Accurate EELS background subtraction – an adaptable method in MATLAB

Electron energy-loss spectroscopy (EELS) is a technique that can give useful information on elemental composition and bonding environments. However in practice, the complexity of the background contributions, which can arise from multiple sources, can hamper the interpretation of the spectra. As a result, background removal is both an essential and difficult part of EELS analysis, especially during quantification of elemental composition. Typically, a power law is used to fit the background but this is often not suitable for many spectra such as in the low-loss region (< 50 eV) and when there are overlapping EELS edges. In this article, we present a series of scripts written in MATLAB v. R2019b that aims to provide statistical information on the model used to fit the background, allowing the user to determine the accuracy of background subtraction. The scripts were written for background subtraction of vibrational EELS in the ultralow-loss region near the zero-loss peak but can also be applied to other kinds of EEL spectra. The scripts can use a range of models for fitting, provided by the Curve Fitting Toolbox of MATLAB, and the user is able to precisely define the window for fitting as well as for edge integration. We demonstrate the advantages of using these scripts by comparing their background subtraction of example spectra to the most commonly used software, Gatan Microscopy Suite 3. The example spectra include those containing multiple scattering, multiple overlapping peaks, as well as vibrational EELS. Additionally, a comprehensive guide to using the scripts has been included in the Supplementary Information

Isotopic compositions, nitrogen functional chemistry, and low‐loss electron spectroscopy of complex organic aggregates at the nanometer scale in the carbonaceous chondrite Renazzo

Organic matter (OM) was widespread in the early solar nebula and might have played an important role for the delivery of prebiotic molecules to the early Earth. We investigated the textures, isotopic compositions, and functional chemistries of organic grains in the Renazzo carbonaceous chondrite by combined high spatial resolution techniques (electron microscopy–secondary ion mass spectrometry). Morphologies are complex on a submicrometer scale, and some organics exhibit a distinct texture with alternating layers of OM and minerals. These layered organics are also characterized by heterogeneous 15N isotopic abundances. Functional chemistry investigations of five focused ion beam‐extracted lamellae by electron energy loss spectroscopy reveal a chemical complexity on a nanometer scale. Grains show absorption at the C‐K edge at 285, 286.6, 287, and 288.6 eV due to polyaromatic hydrocarbons, different carbon‐oxygen, and aliphatic bonding environments with varying intensity. The nitrogen K‐edge functional chemistry of three grains is shown to be highly complex, and we see indications of amine (C‐NHx) or amide (CO‐NR2) chemistry as well as possible N‐heterocycles and nitro groups. We also performed low‐loss vibrational spectroscopy with high energy resolution and identified possible D‐ and G‐bands known from Raman spectroscopy and/or absorption from C=C and C‐O stretch modes known from infrared spectroscopy at around 0.17 and 0.2 eV energy loss. The observation of multiglobular layered organic aggregates, heterogeneous 15N‐anomalous compositions, and indication of NHx‐(amine) functional chemistry lends support to recent ideas that 15N‐enriched ammonia (NH3) was a powerful agent to synthesize more complex organics in aqueous asteroidal environments

Machine Learning Data Augmentation Strategy for Electron Energy Loss Spectroscopy : Generative Adversarial Networks

Recent advances in machine learning (ML) have highlighted a novel challenge concerning the quality and quantity of data required to effectively train algorithms in supervised ML procedures. This article introduces a data augmentation (DA) strategy for electron energy loss spectroscopy (EELS) data, employing generative adversarial networks (GANs). We present an innovative approach, called the data augmentation generative adversarial network (DAG), which facilitates data generation from a very limited number of spectra, around 100. Throughout this study, we explore the optimal configuration for GANs to produce realistic spectra. Notably, our DAG generates realistic spectra, and the spectra produced by the generator are successfully used in real-world applications to train classifiers based on artificial neural networks (ANNs) and support vector machines (SVMs) that have been successful in classifying experimental EEL spectra

Confined magnon dispersion in ferromagnetic and antiferromagnetic thin films in a second quantization approach: the case of Fe and NiO

