Literature DB >> 21817421

First-principles calculations of x-ray absorption near edge structure and energy loss near edge structure: present and future.

Isao Tanaka1, Teruyasu Mizoguchi.   

Abstract

Computational methods for theoretical x-ray absorption near edge structure (XANES) and energy loss near edge structure (ELNES) are classified into a few groups. Depending on the absorption (or excitation) edge, required accuracy and desired information, one needs to select the most suitable method. In this paper, after providing a map of available computational methods, some examples of first-principles calculations of XANES/ELNES for selected wide gap materials are given together with references. For ZnO, for example, experimental spectra at three edges, Zn K, L(3), and O K, including their orientation dependence, are well reproduced by the supercell calculations with a core hole. Good agreement between theoretical and experimental spectra of ZnO alloys can also be seen. Theoretical fingerprints are satisfactorily obtained in this way. However, there are remaining issues beyond 'good agreements' which need to be solved in the future.

Entities:  

Year:  2009        PMID: 21817421     DOI: 10.1088/0953-8984/21/10/104201

Source DB:  PubMed          Journal:  J Phys Condens Matter        ISSN: 0953-8984            Impact factor:   2.333


  3 in total

Review 1.  In Situ/Operando Electrocatalyst Characterization by X-ray Absorption Spectroscopy.

Authors:  Janis Timoshenko; Beatriz Roldan Cuenya
Journal:  Chem Rev       Date:  2020-09-28       Impact factor: 60.622

2.  Quantum simulation of thermally-driven phase transition and oxygen K-edge x-ray absorption of high-pressure ice.

Authors:  Dongdong Kang; Jiayu Dai; Huayang Sun; Yong Hou; Jianmin Yuan
Journal:  Sci Rep       Date:  2013-11-20       Impact factor: 4.379

3.  High-throughput computational X-ray absorption spectroscopy.

Authors:  Kiran Mathew; Chen Zheng; Donald Winston; Chi Chen; Alan Dozier; John J Rehr; Shyue Ping Ong; Kristin A Persson
Journal:  Sci Data       Date:  2018-07-31       Impact factor: 6.444

  3 in total

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