Electron Energy-loss Spectroscopy Spectrum Imaging Research Articles

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

Visualization of oxygen vacancies at CeO x /Y-HZO interface by spectrum imaging method and multivariate analysis

Electron energy loss spectroscopy—spectrum imaging measurements using a scanning transmission electron microscope are carried out to clarify the details of microstructure at the interface of the CeO x -capped Y-HZO film prepared by the chemical solution deposition (CSD) method. We confirmed that by the present CSD the independent capped layer of CeOx successively deposited on Y-HZO. The crystal structure of CeO x film is mainly the cubic CeO2 structure with Ce4+. Chemical state maps are also successfully obtained by the multivariate analysis. We found that Ce3+ and Ce4+ coexist in the interface layer with cubic CeO2 crystal structure containing O vacancy. The results of the quantitative elemental distribution maps of energy dispersive X-ray spectroscopy also supported that O vacancies exist at the interface.

Detection of ferric iron in an exsolved lunar pyroxene using electron energy loss spectroscopy (EELS): Implications for space weathering and redox conditions on the Moon

AbstractTo shed light on the mechanism of formation of nanophase iron particles (npFe) in space‐weathered materials from airless bodies, we analyzed exsolved and unexsolved space‐weathered lunar pyroxenes from Apollo 17 sample 71501. The exsolved pyroxene allowed for the observation of the effects of space weathering on similar mineral phases with variable composition. Using coordinated scanning transmission electron microscopy with energy‐dispersive X‐ray spectroscopy and electron energy loss spectroscopy (EELS), we determined that two coexisting pyroxenes in the exsolved grain showed systematic variations in response to space weathering, despite equivalent exposure conditions. The npFe in the space‐weathered rim of augite lamellae were smaller and fewer than the npFe in the rim of pigeonite lamellae. EELS spectrum imaging revealed the presence and heterogeneous distribution of Fe0, Fe2+, and Fe3+ in the exsolved pyroxene. Metallic iron occurred in the npFe, a mixture of Fe2+ and Fe3+ occurred in the pigeonite lamellae, and the augite lamellae contained virtually all Fe3+. Approximately 50% of the total Fe measured in the exsolved pyroxene grain was ferric. Partitioning of Fe2+ and Fe3+ among the lamellae is invoked to explain the difference in npFe development in pigeonite and augite. The results of this study, the first to identify Fe3+ in a crystalline lunar ferromagnesian silicate, have implications for our understanding of how space weathering might proceed in oxidized phases. Furthermore, the discovery of an Fe3+‐rich pyroxene also supports attribution of the 0.7 μm absorption feature observed in Galileo Solid State Imager data to oxidized Fe in clinopyroxenes.

Applications of a novel electron energy filter combined with a hybrid-pixel direct electron detector for the analysis of functional oxides by STEM/EELS and energy-filtered imaging

The performance and suitability of a new electron energy filter in combination with a hybrid pixel, direct electron detector for analytical (scanning) transmission electron microscopy are demonstrated using four examples. The STEM-EELS capabilities of the CEOS Energy Filtering and Imaging Device (CEFID) were tested with focus on weak signals and high spatio-temporal resolution. A multiferroic, multilayer structure of REMnO3 (RE = Yb, Er, Tb, Y), grown on yttria-stabilized zirconia (YSZ), is used to exemplify that this new instrumental setup produces valuable electron energy-loss spectroscopy (EELS) data at high energy losses even when using short acquisition times, providing detailed chemical information about the interfaces in this complex multilayer sample. Another functional oxide, namely a ferromagnetic La2NiMnO6 thin film grown on SrTiO3, demonstrates that atomically resolved spectrum images can be recorded, using short dwell times and moderate beam currents in order to warrant the integrity of the sample. In a third example, inhomogeneously Er-doped YSZ shows by EELS spectrum imaging that elements at low concentrations can be detected semi-quantitatively, uncovering the expected layered Er distribution but revealing substantial interdiffusion. In a final example, we simply demonstrate that the hybrid pixel detector in combination with the energy filter can also be used for energy-filtered imaging and thus for elemental mapping complementary to EELS in scanning transmission mode.

