Fast reconstruction of atomic-scale STEM-EELS images from sparse sampling

This paper discusses the reconstruction of partially sampled spectrum-images to accelerate the acquisition in scanning transmission electron microscopy (STEM). The problem of image reconstruction has been widely considered in the literature for many imaging modalities, but only a few attempts handled 3D data such as spectral images acquired by STEM electron energy loss spectroscopy (EELS). Besides, among the methods proposed in the microscopy literature, some are fast but inaccurate while others provide accurate reconstruction but at the price of a high computation burden. Thus none of the proposed reconstruction methods fulfills our expectations in terms of accuracy and computation complexity. In this paper, we propose a fast and accurate reconstruction method suited for atomic-scale EELS. This method is compared to popular solutions such as beta process factor analysis (BPFA) which is used for the first time on STEM-EELS images. Experiments based on real as synthetic data will be conducted

Linear chemically sensitive electron tomography using DualEELS and dictionary-based compressed sensing

We have investigated the use of DualEELS in elementally sensitive tilt series tomography in the scanning transmission electron microscope. A procedure is implemented using deconvolution to remove the effects of multiple scattering, followed by normalisation by the zero loss peak intensity. This is performed to produce a signal that is linearly dependent on the projected density of the element in each pixel. This method is compared with one that does not include deconvolution (although normalisation by the zero loss peak intensity is still performed). Additionaly, we compare the 3D reconstruction using a new compressed sensing algorithm, DLET, with the well-established SIRT algorithm. VC precipitates, which are extracted from a steel on a carbon replica, are used in this study. It is found that the use of this linear signal results in a very even density throughout the precipitates. However, when deconvolution is omitted, a slight density reduction is observed in the cores of the precipitates (a so-called cupping artefact). Additionally, it is clearly demonstrated that the 3D morphology is much better reproduced using the DLET algorithm, with very little elongation in the missing wedge direction. It is therefore concluded that reliable elementally sensitive tilt tomography using EELS requires the appropriate use of DualEELS together with a suitable reconstruction algorithm, such as the compressed sensing based reconstruction algorithm used here, to make the best use of the limited data volume and signal to noise inherent in core-loss EELS

Atomic Configuration of Nitrogen Doped Single-Walled Carbon Nanotubes

Having access to the chemical environment at the atomic level of a dopant in a nanostructure is crucial for the understanding of its properties. We have performed atomically-resolved electron energy-loss spectroscopy to detect individual nitrogen dopants in single-walled carbon nanotubes and compared with first principles calculations. We demonstrate that nitrogen doping occurs as single atoms in different bonding configurations: graphitic-like and pyrrolic-like substitutional nitrogen neighbouring local lattice distortion such as Stone-Thrower-Wales defects. The stability under the electron beam of these nanotubes has been studied in two extreme cases of nitrogen incorporation content and configuration. These findings provide key information for the applications of these nanostructures.Comment: 25 pages, 13 figure

Physics discovery in nanoplasmonic systems via autonomous experiments in Scanning Transmission Electron Microscopy

Physics-driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here we develop and experimentally implement a deep kernel learning workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics-based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure-property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk- and edge plasmon discovery in MnPS3, a lesser-known beam-sensitive layered 2D material. This approach is universal, can be directly used as-is with any specimen, and is expected to be applicable to any probe-based microscopic techniques including other STEM modalities, Scanning Probe Microscopies, chemical, and optical imaging

Instability, Intermixing and Electronic Structure at the Epitaxial LaAlO3/SrTiO3(001) Heterojunction

The question of stability against diffusional mixing at the prototypical LaAlO3/SrTiO3(001) interface is explored using a multi-faceted experimental and theoretical approach. We combine analytical methods with a range of sensitivities to elemental concentrations and spatial separations to investigate interfaces grown using on-axis pulsed laser deposition. We also employ computational modeling based on the density function theory as well as classical force fields to explore the energetic stability of a wide variety of intermixed atomic configurations relative to the idealized, atomically abrupt model. Statistical analysis of the calculated energies for the various configurations is used to elucidate the relative thermodynamic stability of intermixed and abrupt configurations. We find that on both experimental and theoretical fronts, the tendency toward intermixing is very strong. We have also measured and calculated key electronic properties such as the presence of electric fields and the value of the valence band discontinuity at the interface. We find no measurable electric field in either the LaAlO3 or SrTiO3, and that the valence band offset is near zero, partitioning the band discontinuity almost entirely to the conduction band edge. Moreover, we find that it is not possible to account for these electronic properties theoretically without including extensive intermixing in our physical model of the interface. The atomic configurations which give the greatest electrostatic stability are those that eliminate the interface dipole by intermixing, calling into question the conventional explanation for conductivity at this interface - electronic reconstruction. Rather, evidence is presented for La indiffusion and doping of the SrTiO3 below the interface as being the cause of the observed conductivity

Energy-Filtering Transmission Electron Microscopy of Biological Specimens

By energy-filtering transmission electron microscopy (EFTEM) electrons can be separated by their energy losses. An electron-energy filter, added to the microscope column allows the measurement of the energy distribution of transmitted electrons that have lost energy (\u3c 2,000 eV, with an energy resolution of ~ 1 eV). These filtered electrons, recorded either as a spectrum or as an image, are composed of two parts superimposed on top of each other: (a) the unspecific energy-loss population (= the continuum) and (b) the specific element-related energy-loss population (= the edges). At the edges, electron data in spectra and images are mathematically processed, to obtain the desired element-related net-intensity values or images. These data are related to the total transmitted electron intensity, from the zero-and low-loss spectral region giving the relative spectral-or image intensity ratios (SR*x, IR*x), which can be related to the element concentration. The acquisition of the zero-loss and low-loss data is hampered by the restricted dynamic range of the TV camera. By improvements through the introduction of calibrated attenuation filters in the optical path to the TV-camera, more reliable values for SR*x and IR*x can be acquired. By addition of Bio-standards adjacent to the tissue, a known and unknown concentration of the element present in the same ultrathin section and the bias in the concentration estimation, can be obtained. Some practical examples are given for the estimation of the iron concentration in siderosomes, boron in melanosomes and calcium in calcium oxalate monohydrate crystals

Analytical transmission electron microscopy at organic interfaces

Organic materials are ubiquitous in all aspects of our daily lives. Increasingly there is a need to understand interactions between different organic phases, or between organic and inorganic materials (hybrid interfaces), in order to gain fundamental knowledge about the origin of their structural and functional properties. In order to understand the complex structure–property–processing relationships in (and between) these materials, we need tools that combine high chemical sensitivity with high spatial resolution to allow detailed interfacial characterisation. Analytical transmission electron microscopy (TEM) is a powerful and versatile technique that can fulfil both criteria. However, the application of analytical TEM to organic systems presents some unique challenges, such as low contrast between phases, and electron beam sensitivity. In this review recent analytical TEM approaches to the nanoscale characterisation of two systems will be discussed: the hybrid collagen/mineral interface in bone, and the all-organic donor/acceptor interface in OPV devices