Automatic 3D image registration for nano-resolution chemical mapping using synchrotron spectro-tomography.

3D image registration X-ray spectro-tomography chemical heterogeneity transmission X-ray microscopy

Journal

Journal of synchrotron radiation
ISSN: 1600-5775
Titre abrégé: J Synchrotron Radiat
Pays: United States
ID NLM: 9888878

Informations de publication

Date de publication:
01 Jan 2021
Historique:
received: 20 06 2020
accepted: 06 11 2020
entrez: 5 1 2021
pubmed: 6 1 2021
medline: 6 1 2021
Statut: ppublish

Résumé

Nano-resolution synchrotron X-ray spectro-tomography has been demonstrated as a powerful tool for probing the three-dimensional (3D) structural and chemical heterogeneity of a sample. By reconstructing a number of tomographic data sets recorded at different X-ray energy levels, the energy-dependent intensity variation in every given voxel fingerprints the corresponding local chemistry. The resolution and accuracy of this method, however, could be jeopardized by non-ideal experimental conditions, e.g. instability in the hardware system and/or in the sample itself. Herein is presented one such case, in which unanticipated sample deformation severely degrades the data quality. To address this issue, an automatic 3D image registration method is implemented to evaluate and correct this effect. The method allows the redox heterogeneity in partially delithiated Li

Identifiants

pubmed: 33399578
pii: S1600577520014691
doi: 10.1107/S1600577520014691
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

278-282

Subventions

Organisme : National Key Research and Development Program of China
ID : 2016YFA0400900
Organisme : U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences
ID : DE-AC02-76SF00515

Auteurs

Jin Zhang (J)

Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, People's Republic of China.

Jun Hu (J)

School of Materials Science and Engineering, Nanjing Institute of Technology, Nanjing, Jiangsu 211167, People's Republic of China.

Zhisen Jiang (Z)

Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA.

Kai Zhang (K)

Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, People's Republic of China.

Peng Liu (P)

Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, People's Republic of China.

Chaonan Wang (C)

School of Science, Nantong University, Nantong, Jiangsu 226019, People's Republic of China.

Qingxi Yuan (Q)

Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, People's Republic of China.

Piero Pianetta (P)

Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA.

Yijin Liu (Y)

Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA.

Classifications MeSH