A “Thickness Series”: Weak Signal Extraction of ELNES in EELS Spectra From Surfaces

Zhu, Guo‐zhen; Botton, Gianluigi A.

doi:10.1017/s1431927613013676

Cited by 4 publications

(6 citation statements)

References 23 publications

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“…Also shown in figure 7 is the spectrum for a subsurface oxygen atom, this spectrum shows significant differences from the spectrum of the bridging atom: there is a reduction in intensity of the first peak relative to the second and an increase in peak separation. Together these changes should make it possible to resolve between surface and bulk spectra using a method like that in [6]. In [6] a series of elec tron energy loss spectra were taken through areas of a sample with differing thickness and therefore differing contributions of the bulk to the recorded spectrum.…”

Section: Anatase Surfacesmentioning

confidence: 99%

“…Together these changes should make it possible to resolve between surface and bulk spectra using a method like that in [6]. In [6] a series of elec tron energy loss spectra were taken through areas of a sample with differing thickness and therefore differing contributions of the bulk to the recorded spectrum. A principal components method was then used separate the surface contribution to the spectra.…”

Section: Anatase Surfacesmentioning

confidence: 99%

“…As well as positional information on dopants and impurities, information about the local chemical environment [1,2] of an atom may be obtained, including oxidation state [3,4] and coordination of individual atoms [5]. Signatures from surfaces may also be extracted [6].…”

Section: Introductionmentioning

confidence: 99%

“…Figure 7.Predicted oxygen K edge spectra of surface and bulk atoms in a perfect anatase (1 0 1) slab. The differences between these spectra may be sufficient to resolve the surface signal experimentally using a method similar to that described in[6]. The subsurface atom used was one of those directly below a surface bridging oxygen: it occupied the same position as the 'def' atom did prior to relaxation.…”

mentioning

confidence: 99%

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Simulation of electron energy loss spectra of nanomaterials with linear-scaling density functional theory

Tait¹,

Ratcliff

Payne³

et al. 2016

J. Phys.: Condens. Matter

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Experimental techniques for electron energy loss spectroscopy (EELS) combine high energy resolution with high spatial resolution. They are therefore powerful tools for investigating the local electronic structure of complex systems such as nanostructures, interfaces and even individual defects. Interpretation of experimental electron energy loss spectra is often challenging and can require theoretical modelling of candidate structures, which themselves may be large and complex, beyond the capabilities of traditional cubic-scaling density functional theory. In this work, we present functionality to compute electron energy loss spectra within the onetep linear-scaling density functional theory code. We first demonstrate that simulated spectra agree with those computed using conventional plane wave pseudopotential methods to a high degree of precision. The ability of onetep to tackle large problems is then exploited to investigate convergence of spectra with respect to supercell size. Finally, we apply the novel functionality to a study of the electron energy loss spectra of defects on the (1 0 1) surface of an anatase slab and determine concentrations of defects which might be experimentally detectable.

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Section: Anatase Surfacesmentioning

confidence: 99%

Section: Anatase Surfacesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Simulation of electron energy loss spectra of nanomaterials with linear-scaling density functional theory

Tait¹,

Ratcliff

Payne³

et al. 2016

J. Phys.: Condens. Matter

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show abstract

“…(Lest we appear to be making too much of the method, it has been shown to have weak sensitivity to atomic column displacements [31] and, as He et al [34] caution, the number of reference simulations and thus computation time increases dramatically if one seeks to estimate multiple structural quantities simultaneously.) The dependence on thickness means that, for known structures, comparison against simulations allows the sample thickness to be determined [8,11,14,27,[35][36][37][38][39]. 1 The essence of this approach is illustrated in Fig.…”

Section: Introductionmentioning

confidence: 99%

Accuracy and precision of thickness determination from position-averaged convergent beam electron diffraction patterns using a single-parameter metric

et al. 2017

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Analytical Electron Microscopy

Botton¹,

Prabhudev²

2019

Springer Handbook of Microscopy

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Analytical electron microscopy (AEM) refers to a collection of spectroscopic techniques that are capable of providing structural, compositional, and bonding information about samples probed by an electron beam, typically inside a transmission electron microscope (TEM). Several AEM techniques are covered with particular attention given to the EDXS (energy-dispersive x-ray spectroscopy) microanalysis and EELS (electron energyloss spectroscopy) techniques. First, the different AEM techniques available in TEMs are surveyed and a parallel between EELS and EDXS is drawn. A fundamental description of the elastic and inelastic scattering events responsible for these signals is presented. The practical challenges related to electron optics and instrumentation capabilities are then discussed. Technical advances that have affected the performance of these AEM techniques are outlined, including successive generations and technologies of energy filters, monochromators, aberration correctors, and advanced energydispersive x-ray spectrometers. The different approaches of spectroscopic imaging with x-rays and energy-loss spectroscopy, the resolution limits, and the effects of electron-beam propagation are also described along with the types of information that can be extracted with electron-energyloss near-edge structures. After a review of dielectric theory and low-loss spectroscopy, examples of plasmonic imaging are presented. The review also draws attention to the many efforts to extend the limits of spatial resolution and the atomic-level chemical analyses of materials. Some important progress in the statistical analysis of signals and associated numerical methods is mentioned. The review also presents some novel developments in image capture, such as the pixelated detectors. Finally, the realm of phonon spectroscopy made possible through the latest instrumentation is also discussed.

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A “Thickness Series”: Weak Signal Extraction of ELNES in EELS Spectra From Surfaces

Cited by 4 publications

References 23 publications

Simulation of electron energy loss spectra of nanomaterials with linear-scaling density functional theory

Simulation of electron energy loss spectra of nanomaterials with linear-scaling density functional theory

Accuracy and precision of thickness determination from position-averaged convergent beam electron diffraction patterns using a single-parameter metric

Analytical Electron Microscopy

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