We present a methodology based on the calculation of the inelastic scattering from magnons via the spin scattering function in confined geometries such as thin films using a second quantization formalism, for both ferromagnetic and antiferromagnetic materials. The case studies are chosen with an aim to demonstrate the effects of film thickness and crystal orientation on magnon modes, using bcc Fe(100) and NiO with (100) and (111) crystallographic orientations as prototypical systems. Due to the quantization of the quasi-momentum we observe a granularity in the inelastic spectra in the reciprocal space path reflecting the orientation of the thin film. This approach also allows to capture softer modes that appear due to the partial interaction of magnetic moments close to the surface in a thin film geometry, in addition to bulk modes. The softer modes are also affected by crystallographic orientations as illustrated by the different surface-related peaks of NiO magnon density of states at approximately ~ 65 meV for (100) and ~ 42 meV for (111). Additionally, we explore the role of anisotropy on magnon modes, revealing that introducing anisotropy to both Fe and NiO films increases the overall hardness of the magnon modes. The introduction of a surface anisotropy produces a shift of the surface-related magnon DOS peak to higher energies with increased surface anisotropy, and in some cases leading to surface confined mode

Atomic-Scale Spectroscopic Imaging of the Extreme-UV Optical Response of B- and N-Doped Graphene

Abstract Substitutional doping of graphene by impurity atoms such as boron and nitrogen, followed by atom-by-atom manipulation via scanning transmission electron microscopy, can allow for accurate tailoring of its electronic structure, plasmonic response, and even the creation of single atom devices. Beyond the identification of individual dopant atoms by means of ?Z contrast? imaging, spectroscopic characterization is needed to understand the modifications induced in the electronic structure and plasmonic response. Here, atomic scale spectroscopic imaging in the extreme UV-frequency band is demonstrated. Characteristic and energy-loss-dependent contrast changes centered on individual dopant atoms are highlighted. These effects are attributed to local dopant-induced modifications of the electronic structure and are shown to be in excellent agreement with calculations of the associated densities of states

Theory of momentum-resolved magnon electron energy loss spectra: The case of Yttrium Iron Garnet

We explore the inelastic spectra of electrons impinging in a magnetic system. The methodology here presented is intended to highlight the charge-dependent interaction of the electron beam in a STEM-EELS experiment, and the local vector potential generated by the magnetic lattice. This interaction shows an intensity $10^{-2}$ smaller than the purely spin interaction, which is taken to be functionally the same as in the inelastic neutron experiment. On the other hand, it shows a strong scattering vector dependence ($\kappa^{-4}$) and a dependence with the relative orientation between the probe wavevector and the local magnetic moments of the solid. We present YIG as a case study due to its high interest by the community

Mapping grain boundary heterogeneity at the nanoscale in a positive temperature coefficient of resistivity ceramic

Despite being of wide commercial use in devices, the orders of magnitude increase in resistance that can be seen in some semiconducting BaTiO3-based ceramics, on heating through the Curie temperature (TC), is far from well understood. Current understanding of the behavior hinges on the role of grain boundary resistance that can be modified by polarization discontinuities which develop in the ferroelectric state. However, direct nanoscale resistance mapping to verify this model has rarely been attempted, and the potential approach to engineer polarization states at the grain boundaries, that could lead to optimized positive temperature coefficient (PTC) behavior, is strongly underdeveloped. Here we present direct visualization and nanoscale mapping in a commercially optimized BaTiO3-PbTiO3-CaTiO3 PTC ceramic using Kelvin probe force microscopy, which shows that, even in the low resistance ferroelectric state, the potential drop at grain boundaries is significantly greater than in grain interiors. Aberration-corrected scanning transmission electron microscopy and electron energy loss spectroscopy reveal new evidence of Pb-rich grain boundaries symptomatic of a higher net polarization normal to the grain boundaries compared to the purer grain interiors. These results validate the critical link between optimized PTC performance and higher local polarization at grain boundaries in this specific ceramic system and suggest a novel route towards engineering devices where an interface layer of higher spontaneous polarization could lead to enhanced PTC functionality

Self-Nano-Structuring in SrTiO₃: A Novel Strategy for Enhancement of Thermoelectric Response in Oxides