Dimensionality reduction and unsupervised clustering for EELS-SI

A novel combination of machine learning algorithms is proposed for the differentiation of distinct spectra in a large electron energy loss spectroscopy spectrum image (EELS-SI) dataset. For clustering of the EEL spectra including similar fine structures in an efficient space, linear and nonlinear dimensionality reduction methods are used to project the EEL spectra onto a low-dimensional space. Then, a density-based clustering algorithm is applied to distinguish the meaningful data clusters. By applying this strategy to various experimental EELS-SI datasets, differentiation of several groups of EEL spectra representing specific fine structures was achieved. It is possible to investigate particular fine structures by averaging all of the spectra in each cluster. Also, the spatial distributions of each cluster in the scanning regions can be observed, which enables investigation of the locations of different fine structures in materials. This method does not require any prior knowledge, i.e., it is a data-driven analysis; therefore, it can be applied to any hyperspectral image.

On the thermal stability of mesoporous metal oxide systems decorated with metallic nanoparticles for gas sensing applications

Mesoporous metal oxide systems decorated with metallic nanoparticles are among the most studied functional materials for their applications as chemo-resistive gas sensors. The temperature at which such materials are supposed to operate as gas sensors in real working conditions for an optimum device sensitivity ranges around 150-300oC. In our work, SnO2 mesoporous systems have been prepared by solvothermal methods. As a method for tailoring the chemo-resistive properties, the obtained mesoporous matrix has been further decorated with metallic Fe nanoparticles by wet spraying methods. The as-prepared systems have been extensively investigated by analytical transmission electron microscopy using a JEOL ARM200F instrument equipped with X-ray Energy Dispersive and Electron Energy Loss spectrometers (EDS/EELS). Our work has been focused on the morphological and structural aspects of the above mentioned system under the influence of in-situ heating up to 550oC (a meaningful temperature from the point of view of sample preparation). The morpho-structural evolution with temperature has been emphasized by High Resolution Transmission Electron Microscopy (HRTEM), Selected Area Electron Diffraction (SAED), Scanning Transmission Electron Microscopy (STEM) and Electron Energy Loss Spectroscopy Spectrum Imaging (EELS-SI).

Reconstruction of Partially Sampled Multiband Images—Application to STEM-EELS Imaging

Electron microscopy has shown to be a very powerful tool to map the chemical nature of samples at various scales down to atomic resolution. However, many samples can not be analyzed with an acceptable signal-to-noise ratio because of the radiation damage induced by the electron beam. This is particularly crucial for electron energy loss spectroscopy (EELS), which acquires spectral-spatial data and requires high beam intensity. Since scanning transmission electron microscopes (STEM) are able to acquire data cubes by scanning the electron probe over the sample and recording a spectrum for each spatial position, it is possible to design the scan pattern and to sample only specific pixels. As a consequence, partial acquisition schemes are now conceivable, provided a reconstruction of the full data cube is conducted as a postprocessing step. This paper proposes two reconstruction algorithms for multiband images acquired by STEM-EELS which exploits the spectral structure and the spatial smoothness of the image. The performance of the proposed schemes is illustrated thanks to experiments conducted on a realistic phantom dataset as well as real EELS spectrum-images.

High efficiency core-loss EELS analyzing from the viewpoint of chemometrics

Electron energy–loss spectroscopy (EELS) equipped on a modern scanning transmission electron microscope is a powerful high resolution elemental analysis technique. However, the conventional method of extracting elemental information quantitatively from EELS spectra is non-trivial. In this article we tried to interpret EELS data from the viewpoint of chemometrics. An EELS spectrum image collected from a vicinal SiC/SiO2 interface was employed as an example. By analyzing the EELS data with sophisticated chemometrics methods, chemical components and elemental ratios of C/Si and O/Si across the interface were derived. Compared with conventional EELS analysis, the chemometrics methods gave more reliable and accurate results with higher calculation efficiency. The chemometrics analysis confirmed that the transition from SiC to SiO2 was chemically sharp, and the transition layer in the vicinal interface was a linear combination of SiC and SiO2. Chemometrics analysis can be a fast and robust complementary method for EELS analysis.

