Enzo Rotunno

Short Bio

Enzo Rotunno graduated magna cum laude in Material Science at the University of Parma in 2010 and obtained his PhD degree in material science from the same institution in 2014.
Since 2014 he has a research fellow position at the Italian National Research Council. During his career he achieved high competence in the field of Transmission Electron Microscopy mastering the main electron imaging, diffraction and spectroscopic techniques, with his main research interest being the study of materials through STEM with HAADF detector and the developed of numerical algorithms for the simulation of the electron-matter interaction. He currently works in CNR-NANO Quantum e-optics group among the world’s leading groups in the field of electron vortex beams, and the theory of spin-orbit coupling with vortex. Recently he has started a theoretical activity related to the development of deep learning techniques for electron microscopy.

He is co-author of more than 40 research paper. The H-index of his publications is 14.

 

Research Interests

His research activities are mainly focused on:

  • the development of beam shaping techniques within a transmission electron microscope and their automation using artificial neural networks
  • quantitative TEM analysis by means of HRTEM, STEM-HAADF and EELS techniques
  • realization/application of software for the numerical calculation of the interaction processes between electron beams and matter.

Selected Recent Projects

Selected Publications

V. Grillo and E. Rotunno "STEM_CELL: A software tool for electron microscopy: Part I-simulations." Ultramicroscopy (2013)

E. Rotunno et al. "Three dimensional analysis of the composition in solid alloys by variable probe in scanning transmission electron microscopy" Ultramicroscopy 146 (2014) 62-70

E. Rotunno et al. "A Novel Sb2Te3 Polymorph Stable at the Nanoscale" Chem. Mater. 27 (2015)4368−4373

E. Rotunno et al. “Orbital angular momentum resolved electron magnetic chiral dichroism” Phis. Rev. B (2019) 224409

E. Rotunno et al. “Alignment of electron optical beam shaping elements using a convolutional neural network” Ultramicroscopy (2021) 113338