Experimental reconstructions of 3D atomic structures from electron microscopy images using a Bayesian genetic algorithm
- Resource Type
- article
- Authors
- Annick De Backer; Sandra Van Aert; Christel Faes; Ece Arslan Irmak; Peter D. Nellist; Lewys Jones
- Source
- npj Computational Materials, Vol 8, Iss 1, Pp 1-8 (2022)
- Subject
- Materials of engineering and construction. Mechanics of materials
TA401-492
Computer software
QA76.75-76.765
- Language
- English
- ISSN
- 2057-3960
Abstract We introduce a Bayesian genetic algorithm for reconstructing atomic models of monotype crystalline nanoparticles from a single projection using Z-contrast imaging. The number of atoms in a projected atomic column obtained from annular dark field scanning transmission electron microscopy images serves as an input for the initial three-dimensional model. The algorithm minimizes the energy of the structure while utilizing a priori information about the finite precision of the atom-counting results and neighbor-mass relations. The results show promising prospects for obtaining reliable reconstructions of beam-sensitive nanoparticles during dynamical processes from images acquired with sufficiently low incident electron doses.