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 journalArticlepeer-review

15 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 2012

All Science Journal Classification (ASJC) codes

  • Instrumentation

Fingerprint Dive into the research topics of 'Three-dimensional characterization of iron oxide (α-Fe<sub>2O</sub>3) nanoparticles: Application of a compressed sensing inspired reconstruction algorithm to electron tomography'. Together they form a unique fingerprint.

Cite this