Characterization of carbon nanostructures in Al and Ag covetic alloys

Electrocharging assisted process is a method for the incorporation of carbon in molten metals under high electric current which results in the formation of networks of carbon nanostructures inside the metal matrix, and gives the new material improved mechanical, electrical and thermal properties. Alloys produced with this method are called covetics. In our previous works, different characterization techniques such X-ray photoelectron spectroscopy (XPS), Raman, X-ray diffraction (XRD), transmission electron microscopy (TEM) and electron energy loss spectroscopy (EELS) confirmed the presence of sp2 crystalline graphene nanoribbons and sheets in Ag and Al-covetic samples. Here, we report on detailed Raman mapping and characterization of Al-6061, Al-7075 and Ag covetics to further investigate the fraction of sp2/sp3 bonding, strain, defects, degree of oxidation, and crystalline sizes of the graphene nanoribbons. Gradual changes of strain are observed in regions with sp2 bonding and some degree of amorphous carbon is revealed by Raman scattering. Different degrees of oxidation of the carbon nanostructures with mostly sp2 bonding are evident by EELS spectrum imaging. Atomic force microscopy (AFM) and Kelvin probe force microscopy (KPFM) also reveal the presence of graphene ribbons and sheets with different lengths and conductivity.

Automated background subtraction technique for electron energy-loss spectroscopy and application to semiconductor heterostructures.

Electron energy-loss spectroscopy (EELS) has become a standard tool for identification and sometimes also quantification of elements in materials science. This is important for understanding the chemical and/or structural composition of processed materials. In EELS, the background is often modelled using an inverse power-law function. Core-loss ionization edges are superimposed on top of the dominating background, making it difficult to quantify their intensities. The inverse power-law has to be modelled for each pre-edge region of the ionization edges in the spectrum individually rather than for the entire spectrum. To achieve this, the prerequisite is that one knows all core losses possibly present. The aim of this study is to automatically detect core-loss edges, model the background and extract quantitative elemental maps and profiles of EELS, based on several EELS spectrum images (EELS SI) without any prior knowledge of the material. The algorithm provides elemental maps and concentration profiles by making smart decisions in selecting pre-edge regions and integration ranges. The results of the quantification for a semiconductor thin film heterostructure show high chemical sensitivity, reasonable group III/V intensity ratios but also quantification issues when narrow integration windows are used without deconvolution.

Nitrogen Nanobubbles in a-SiOxNy Coatings: Evaluation of Its Physical Properties and Chemical Bonding State by Spatially Resolved Electron Energy-Loss Spectroscopy

Nanoporous silicon-based materials with closed porosity filled with the sputtering gas have been recently developed by magnetron sputtering. In this work the physical properties (density and pressure) of molecular nitrogen inside closed pores in a SiOxNy coating are investigated for the first time using spatially resolved electron energy-loss spectroscopy (EELS) in a scanning transmission electron microscope. The paper offers a detailed methodology to record and process multiple EELS spectrum images (SIs) acquired at different energy ranges and with different dwell times. An adequate extraction and quantification of the N–K edge contribution due to the molecular nitrogen inside nanopores is demonstrated. Core-loss intensity and N chemical bond state were evaluated to retrieve 2D maps revealing the stable high density of molecular nitrogen (from 40 to 70 at./nm3) in nanopores of different size (20–11 nm). This work provides new insights into the quantification of molecular N2 trapped in porous nitride matr...

Quantitative parameters for the examination of InGaN QW multilayers by low-loss EELS.

