Molecular organization of n-cyanobiphenyl liquid crystals on a molybdenite surface

The alignement and anchoring of liquid crystals on solid surfaces is a key problem for modern device technology that until now has been treated empirically, but that can now be tackled by atomistic computer simulations. Molecular dynamics (MD) simulations were used in this thesis work to study two films of 7 and 8 n-alkyl-4’cyanobiphenyl (7CB and 8CB) liquid crystals , with a thickness of 15 nm, confined between two (001) surfaces of MoS2 (molybdenite). The isotropic and nematic phases of both liquid crystals were simulated, and the resulting structures characterized structurally. A new force field was designed to model the interactions between the liquid crystal (LC) molecules and the surface of molybdenite, while an accurate force field developed previously was used to model the 7CB and 8CB molecules. The results show that the (001) molybdenite surface induces a planar orientation in both the liquid crystals. For the nematic phase of 8CB, one of the two solid/LC interfaces is composed of a first layer of molecules aligned parallel to the surface, followed by a second layer of molecules aligned perpendicular to the surface (also called, homeotropic). The effect of the surface appears to be local in nature as it is confined to the first 15 Angström of the LC film. Conversely, for the nematic phase of 7CB, a planar ordering is established into the LC film. The LC molecules at the interface with the molybdenite appear to align preferentially their alkyl chains toward the solid substrate. The resulting tilt angle of molecules was found to be in good agreement with experimental measurements available in literature. Despite the fact that the MD simulations spanned a time range of more than 100 ns, the nematic phases of both 7CB and 8CB were found not to be completely formed. In order to confirm the findings presented in this thesis, we propose to extend the current study.

Integrali sui cammini e ordinamento di Weyl

In questa tesi viene affrontato lo studio degli integrali funzionali nella meccanica quantistica, sia come rielaborazione dell'operatore di evoluzione temporale che costruendo direttamente una somma sui cammini. Vengono inoltre messe in luce ambiguit\`a dovute alla discretizzazione dell'azione corrispondenti ai problemi di ordinamento operatoriale della formulazione canonica. Si descrive inoltre come una possibile scelta della discretizzazione dell'integrale funzionale pu\`o essere ottenuta utilizzando l'ordinamento di Weyl dell'opertore Hamiltoniano, sfruttando la relazione tra Hamiltoniana Weyl ordinata e la prescrizione del punto di mezzo da usare nella discretizzazione dell'azione classica. Studieremo in particolare il caso di una particella non relativistica interagente con un potenziale scalare, un potenziale vettore (campo magnetico) ed un potenziale tensore (metrica).

Simulating the aggregation of DNA oligonucleotides

In this work we have studied, by means of Molecular Dynamics simulations, the process of denaturation and self-assembly of short oligonucleotides. Supramolecular ordering of DNA short strands is a promising field which is constantly enriched with new findings. Examples are provided by micellar and fibrils formations and due to the selectivity of DNA bindings, "intelligent" devices have been developed to perform simple logic operations. It is worth to notice that computer simulations of these DNA nanosystems would complement experiments with detailed insight into processes involved in self-assembly. In order to obtain an accurate description of the interactions involved in the complex structure of DNA we used oxDNA, a coarse-grained model developed by Ouldridge. We simulated the melting transition of 4, 6, and 8 base pair sequences. Sequence and length dependence were analyzed, specifically we compared thermodynamic parameters DeltaH, DeltaS and the melting temperature with literature results. Moreover, we have attempted to reproduce liquid crystal ordering of the ultrashort sequence GCCG at relatively high saline concentration, until now only experimentally observed in Bellini's works. We found that our simple model successfully reproduces the experimental phase sequence (isotropic, nematic, columnar) at T= 5 °C as a function of oligonucleotide concentration, and we fully characterized the microscopic structure of the three phases.

Neutrino interactions in the SAND LAr volume at the DUNE Near Detector site

The neutrino mass ordering and the leptonic CP violation phase are key parameters of the three-neutrino flavour mixing still to be determined. Measuring these parameters is the main goal of DUNE, a next generation Long Baseline neutrino experiment under construction in the United States. DUNE will feature a Near and a Far Detector site. An important component of the Near detector complex is the SAND apparatus, which will include GRAIN, a novel liquid Argon detector that aims at imaging neutrino interactions using scintillation light. For this purpose, an innovative optical readout system based on Coded Aperture Masks is under study. This thesis work is aimed at a first quantitative assessment of a 3D neutrino event reconstruction algorithm for GRAIN. The processing procedure is optimized and the reconstruction performance is evaluated. Promising results are obtained.

Motor Unit Spike Trains Recontruction from sEMG Signals for Gesture Classification on a Low-Power Processing Platform

Hand gesture recognition based on surface electromyography (sEMG) signals is a promising approach for the development of intuitive human-machine interfaces (HMIs) in domains such as robotics and prosthetics. The sEMG signal arises from the muscles' electrical activity, and can thus be used to recognize hand gestures. The decoding from sEMG signals to actual control signals is non-trivial; typically, control systems map sEMG patterns into a set of gestures using machine learning, failing to incorporate any physiological insight. This master thesis aims at developing a bio-inspired hand gesture recognition system based on neuromuscular spike extraction rather than on simple pattern recognition. The system relies on a decomposition algorithm based on independent component analysis (ICA) that decomposes the sEMG signal into its constituent motor unit spike trains, which are then forwarded to a machine learning classifier. Since ICA does not guarantee a consistent motor unit ordering across different sessions, 3 approaches are proposed: 2 ordering criteria based on firing rate and negative entropy, and a re-calibration approach that allows the decomposition model to retain information about previous sessions. Using a multilayer perceptron (MLP), the latter approach results in an accuracy up to 99.4% in a 1-subject, 1-degree of freedom scenario. Afterwards, the decomposition and classification pipeline for inference is parallelized and profiled on the PULP platform, achieving a latency < 50 ms and an energy consumption < 1 mJ. Both the classification models tested (a support vector machine and a lightweight MLP) yielded an accuracy > 92% in a 1-subject, 5-classes (4 gestures and rest) scenario. These results prove that the proposed system is suitable for real-time execution on embedded platforms and also capable of matching the accuracy of state-of-the-art approaches, while also giving some physiological insight on the neuromuscular spikes underlying the sEMG.

Calorimetric efficiency of the DUNE experiment

The Deep Underground Neutrino Experiment is a long-baseline neutrino experiment which is under construction in the United States. It will be composed of a Near Detector system located a few hundred meters from the neutrino source at Fermilab and a far detector system composed of four multi-kt LArTPCs at Sanford Underground Research Facility in South Dakota. The experiment will measure the leptonic CP violation phase of the PMNS matrix and discriminate the ordering of neutrino masses. Additional physics goals include detection of neutrinos from supernovae collapse and search for possible proton decay. One component of the Near detector complex is the System for on-Axis Neutrino Detection apparatus, which includes GRanular Argon for Interaction of Neutrinos, a novel liquid Argon detector that aims at imaging neutrino interactions using scintillation light collected by optical system and read-out by SIPM matrix. This thesis work aims at studying the GRAIN performances as a homogeneous calorimeter, able to measure the energy deposited by charged particles in LAr through scintillation photons emitted along their path inside the vessel. The energy calibration of the liquid argon volume required to write (and validate) an efficient software for the detector response simulation to the arrival of scintillation photons.