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

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.