Titolo della tesi: Unlocking the Secrets of Complex Structures through Advanced Correlative Microscopy Techniques
The long journey of correlative microscopy (CM) began in 1945 when Keith Porter conducted pioneering studies demonstrating that specific details within specimens could be observed and characterized using both light microscopy (LM) and electron microscopy (EM) with proper sample preparation. Subsequent comparative attempts followed, thanks to contributions from McDonald, Pease, Hayes, and Geissenger, culminating in the development of detailed and robust protocols leading to correlative light and electron microscopy (CLEM) by 1980, as detailed in Chapter 1. Since then, CLEM has matured significantly, benefitting from technological advancements in both LM and EM fields, including super-resolution techniques overcoming the Abbe limit and the introduction of EM tomography enabling three-dimensional structure surveys with nanometric resolution. Currently, CLEM is defined as an imaging approach that combines the strengths of LM and EM to provide crucial information in the analysis of both materials and biological specimens. CLEM allows researchers to visualize the same area of the same sample using both LM and EM. This integration can be supplemented by additional complementary investigation techniques for multiscale and multimodal characterization in terms of microstructure, morphology, function, and chemistry, as extensively discussed in Chapter 2. In this thesis, practical examples and methodologies optimization for advanced CLEM experiments are provided. The innovative approach brought by CLEM has delineated the fundamental principles of modern CM, representing a game-changing element in scientific research. The laboratory landscape is currently undergoing dynamic transformation, driven by relentless scientific progress and contemporary research demands. Both academic and industrial research fields are characterized by an insatiable thirst for more precise, comprehensive, and interdisciplinary insights into material and biological sample properties and behaviors. The increasing complexity of scientific questions necessitates a holistic, multimodal, and multiscale approach, from macrostructures down to the atomic level, across multiple characterization tools. This thesis delves into the pivotal role of CM, as a key enabling technology, for the development of new investigation workflows and protocols, exploring its versatility in addressing advanced scientific problems and revealing hidden details across multiple length scales and modalities within specimens. A detailed description of a complete and modern CM workflow is provided, offering practical suggestions and procedures for effective CM experiment design, including advanced hardware and software solutions such as artificial intelligence. In Chapters 3 and 4, the application of CM workflows based on both non-destructive and destructive characterization techniques in some of today's cutting-edge scientific research fields will be described, including electronics and semiconductors, aerospace, biodegradation of recalcitrant materials, geosciences, and cultural heritage. In Chapter 3, CM is used to explore the infiltrative and degradative ability of Fusarium oxysporum on Polyethylene terephthalate (PET) with the combined use of Deep Learning (DL) techniques. The fungal strain F2 was chosen for this study among the many isolated from soil with the aid of PET baits, as it was the one performing best in growth tests on PET and had an abundant production of the enzymes cutinases and esterases, which are heavily involved in plastic degradation. The use of non-destructive high-resolution X-ray microscopy (XRM) coupled with the state-of-art DL reconstruction algorithm, called ZEISS DeepScout, revealed that the fungal strain F2 exhibited a preferential distribution and enhanced penetration when growing in proximity to edges and corners of PET fragments, compared to planar surfaces. The fungal attack resulted in a multiphase region, with variations in morphology and composition. Indeed, this study allowed for the identification of three distinct phases constituting the sample, which, thanks to additional analyses with Raman spectroscopy and energy dispersive X-ray spectroscopy (EDX), were identified as the fungal strain, biodegraded plastic, and salt crystals. The correlative microscopy approach enabled a comprehensive understanding of the interaction between the fungal strain and the PET substrate, shedding light on degradation processes, morphological changes, and potential structural alterations. This study highlights the importance of employing advanced microscopy techniques to investigate the complex dynamics of fungal plastic degradation, contributing to our understanding of potential strategies for mitigating plastic pollution. In Chapter 4, CM workflows are applied in the electronics and semiconductors field, cultural heritage and geosciences. Failure analysis engineers presented a multiscale and multimodal CM workflow for the comprehensive characterization of copper inclusions in the epitaxial layer of Superjunction Multi-drain MOSFETs. Copper inclusions can introduce defects in the crystal lattice, leading to localized areas of high resistance or conductivity and causing issues like high leakage (IDSS) or soft breakdown voltage (BVDSS). To address these challenges, a combination of LM, XRM, FIB-SEM tomography, EDX, TEM, and EELS was applied. The multimodal approach allowed failure analysis engineers to gain insights into the morphology, topology, and chemistry of the copper inclusions across different length scales. These findings revealed the distribution and characteristics of copper segregations with different shapes and sizes, providing a comprehensive understanding of their impact on the structural level of the power MOSFETs. This approach, which can be adopted in further workflows in the field of electronics and semiconductor failure analysis and research, is instrumental in addressing and mitigating issues related to epitaxial layers in Superjunction Multi-drain MOSFETs, offering valuable insights for improving device performance and reliability in power electronics applications. In the field of cultural heritage and conservation studies, researchers adopted CM workflows and proved it to be an effective mean the push the boundaries of our understanding of ancient artifacts. Conservation scientists also emphasized the importance of an integrated approach in addressing complex issues related to metallurgy and the conservation of historical artifacts. The application of advanced techniques offered new perspectives in the field of archaeology and heritage conservation, with significant implications for understanding the interactions between metallic materials and corrosive environments over time while also elucidating new corrosion models and mechanisms. CM was applied in structural geology suggesting that at a depth range between 30 and 80 km in subduction zones the genesis and migration of fluids carrying deep energy sources can lead to supralithostatic pore-fluid pressure and trigger brittle failure in omphacite-rich, mechanically strong rock types similar to eclogite. Modeling results suggest that these CH4-H2-rich fluids can lead to brittle failure much more easily compared to water-dominated fluids, with a CH4-H2-rich fluid having a volume 70% higher than pure H2O at these conditions. Immiscibility and phase separation may have favored preferential accumulation of carbon-hydrogen fluids via hydrofracturing. Researchers proposed that talcschist and serpentinites acted as low-permeability barriers and seal horizons, thus allowing pore pressure to increase until (supra)lithostatic conditions. The research group envisaged that genesis and migration of CH4-H2-rich aqueous fluids may trigger seismic activity in subduction zones at forearc depths. These processes may play an important role in promoting the migration of deep energy sources from deep source areas towards shallower reservoirs, including the subsurface biosphere where microbial life can take advantage of them through metabolic processes. The results proposed in this thesis stand as a culmination of research and exploration activities carried out by Dr. Flavio Cognigni into the realm of correlative microscopy (CM), representing a comprehensive example of the objectives that the collaboration between academic and industrial research can achieve while also paving new directions for pushing the boundaries of our exploration capabilities.