Coadsorption study of Pb and Sb on Cu(001) by low energy electron diffraction

Md Kabiruzzaman, Rezwan Ahmed, Takeshi Nakagawa, Seigi Mizuno

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Room temperature coadsorption of Pb and Sb on Cu(001) has been studied by low energy electron diffraction (LEED). A p(4×4) structure has been obtained by Pb and Sb at coverages of ∼0.25 and ∼0.125, respectively. This coverage combination is similar to the Pb and Bi study on Cu(001) [1]. This phase is confirmed by clear LEED patterns up to 250 eV. Above this energy some points of p(4×4) phase has been disappeared and only c(4×4) points remain. Based on LEED theory, using computer simulation and similarity of the coverage combination with Pb and Bi study, here a surface alloy model has been proposed and determined. The best-fit structure of the model and its consistency with the experimental results has been discussed in detail.

Original languageEnglish
Title of host publication2017 6th International Conference on Informatics, Electronics and Vision and 2017 7th International Symposium in Computational Medical and Health Technology, ICIEV-ISCMHT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781538610220
DOIs
Publication statusPublished - Apr 16 2018
Event6th International Conference on Informatics, Electronics and Vision and 2017 7th International Symposium in Computational Medical and Health Technology, ICIEV-ISCMHT 2017 - Himeji, Japan
Duration: Sept 1 2017Sept 3 2017

Publication series

Name2017 6th International Conference on Informatics, Electronics and Vision and 2017 7th International Symposium in Computational Medical and Health Technology, ICIEV-ISCMHT 2017
Volume2018-January

Other

Other6th International Conference on Informatics, Electronics and Vision and 2017 7th International Symposium in Computational Medical and Health Technology, ICIEV-ISCMHT 2017
Country/TerritoryJapan
CityHimeji
Period9/1/179/3/17

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Biomedical Engineering
  • Media Technology
  • Health Informatics

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