Toward an accurate quantification in atom probe tomography reconstruction by correlative electron tomography approach on nanoporous materials.

In this contribution, we propose a protocol for analysis and accurate reconstruction of nanoporous materials by atom probe tomography (APT). The existence of several holes in porous materials makes both the direct APT analysis and reconstruction almost inaccessible. In the past, a solution has been proposed by filling pores with electron beam-induced deposition. Here, we present an alternative solution using an electro-chemical method allowing to fill even small and dense pores, making APT analysis possible. Concerning the 3D reconstruction, the microstructural features observed by electron tomography are used to finely calibrate the APT reconstruction parameters.

Doping porous silicon with erbium: pores filling as a method to limit the Er-clustering effects and increasing its light emission.

Er clustering plays a major role in hindering sufficient optical gain in Er-doped Si materials. For porous Si, the long-standing failure to govern the clustering has been attributed to insufficient knowledge of the several, concomitant and complex processes occurring during the electrochemical Er-doping. We propose here an alternative road to solve the issue: instead of looking for an equilibrium between Er content and light emission using 1-2% Er, we propose to significantly increase the electrochemical doping level to reach the filling the porous silicon pores with luminescent Er-rich material. To better understand the intricate and superposing phenomena of this process, we exploit an original approach based on needle electron tomography, EXAFS and photoluminescence. Needle electron tomography surprisingly shows a heterogeneous distribution of Er content in the silicon thin pores that until now couldn't be revealed by the sole use of scanning electron microscopy compositional mapping. Besides, while showing that pore filling leads to enhanced photoluminescence emission, we demonstrate that the latter is originated from both erbium oxide and silicate. These results give a much deeper understanding of the photoluminescence origin down to nanoscale and could lead to novel approaches focused on noteworthy enhancement of Er-related photoluminescence in porous silicon.

Non-rigid alignment in electron tomography in materials science.

Electron tomography is a key technique that enables the visualization of an object in three dimensions with a resolution of about a nanometre. High-quality 3D reconstruction is possible thanks to the latest compressed sensing algorithms and/or better alignment and preprocessing of the 2D projections. Rigid alignment of 2D projections is routine in electron tomography. However, it cannot correct misalignments induced by (i) deformations of the sample due to radiation damage or (ii) drifting of the sample during the acquisition of an image in scanning transmission electron microscope mode. In both cases, those misalignments can give rise to artefacts in the reconstruction. We propose a simple-to-implement non-rigid alignment technique to correct those artefacts. This technique is particularly suited for needle-shaped samples in materials science. It is initiated by a rigid alignment of the projections and it is then followed by several rigid alignments of different parts of the projections. Piecewise linear deformations are applied to each projection to force them to simultaneously satisfy the rigid alignments of the different parts. The efficiency of this technique is demonstrated on three samples, an intermetallic sample with deformation misalignments due to a high electron dose typical to spectroscopic electron tomography, a porous silicon sample with an extremely thin end particularly sensitive to electron beam and another porous silicon sample that was drifting during image acquisitions.

Self-adapting denoising, alignment and reconstruction in electron tomography in materials science.

An automatic procedure for electron tomography is presented. This procedure is adapted for specimens that can be fashioned into a needle-shaped sample and has been evaluated on inorganic samples. It consists of self-adapting denoising, automatic and accurate alignment including detection and correction of tilt axis, and 3D reconstruction. We propose the exploitation of a large amount of information of an electron tomography acquisition to achieve robust and automatic mixed Poisson-Gaussian noise parameter estimation and denoising using undecimated wavelet transforms. The alignment is made by mixing three techniques, namely (i) cross-correlations between neighboring projections, (ii) common line algorithm to get a precise shift correction in the direction of the tilt axis and (iii) intermediate reconstructions to precisely determine the tilt axis and shift correction in the direction perpendicular to that axis. Mixing alignment techniques turns out to be very efficient and fast. Significant improvements are highlighted in both simulations and real data reconstructions of porous silicon in high angle annular dark field mode and agglomerated silver nanoparticles in incoherent bright field mode. 3D reconstructions obtained with minimal user-intervention present fewer artefacts and less noise, which permits easier and more reliable segmentation and quantitative analysis. After careful sample preparation and data acquisition, the denoising procedure, alignment and reconstruction can be achieved within an hour for a 3D volume of about a hundred million voxels, which is a step toward a more routine use of electron tomography.