Polarimetric Imaging for the Optical Characterization of Advanced Materials: Application to Organic Glasses and nanostructured materials

Organic semiconductor materials are attracting growing interest due to their advantages over conventional semiconductors such as silicon and germanium. Their lightweight, flexible nature, reduced toxicity, and low production costs make them promising for applications in organic electronics and optoelectronics. Both organic and inorganic nanostructured systems offer unique opportunities, as their electronic and optical properties can be tuned through chemical composition, molecular design, and nanoscale architecture.

A key challenge is the reliable characterization of these complex materials, as their internal organization and anisotropy directly affect charge transport, exciton dynamics, optical response, and stability. Optical techniques are ideal to addressing this challenge. Advanced polarimetric methods, including generalized ellipsometry and imaging Mueller polarimetry, enable spatially resolved mapping of birefringence, dichroism, depolarization, and molecular orientation, directly linking nanoscale structure to macroscopic function. Despite their potential, these approaches remain underexplored in the study of advanced organic and inorganic nanostructured materials.

This doctoral thesis will investigate the use of state-of-the-art polarimetric imaging to non-invasively characterize key optical and structural properties of above stated materials. Since imaging techniques will be used, the studies can be applied to analyze heterogeneities within the sample.

We also aim to investigate whether physical features extracted through polarimetric techniques can be used to train artificial intelligence models capable of identifying key properties of unknown samples. In this way, we seek to establish a data-driven framework that links polarimetric signatures to intrinsic material characteristics. This approach could enable rapid, non-destructive characterization and open new pathways for intelligent material diagnostics and classification.

The candidate should hold a degree in Physics, Materials Science, or a related discipline. A solid foundation in optics and/or materials engineering is expected, as well as familiarity with experimental laboratory work. While not strictly required, prior knowledge in one or more of the following areas would be considered an asset:

• Optics: understanding of polarization, optical anisotropy, and the interaction of light with matter; familiarity with polarimetric methods and optical characterization techniques.
• Materials science: experience in the preparation, processing, or thin-film growth of organic, inorganic, or hybrid materials; basic knowledge of structural and spectroscopic characterization methods.

In addition, the candidate should demonstrate analytical skills, motivation to learn advanced experimental techniques, and the ability to work in an interdisciplinary environment that combines physics, materials science, and optical engineering. Strong written and oral communication skills in English are also desirable.

The Optics Group at UAB is internationally recognized for its research in image processing, surface metrology, and liquid crystal applications. They specialize in polarimetric instrumentation, with innovations using liquid crystal panels and conical refraction. Their technology has been applied in industry and biomedicine, notably enhancing tissue imaging and recognition using machine learning and depolarizing observables.The team currently consists of 3 senior researchers, 1 Ramon y Cajal (RyC) investigator, 1 postdoc, and 4 PhD students.

The project will be a collaboration with the Group of Thermal Properties of Nanoscale Materials (GTNaM). The group is partially ascribed to ICN2 and focuses its research on the fabrication and characterization of materials at the nanoscale, both organic and inorganic, with special emphasis on thin films. The part of the team working on the topic of this project consists of 3 senior researchers and 2 PhD students.