Three-dimensional characterization of iron oxide (α-Fe2O3) nanoparticles: Application of a compressed sensing inspired reconstruction algorithm to electron tomography

Niven Monsegue, Xin Jin, Takuya Echigo, Ge Wang, Mitsuhiro Murayama

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

In this article, we demonstrate the application of a new compressed sensing three-dimensional reconstruction algorithm for electron tomography that increases the accuracy of morphological characterization of nanostructured materials such as nanocrystalline iron oxide particles. A powerful feature of the algorithm is an anisotropic total variation norm for the L1 minimization during algebraic reconstruction that effectively reduces the elongation artifacts caused by limited angle sampling during electron tomography. The algorithm provides faithful morphologies that have not been feasible with existing techniques.

Original languageEnglish
Pages (from-to)1362-1367
Number of pages6
JournalMicroscopy and Microanalysis
Volume18
Issue number6
DOIs
Publication statusPublished - Dec 1 2012

Fingerprint

Compressed sensing
Iron oxides
iron oxides
Tomography
tomography
Nanoparticles
nanoparticles
Electrons
electrons
Nanostructured materials
norms
elongation
artifacts
Elongation
sampling
Sampling
optimization

All Science Journal Classification (ASJC) codes

  • Instrumentation

Cite this

Three-dimensional characterization of iron oxide (α-Fe2O3) nanoparticles : Application of a compressed sensing inspired reconstruction algorithm to electron tomography. / Monsegue, Niven; Jin, Xin; Echigo, Takuya; Wang, Ge; Murayama, Mitsuhiro.

In: Microscopy and Microanalysis, Vol. 18, No. 6, 01.12.2012, p. 1362-1367.

Research output: Contribution to journalArticle

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