English

Energy-Resolved EBSD using a Monolithic Direct Electron Detector

Materials Science 2025-12-19 v2

Abstract

Accurate quantification of the energy distribution of backscattered electrons (BSEs) contributing to electron backscatter diffraction (EBSD) patterns remains as an active challenge. This study introduces an energy-resolved EBSD methodology based on a monolithic active pixel sensor direct electron detector and an electron-counting algorithm to enable the energy quantification of individual BSEs, providing direct measurements of electron energy spectra within diffraction patterns. Following detector calibration of the detector signal as a function of primary beam energy, measurements using a 12 keV primary beam on Si(100) reveal a broad BSE energy distribution across the diffraction pattern, extending down to 3 keV. Furthermore, an angular dependence in the weighted average BSE energy is observed, closely matching predictions from Monte Carlo simulations. Pixel-resolved energy maps reveal subtle modulations at Kikuchi band edges, offering insights into the backscattering process. By applying energy filtering within spectral windows as narrow as 2 keV centered on the primary beam energy, significant enhancement in pattern clarity and high-frequency detail is observed. Notably, BSEs in the 9--10 keV range dominate Kikuchi pattern formation, while BSEs in the 2--8 keV range, despite having undergone substantial energy loss, still produce Kikuchi patterns. By enabling energy determination at the single-electron level, this approach introduces a versatile tool-set for expanding the quantitative capabilities of EBSD, thereby offering the potential to deepen the understanding of diffraction contrast mechanisms and to advance the precision of crystallographic measurements.

Keywords

Cite

@article{arxiv.2507.20105,
  title  = {Energy-Resolved EBSD using a Monolithic Direct Electron Detector},
  author = {Nicolò M. Della Ventura and Kalani Moore and McLean P. Echlin and Matthew R. Begley and Tresa M. Pollock and Marc De Graef and Daniel S. Gianola},
  journal= {arXiv preprint arXiv:2507.20105},
  year   = {2025}
}

Comments

14 pages, 10 figures