PhD: Ivan Pinto Huguet

Directors:

ICREA Prof. Jordi Arbiol, Group Leader of the Advanced Electron Nanoscopy group at Institut Català de Nanociència i Nanotecnologia (ICN2)

Dr Marc Botifoll, Marie Curie Posdoctoral researcher at Ernst Ruska Centre, Forschungszentrum Jülich

Short Abstract:

Nanomaterials play a central role in emerging technologies, yet their increasing structural complexity and the large volumes of data generated by modern electron microscopy pose major challenges for conventional characterization workflows. This thesis develops artificial intelligence and computer vision methodologies to automate and enhance nanomaterials characterization through electron microscopy. A collection of AI-assisted methodologies is developed to address different characterization challenges, including image segmentation, denoising, feature detection, classification, and quantitative analysis across multiple microscopy modalities. These methodologies are validated across a wide range of applications, including quantum materials, nanoparticles, glasses, dual-atom catalysts, and two-dimensional materials, demonstrating their robustness under challenging imaging conditions. Beyond individual algorithms, this work integrates these developments into complete AI-assisted characterization workflows that enable automated, reproducible, and high-throughput analysis of complex microscopy datasets. 

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