@article{20594,
  abstract     = {(Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of devices due to its time-intensive nature. To address this, an analytical workflow is introduced for the holistic characterization, modelling, and simulation of device heterostructures. This workflow automates the experimental (S)TEM data analysis, providing an in-depth characterization of crystallographic information, 3D orientation, elemental composition, and strain distribution. It reduces a process that typically takes days for a trained human into an automatic routine solved in minutes. Utilizing a physics-guided artificial intelligence model, it generates representative descriptions of materials and samples. The workflow culminates in creating digital twins of systems limited with at least one axis of translational invariance –3D finite element and atomic models of millions of atoms–enabling simulations that provide crucial insights into device behavior in practical applications. Demonstrated with SiGe planar heterostructures for scalable spin qubits, the workflow links digital twins to theoretical properties, revealing how atomic structure impacts materials and functional properties such as spatially-resolved phononic or electronic characteristics, or (inverse) spin orbit lengths. The versatility of the workflow is demonstrated through its application to a wide array of materials systems, device configurations, and sample morphologies.},
  author       = {Botifoll, Marc and Pinto-Huguet, Ivan and Rotunno, Enzo and Galvani, Thomas and Coll, Catalina and Kavkani, Payam Habibzadeh and Spadaro, Maria Chiara and Niquet, Yann Michel and Eriksen, Martin Børstad and Martí-Sánchez, Sara and Katsaros, Georgios and Scappucci, Giordano and Krogstrup, Peter and Isella, Giovanni and Cabot, Andreu and Merino, Gonzalo and Ordejón, Pablo and Roche, Stephan and Grillo, Vincenzo and Arbiol, Jordi},
  issn         = {1521-4095},
  journal      = {Advanced Materials},
  publisher    = {Wiley},
  title        = {{Artificial intelligence-assisted workflow for transmission electron microscopy: From data analysis automation to materials knowledge unveiling}},
  doi          = {10.1002/adma.202506785},
  year         = {2025},
}