Speaker
Yue Li
(Max-Planck-Institut für Eisenforschung GmbH)
Description
L12-type nano-ordered structures are typically fully-coherent with FCC matrix, which is challengeable to be characterized. Spatial distribution maps are used to probe local order within reconstructed APT data. However, it is almost impossible to manually analyse the complete point cloud in search for the partial crystallographic information retained within the data. Here, we proposed an intelligent L12-ordered structure recognition method based on convolutional neural networks. The approach was successfully applied to reveal the 3D distribution of L12–type nanoparticles with an average radius of 2.54nm in an Al-Li-Mg system. The minimum radius of detectable nanodomain is even down to 5 Å.
Primary author
Yue Li
(Max-Planck-Institut für Eisenforschung GmbH)
Co-authors
Dr
Xuyang Zhou
(Max-Planck Institut für Eisenforschung GmbH)
Timoteo Colnaghi
(Max Planck Computing and Data Facility)
Dr
Ye Wei
(Max-Planck Institut für Eisenforschung GmbH)
Andreas Marek
(Max Planck Computing and Data Facility)
Prof.
Hongxiang Li
(University of Science and Technology Beijing)
Dr
Stefan Bauer
(Max-Planck-Institut für Intelligente Systeme)
Markus Rampp
(Max Planck Computing and Data Facility (MPCDF))
Leigh Stephenson
(Max-Planck Institut für Eisenforschung GmbH)
