Silica-Supported Gold Nanoparticles: Synthesis, Characterization and Reactivity

The main aim of this work was the synthesis and applications of functionalized-silica-supported gold nanoparticles. The silica-anchored functionalities employed, e.g. amine, alkynyl carbamate and sulfide moieties, possess a notable affinity with gold, so that they could be able to capture the gold precursor, to spontaneously reduce it (possibly at room temperature), and to stabilize the resulting gold nanoparticles. These new materials, potentially suitable for heterogeneous catalysis applications, could represent a breakthrough among the “green” synthesis of supported gold nanoparticles, since they would circumvent the addition of extra reducing agent and stabilizers, also allowing concomitant absorption of the active catalyst particles on the support immediately after spontaneous formation of gold nanoparticles. In chapter 4 of this thesis is also presented the work developed during a seven-months Marco Polo fellowship stay at the University of Lille (France), regarding nanoparticles nucleation and growth inside a microfluidic system and the study of the corresponding mechanism by in situ XANES spectroscopy. Finally, studies regarding the reparation and reactivity of gold decorated nanodiamonds are also described. Various methods of characterization have been used, such as ultraviolet-visible spectroscopy (UV-Vis), Transmission Electron Microscopy (TEM), Dynamic Light Scattering (DLS), X-ray Fluorescence (XRF), Field Emission Gun Scanning Electron Microscopy (SEM-FEG), X-ray Photoionization (XPS), X ray Absorption Spectroscopy (XAS).

Supporting Scientific Research Through Machine and Deep Learning: Fluorescence Microscopy and Operational Intelligence Use Cases

Although the debate of what data science is has a long history and has not reached a complete consensus yet, Data Science can be summarized as the process of learning from data. Guided by the above vision, this thesis presents two independent data science projects developed in the scope of multidisciplinary applied research. The first part analyzes fluorescence microscopy images typically produced in life science experiments, where the objective is to count how many marked neuronal cells are present in each image. Aiming to automate the task for supporting research in the area, we propose a neural network architecture tuned specifically for this use case, cell ResUnet (c-ResUnet), and discuss the impact of alternative training strategies in overcoming particular challenges of our data. The approach provides good results in terms of both detection and counting, showing performance comparable to the interpretation of human operators. As a meaningful addition, we release the pre-trained model and the Fluorescent Neuronal Cells dataset collecting pixel-level annotations of where neuronal cells are located. In this way, we hope to help future research in the area and foster innovative methodologies for tackling similar problems. The second part deals with the problem of distributed data management in the context of LHC experiments, with a focus on supporting ATLAS operations concerning data transfer failures. In particular, we analyze error messages produced by failed transfers and propose a Machine Learning pipeline that leverages the word2vec language model and K-means clustering. This provides groups of similar errors that are presented to human operators as suggestions of potential issues to investigate. The approach is demonstrated on one full day of data, showing promising ability in understanding the message content and providing meaningful groupings, in line with previously reported incidents by human operators.

Effective field theories and their phenomenological applications

Effective field theories (EFTs) are ubiquitous in theoretical physics and in particular in field theory descriptions of quantum systems probed at energies much lower than one or few characterizing scales. More recently, EFTs have gained a prominent role in the study of fundamental interactions and in particular in the parametriasation of new physics beyond the Standard Model, which would occur at scales Λ, much larger than the electroweak scale. In this thesis, EFTs are employed to study three different physics cases. First, we consider light-by-light scattering as a possible probe of new physics. At low energies it can be described by dimension-8 operators, leading to the well-known Euler-Heisenberg Lagrangian. We consider the explicit dependence of matching coefficients on type of particle running in the loop, confirming the sensitiveness to the spin, mass, and interactions of possibly new particles. Second, we consider EFTs to describe Dark Matter (DM) interactions with SM particles. We consider a phenomenologically motivated case, i.e., a new fermion state that couples to the Hypercharge through a form factor and has no interactions with photons and the Z boson. Results from direct, indirect and collider searches for DM are used to constrain the parameter space of the model. Third, we consider EFTs that describe axion-like particles (ALPs), whose phenomenology is inspired by the Peccei-Quinn solution to strong CP problem. ALPs generically couple to ordinary matter through dimension-5 operators. In our case study, we investigate the rather unique phenomenological implications of ALPs with enhanced couplings to the top quark.

Nanomechanical characterization of soft bioelectronic interfaces via modeling-informed atomic force microscopy

The field of bioelectronics involves the use of electrodes to exchange electrical signals with biological systems for diagnostic and therapeutic purposes in biomedical devices and healthcare applications. However, the mechanical compatibility of implantable devices with the human body has been a challenge, particularly with long-term implantation into target organs. Current rigid bioelectronics can trigger inflammatory responses and cause unstable device functions due to the mechanical mismatch with the surrounding soft tissue. Recent advances in flexible and stretchable electronics have shown promise in making bioelectronic interfaces more biocompatible. To fully achieve this goal, material science and engineering of soft electronic devices must be combined with quantitative characterization and modeling tools to understand the mechanical issues at the interface between electronic technology and biological tissue. Local mechanical characterization is crucial to understand the activation of failure mechanisms and optimizing the devices. Experimental techniques for testing mechanical properties at the nanoscale are emerging, and the Atomic Force Microscope (AFM) is a good candidate for in situ local mechanical characterization of soft bioelectronic interfaces. In this work, in situ experimental techniques with solely AFM supported by interpretive models for the characterization of planar and three-dimensional devices suitable for in vivo and in vitro biomedical experimentations are reported. The combination of the proposed models and experimental techniques provides access to the local mechanical properties of soft bioelectronic interfaces. The study investigates the nanomechanics of hard thin gold films on soft polymeric substrates (Poly(dimethylsiloxane) PDMS) and 3D inkjet-printed micropillars under different deformation states. The proposed characterization methods provide a rapid and precise determination of mechanical properties, thus giving the possibility to parametrize the microfabrication steps and investigate their impact on the final device.

Black hole scattering from Worldline Quantum Field Theory and the Classical Double Copy of Spinning particles

This PhD thesis focuses on studying the classical scattering of massive/massless particles toward black holes, and investigating double copy relations between classical observables in gauge theories and gravity. This is done in the Post-Minkowskian approximation i.e. a perturbative expansion of observables controlled by the gravitational coupling constant κ = 32πGN, with GN being the Newtonian coupling constant. The investigation is performed by using the Worldline Quantum Field Theory (WQFT), displaying a worldline path integral describing the scattering objects and a QFT path integral in the Born approximation, describing the intermediate bosons exchanged in the scattering event by the massive/massless particles. We introduce the WQFT, by deriving a relation between the Kosower- Maybee-O’Connell (KMOC) limit of amplitudes and worldline path integrals, then, we use that to study the classical Compton amplitude and higher point amplitudes. We also present a nice application of our formulation to the case of Hard Thermal Loops (HTL), by explicitly evaluating hard thermal currents in gauge theory and gravity. Next we move to the investigation of the classical double copy (CDC), which is a powerful tool to generate integrands for classical observables related to the binary inspiralling problem in General Relativity. In order to use a Bern-Carrasco-Johansson (BCJ) like prescription, straight at the classical level, one has to identify a double copy (DC) kernel, encoding the locality structure of the classical amplitude. Such kernel is evaluated by using a theory where scalar particles interacts through bi-adjoint scalars. We show here how to push forward the classical double copy so to account for spinning particles, in the framework of the WQFT. Here the quantization procedure on the worldline allows us to fully reconstruct the quantum theory on the gravitational side. Next we investigate how to describe the scattering of massless particles off black holes in the WQFT.