Intermolecular and Intramolecular Charge Transfer in Functional Molecular Materials

This thesis is devoted to the investigation of inter and intramolecular charge transfer (CT) in molecular functional materials and specifically organic dyes and CT crystals. An integrated approach encompassing quantum-chemical calculations, semiempirical tools, theoretical models and spectroscopic measurements is applied to understand structure-property relationships governing the low-energy physics of these materials. Four main topics were addressed: 1) Spectral properties of organic dyes. Charge-transfer dyes are constituted by electron donor (D) and electron acceptor (A) units linked through bridge(s) to form molecules with different symmetry and dimensionality. Their low-energy physics is governed by the charge resonance between D and A groups and is effectively described by a family of parametric Hamiltonians known as essential-state models. These models account for few electronic states, corresponding to the main resonance structures of the relevant dye, leading to a simple picture that is completed introducing the coupling of the electronic system to molecular vibrations, treated in a non-adiabatic way, and an effective classical coordinate, describing polar solvation. In this work a specific essential-state model was proposed and parametrized for the dye Brilliant Green. The central issue in this work has been the definition of the diabatic states, a not trivial task for a multi-branched chromophore. In a second effort, we have used essential-state models for the description of the early-stage dynamics of excited states after ultrafast excitation. Crucial to this work is the fully non-adiabatic treatment of the coupled electronic and vibrational motion, allowing for a reliable description of the dynamics of systems showing a multistable, broken-symmetry excited state. 2) Mixed-stack CT salts. Mixed-stack (MS) CT crystals are an interesting class of multifunctional molecular materials, where D and A molecules arrange themselves to form stacks, leading to delocalized electrons in one dimension. The interplay between the intermolecular CT, electrostatic interactions, lattice phonons and molecular vibrations leads to intriguing physical properties that include (photoinduced) phase transitions, multistability, antiferromagnetism, ferroelectricity and potential multiferroicity. The standard microscopic model to describe this family of materials is the Modified Hubbard model accounting for electron-phonon coupling (Peierls coupling), electron-molecular vibrations coupling (Holstein coupling) and electrostatic interactions. We adopt and validate a method, based on DFT calculations on dimeric DA structures, to extract relevant model parameters. The approach offers a powerful tool to shed light on the complex physics of MS-CT salts. 3) Charge transfer in organic radical dipolar dyes. In collaboration with the group of Prof. Jaume Veciana (ICMAB- Barcellona), we have studied spectral properties of a special class of CT dyes with D-bridge-A structure where the acceptor group is a stable radical (of the perchlorotriphenylmethyl, PTM, family), leading to an open-shell CT dyes. These materials are of interest since they associate the electronic and optical properties of CT dyes with magnetic properties from the unpaired electron. The first effort was devoted to the parametrization of the relevant essential-state model. Two strategies were adopted, one based on the calculation of the low-energy spectral properties, the other based on the variation of ground state properties with an applied electric field. 4) The spectral properties of organic nanoparticles based on radical species are investigated in collaboration with Dr. I. Ratera (ICMAB- Barcellona). Intriguing spectroscopic behavior was observed pointing to the presence of excimer states. In an attempt to rationalize these findings, extensive calculations (TD-DFT and ZINDO) were performed. The results for the isolated dyes are validated against experimental spectra in solution. To address intermolecular interactions we studied dimeric structures in the gas phase, but the preliminary results obtained do not support excimer formation.

Multisensorial obstacles detection and classification for ADAS and autonomous driving

A reliable perception of the real world is a key-feature for an autonomous vehicle and the Advanced Driver Assistance Systems (ADAS). Obstacles detection (OD) is one of the main components for the correct reconstruction of the dynamic world. Historical approaches based on stereo vision and other 3D perception technologies (e.g. LIDAR) have been adapted to the ADAS first and autonomous ground vehicles, after, providing excellent results. The obstacles detection is a very broad field and this domain counts a lot of works in the last years. In academic research, it has been clearly established the essential role of these systems to realize active safety systems for accident prevention, reflecting also the innovative systems introduced by industry. These systems need to accurately assess situational criticalities and simultaneously assess awareness of these criticalities by the driver; it requires that the obstacles detection algorithms must be reliable and accurate, providing: a real-time output, a stable and robust representation of the environment and an estimation independent from lighting and weather conditions. Initial systems relied on only one exteroceptive sensor (e.g. radar or laser for ACC and camera for LDW) in addition to proprioceptive sensors such as wheel speed and yaw rate sensors. But, current systems, such as ACC operating at the entire speed range or autonomous braking for collision avoidance, require the use of multiple sensors since individually they can not meet these requirements. It has led the community to move towards the use of a combination of them in order to exploit the benefits of each one. Pedestrians and vehicles detection are ones of the major thrusts in situational criticalities assessment, still remaining an active area of research. ADASs are the most prominent use case of pedestrians and vehicles detection. Vehicles should be equipped with sensing capabilities able to detect and act on objects in dangerous situations, where the driver would not be able to avoid a collision. A full ADAS or autonomous vehicle, with regard to pedestrians and vehicles, would not only include detection but also tracking, orientation, intent analysis, and collision prediction. The system detects obstacles using a probabilistic occupancy grid built from a multi-resolution disparity map. Obstacles classification is based on an AdaBoost SoftCascade trained on Aggregate Channel Features. A final stage of tracking and fusion guarantees stability and robustness to the result.