Synthesis, characterization and formulation of a cathode active material: Copper nitroprusside

Nowadays, rechargeable Li-ion batteries play an important role in portable consumer devices. Formulation of such batteries is improvable by researching new cathodic materials that present higher performances of cyclability and negligible efficiency loss over cycles. Goal of this work was to investigate a new cathodic material, copper nitroprusside, which presents a porous 3D framework. Synthesis was carried out by a low-cost and scalable co-precipitation method. Subsequently, the product was characterized by means of different techniques, such as TGA, XRF, CHN elemental analysis, XRD, Mössbauer spectroscopy and cyclic voltammetry. Electrochemical tests were finally performed both in coin cells and by using in situ cells: on one hand, coin cells allowed different formulations to be easily tested, on the other operando cycling led a deeper insight to insertion process and both chemical and physical changes. Results of several tests highlighted a non-reversible electrochemical behavior of the material and a rapid capacity fading over time. Moreover, operando techniques report that amorphisation occurs during the discharge.

Variational Quantum Splines: Moving Beyond Linearity for Quantum Activation Functions

Activation functions within neural networks play a crucial role in Deep Learning since they allow to learn complex and non-trivial patterns in the data. However, the ability to approximate non-linear functions is a significant limitation when implementing neural networks in a quantum computer to solve typical machine learning tasks. The main burden lies in the unitarity constraint of quantum operators, which forbids non-linearity and poses a considerable obstacle to developing such non-linear functions in a quantum setting. Nevertheless, several attempts have been made to tackle the realization of the quantum activation function in the literature. Recently, the idea of the QSplines has been proposed to approximate a non-linear activation function by implementing the quantum version of the spline functions. Yet, QSplines suffers from various drawbacks. Firstly, the final function estimation requires a post-processing step; thus, the value of the activation function is not available directly as a quantum state. Secondly, QSplines need many error-corrected qubits and a very long quantum circuits to be executed. These constraints do not allow the adoption of the QSplines on near-term quantum devices and limit their generalization capabilities. This thesis aims to overcome these limitations by leveraging hybrid quantum-classical computation. In particular, a few different methods for Variational Quantum Splines are proposed and implemented, to pave the way for the development of complete quantum activation functions and unlock the full potential of quantum neural networks in the field of quantum machine learning.

Formulation of ionogel, hydrogel and films using a cellulose rich solid obtained from Pinus radiata

The purpose of my internship, carried out during my Erasmus period at the Complutense University of Madrid, was focused on the formulation of ionogels and hydrogels for the obtainment of films with high lignin content, and on their characterization measuring their antibacterial properties. For biomass formulation I used lignocellulosic biomass (Pinus Radiata) as raw material and ionic liquid as solvent. The two ionic liquids proposed were: 1-ethyl-3-methylimidazoliumdimethylphosphate [Emim][DMP] and 1-ethyl-3-methylimidazoliumdiethylphosphate [Emim][DEP]. The two-starting cellulose-rich solids were obtained from Pinus radiata wood that had been submitted to an organosolv process, to reduce its lignin content to fifteen (ORG15) and twenty per cent (ORG20). Having two ionic liquids and two solids available, the first phase of the project was devoted to the screening of both solids in both ionic liquids. Through this, it was possible to identify that only the [Emim][DMP] ionic liquid fulfils the purpose. It was also possible to discard the cellulose-rich solid ORG20 because its dissolution in the ionic liquid was not possible (after the time fixed) and, additionally, a Pinus radiata cellulose-rich solid bleached with hydrogen peroxide and containing ten per cent of lignin (ORG10B) was included in the screening. After screening, a total of five ionogels were subsequently formulated: two gels were formulated with the starting raw material ORG15 (with 1% and 1.75% cellulose, respectively) and three with ORG10B (with 1%, 1.75% and 3% cellulose, respectively). Five hydrogels were obtained from the ionogels. Rheological tests were performed on each ionogel and hydrogel. Finally, films were formulated from hydrogels and they were analysed by antibacterial testing to see if they could be applied as food packaging. In addition, antioxidant and properties such as opacity and transparency were also studied.