Nanostructuring is recognized as an efficient route for enhancing thermoelectric response. Here, we report a new synthesis strategy for nanostructuring oxide ceramics and demonstrate its effectiveness on an important n-type thermoelectric SrTiO3. Ceramics of Sr0.9La0.1TiO3 with additions of B2O3 were synthesized by the mixed oxide route. Samples were sintered in air followed by annealing in a reducing atmosphere. Crystallographic data from X-ray and electron diffraction showed Pm3̅m cubic symmetry for all the samples. High-resolution transmission electron microscopy (HRTEM) showed the formation of a core–shell type structure within the grains for the annealed ceramics. The cores contain nanosize features comprising pairs of nanosize voids and particles; the feature sizes depend on annealing time. Atomic-resolution, high-angle annular-dark-field imaging and electron energy loss spectroscopy in the scanning transmission electron microscopy (STEM-HAADF-EELS) showed the particles to be rich in Ti and the areas around the voids to contain high concentrations of Ti3+. Additionally, dislocations were observed, with significantly higher densities in the shell areas. The observed dislocations are combined (100) and (110) edge dislocations. The major impact of the core–shell type microstructures, with nanosize inclusions, is the reduction of the thermal conductivity. Sr0.9La0.1TiO3 ceramics containing grain boundary shells of size ≈ 1 μm and inclusions in the core of 60–80 nm exhibit a peak power factor of 1600 μW/m·K2 at 540 K; at 1000 K, they exhibit a low thermal conductivity (2.75 W/m·K) and a power factor of 1050 μW/m·K2 leading to a high of ZT of 0.39 ± 0.03. This is the highest ZT reported so far for Sr0.9La0.1TiO3 based-compositions. This nanostructuring strategy should be readily applicable to other functional oxides

Unveiling the impact of temperature on magnon diffuse scattering detection in scanning transmission electron microscopy

Magnon diffuse scattering (MDS) signals could be studied with high spatial resolution in scanning transmission electron microscopy (STEM), thanks to recent technological progress in electron energy loss spectroscopy. However, detecting MDS signals in STEM is challenging due to their overlap with the stronger thermal diffuse scattering (TDS) signals. In bcc Fe at 300~K, MDS signals greater than or comparable to TDS signals occur under the central Bragg disk, into a currently inaccesible energy-loss region. Therefore, to detect MDS in STEM, it is necessary to identify conditions in which TDS and MDS signals can be distinguished from one another. Temperature may be a key factor due to the distinct thermal signatures of magnon and phonon signals. In this work, we present a study on the effects of temperature on MDS and TDS in bcc Fe -- considering a detector outside the central Bragg disk -- using the frozen phonon and frozen magnon multislice methods. Our study reveals that neglecting the effects of atomic vibrations causes the MDS signal to grow approximately linearly up to the Curie temperature of Fe, after which it exhibits less variation. The MDS signal displays an alternating behavior due to dynamical diffraction, instead of increasing monotonically as a function of thickness. The inclusion of the Debye-Waller factor (DWF) causes the linear growth of the MDS signal to change to an oscillatory behavior that exhibits a predominant peak for each thickness, which increases and shifts to higher temperatures as the thickness increases. In contrast, the TDS signal grows more linearly than the MDS signal (with DWF) but still exhibits dynamical diffraction effects. An analysis of the signal-to-noise ratio (SNR) shows that the MDS signal can be a statistically significant contribution to the total scattering intensity under realistic measurement conditions and reasonable acquisition times

Functional group mapping by electron beam vibrational spectroscopy from nanoscale volumes

Vibrational spectroscopies directly record details of bonding in materials, but spatially resolved methods have been limited to surface techniques for mapping functional groups at the nanoscale. Electron energy loss spectroscopy (EELS) in the scanning transmission electron microscope presents a route to functional group analysis from nanoscale volumes using transmitted subnanometer electron probes. Here, we now use vibrational EELS to map distinct carboxylate and imidazolate linkers in a metal–organic framework (MOF) crystal–glass composite material. Domains <100 nm in size are observed using vibrational EELS, with recorded spatial resolution <15 nm at interfaces in the composite. This nanoscale functional group mapping is confirmed by correlated EELS at core ionization edges as well as X-ray energy dispersive spectroscopy for elemental mapping of the metal centers of the two constituent MOFs. These results present a complete nanoscale analysis of the building blocks of the MOF composite and establish spatially resolved functional group analysis using electron beam spectroscopy for crystalline and amorphous organic and metal–organic solids