify the strengths/limitations of the “Principal Path” algorithm by analyzing Convolutional Neural Networks induced vector spaces. This application is conducted in the music and visual arts domains.