Characterization of an OPCPA laser amplifier based on the nonlinear crystal YCOB

The work described in this thesis was performed at the Laboratory for Intense Lasers (L2I) of Instituto Superior Técnico, University of Lisbon (IST-UL). Its main contribution consists in the feasibility study of the broadband dispersive stages for an optical parametric chirped pulse amplifier based on the nonlinear crystal yttrium calcium oxi-borate (YCOB). In particular, the main goal of this work consisted in the characterization and implementation of the several optical devices involved in pulse expansion and compression of the amplified pulses to durations of the order of a few optical cycles (20 fs). This type of laser systems find application in fields such as medicine, telecommunications and machining, which require high energy, ultrashort (sub-100 fs) pulses. The main challenges consisted in the preliminary study of the performance of the broadband amplifier, which is essential for successfully handling pulses with bandwidths exceeding 100 nm when amplified from the μJ to 20 mJ per pulse. In general, the control, manipulation and characterization of optical phenomena on the scale of a few tens of fs and powers that can reach the PW level are extremely difficult and challenging due to the complexity of the phenomena of radiation-matter interaction and their nonlinearities, observed at this time scale and power level. For this purpose the main dispersive components were characterized in detail, specifically addressing the demonstration of pulse expansion and compression. The tested bandwidths are narrower than the final ones, in order to confirm the parameters of these elements and predict the performance for the broadband pulses. The work performed led to additional tasks such as a detailed characterization of laser oscillator seeding the laser chain and the detection and cancelling of additional sources of dispersion.

Nanocomposite polymer beads for cell detection

Circulating tumor cells (CTCs) may induce metastases when detached from the primary tumor. The numbers of these cells in blood offers a valuable prognostic indication. Magnetoresistive sensing is an attractive option for CTC counting. In this technique, cells are labeled with nancomposite polymer beads that provide the magnetic signal. Bead properties such as size and magnetic content must be optimized in order to be used as a detection tool in a magnetoresistive platform. Another important component of the platform is the magnet required for proper sensing. Both components are addressed in this work. Nanocomposite polymer beads were produced by nano-emulsion and membrane emulsification. Formulations of the oil phase comprising a mixture of aromatic monomers and iron oxide were employed. The effect of emulsifier (surfactant) concentration on bead size was studied. Formulations of polydimethilsiloxane (PDMS) with different viscosities were also prepared with nano-emulsion method resulting in colloidal beads. Polycaprolactone (PCL) beads were also synthetized by the membrane emulsification method. The beads were characterized by different techiques such as dynamic light scattering (DLS), thermogravimetric analysis (TGA) and scanning electron microscopy (SEM). Additionally, the magnet dimensions of the platform designed to detect CTCs were optimized through a COMSOL multiphysics simulation.

Analysis of classification algorithms for crop detection using LANDSAT 8 images

Remote sensing - the acquisition of information about an object or phenomenon without making physical contact with the object - is applied in a multitude of different areas, ranging from agriculture, forestry, cartography, hydrology, geology, meteorology, aerial traffic control, among many others. Regarding agriculture, an example of application of this information is regarding crop detection, to monitor existing crops easily and help in the region’s strategic planning. In any of these areas, there is always an ongoing search for better methods that allow us to obtain better results. For over forty years, the Landsat program has utilized satellites to collect spectral information from Earth’s surface, creating a historical archive unmatched in quality, detail, coverage, and length. The most recent one was launched on February 11, 2013, having a number of improvements regarding its predecessors. This project aims to compare classification methods in Portugal’s Ribatejo region, specifically regarding crop detection. The state of the art algorithms will be used in this region and their performance will be analyzed.