Defects in thermosensitive colloidal crystals

Poly-N-Isopropylacrylamide (PNIPAM) colloidal particles form crystal phases that show a thermosensitive behaviour and can be used as atomic model systems. This polymer has both hydrophilic and hydrophobic character and has interesting stimuli-responsive properties in aqueous solution, of which the most important is the temperature response. Above a certain temperature, called Lower Critical Solution Temperature (LCST), the system undergoes a volume phase transition (VPT). Above the LCST, the water is expelled from the polymer network and the swollen state at low temperature transforms into a shrunken state at high temperature. The thermoresponsive behaviour of PNIPAM can be influenced by pH and ionic strength, as well as by the presence of copolymers, such as acrylic acid. In a system formed both by particles of PNIPAM and PNIPAM doped with acrylic acid, one can control the size ratio of the two components by changing the temperature of the mixture, while keeping particle interactions relatively the same. It is therefore possible to obtain thermoresponsive colloidal crystal in which temperature changes induce defects whose formation processes and dynamics can be analysed in an optical microscope at a convenient spatial and temporal scale. The goal of this thesis project was to find the conditions in which such a system could be formed, by using characterization techniques such as Static Light Scattering, Dynamic Light Scattering and Confocal Laser Scanning Microscopy. Two PNIPAM-AAc systems were available, and after characterization it was possible to select a suitable one, on the basis of its low polydispersity and the lack of a VPT, regardless of the external conditions (system JPN_7). The synthesis of a PNIPAM system was attempted, with particles of dimensions matching the JPN_7 system and, unlike JPN_7, displaying a VPT, and one suitable candidate for the mixed system was finally found (system CB_5). The best conditions to obtain thermoresponsive crystal were selected, and the formation and healing of defects were investigated with CLSM temperature scans. The obtained results show that the approach is the correct one and that the present report could represent a useful start for future developments in defect analysis and defect dynamics studies.

Fault diagnosis of an automotive suspension system

With the development of the embedded application and driving assistance systems, it becomes relevant to develop parallel mechanisms in order to check and to diagnose these new systems. In this thesis we focus our research on one of this type of parallel mechanisms and analytical redundancy for fault diagnosis of an automotive suspension system. We have considered a quarter model car passive suspension model and used a parameter estimation, ARX model, method to detect the fault happening in the damper and spring of system. Moreover, afterward we have deployed a neural network classifier to isolate the faults and identifies where the fault is happening. Then in this regard, the safety measurements and redundancies can take into the effect to prevent failure in the system. It is shown that The ARX estimator could quickly detect the fault online using the vertical acceleration and displacement sensor data which are common sensors in nowadays vehicles. Hence, the clear divergence is the ARX response make it easy to deploy a threshold to give alarm to the intelligent system of vehicle and the neural classifier can quickly show the place of fault occurrence.