We present a detailed examination of a multiple InxGa1-xN quantum well (QW) structure for optoelectronic applications. The characterization is carried out using scanning transmission electron microscopy (STEM), combining high-angle annular dark field (HAADF) imaging and electron energy loss spectroscopy (EELS). Fluctuations in the QW thickness and composition are observed in atomic resolution images. The impact of these small changes on the electronic properties of the semiconductor material is measured through spatially localized low-loss EELS, obtaining band gap and plasmon energy values. Because of the small size of the InGaN QW layers additional effects hinder the analysis. Hence, additional parameters were explored, which can be assessed using the same EELS data and give further information. For instance, plasmon width was studied using a model-based fit approach to the plasmon peak; observing a broadening of this peak can be related to the chemical and structural inhomogeneity in the InGaN QW layers. Additionally, Kramers-Kronig analysis (KKA) was used to calculate the complex dielectric function (CDF) from the EELS spectrum images (SIs). After this analysis, the electron effective mass and the sample absolute thickness were obtained, and an alternative method for the assessment of plasmon energy was demonstrated. Also after KKA, the normalization of the energy-loss spectrum allows us to analyze the Ga 3d transition, which provides additional chemical information at great spatial resolution. Each one of these methods is presented in this work together with a critical discussion of their advantages and drawbacks.

Electron energy-loss spectroscopic tomography of FexCo(3-x)O4 impregnated Co3O4 mesoporous particles: unraveling the chemical information in three dimensions.

Electron energy-loss spectroscopy-spectrum image (EELS-SI) tomography is a powerful tool to investigate the three dimensional chemical configuration in nanostructures. Here, we demonstrate, for the first time, the possibility to characterize the spatial distribution of Fe and Co cations in a complex FexCo(3-x)O4/Co3O4 ordered mesoporous system. This hybrid material is relevant because of the ferrimagnetic/antiferromagnetic coupling and high surface area. We unambiguously prove that the EELS-SI tomography shows a sufficiently high resolution to simultaneously unravel the pore structure and the chemical signal.

A multi-method study of the transformation of the carbonaceous skeleton of a polymer-based nanoporous carbon along the activation pathway

The change in the carbonaceous skeleton of nanoporous carbons during their activation has received limited attention, unlike its counterpart process in the presence of an inert atmosphere. Here we adopt a multi-method approach to elucidate this change in a poly(furfuryl alcohol)-derived carbon activated using cyclic application of oxygen saturation at 250°C before its removal (with carbon) at 800°C in argon. The methods used include helium pycnometry, synchrotron-based X-ray diffraction (XRD) and associated radial distribution function (RDF) analysis, transmission electron microscopy (TEM) and, uniquely, electron energy-loss spectroscopy spectrum-imaging (EELS-SI), electron nanodiffraction and fluctuation electron microscopy (FEM). Helium pycnometry indicates the solid skeleton of the carbon densifies during activation from 78% to 93% of graphite. RDF analysis, EELS-SI, and FEM all suggest this densification comes through an in-plane growth of sp2 carbon out to the medium range without commensurate increase in order normal to the plane. This process could be termed ‘graphenization’. The exact way in which this process occurs is not clear, but TEM images of the carbon before and after activation suggest it may come through removal of the more reactive carbon, breaking constraining cross-links and creating space that allows the remaining carbon material to migrate in an annealing-like process.

Monochromated Electron Energy-Loss Spectroscopy Spectrum Imaging of Organic Photovoltaic Devices

Monochromated Electron Energy-Loss Spectroscopy Spectrum Imaging of Organic Photovoltaic Devices

Synthesis and Understanding of Layered Li-Rich Nickel Manganese Oxides for High Energy Density Lithium-Ion Batteries

In the search for high capacity cathode materials for Li-ion batteries, layered oxides with the general formula Li(LiXMnYMZ)O2 (M=Ni, Mn, Mg, ...) either described as xLi2MnO3 · yLiMO2 are receiving much attention. These oxides are characterised by the presence of lithium in the transition metal layers, and high Mn content, leading to high capacities up to 250mAh.g-1. However, upon cycling, they present complex structural changes that are still misunderstood. In this context, our group worked jointly on synthesis development and understanding of the structure evolution occurring into the lithium rich layered cathode material Li1.2Mn0.61Ni0.18Mg0.01O2.The first step was to study one material synthesized using a solid state route. 1st cycle characterization was investigated by XANES, in situ XRD and SQUID magnetic measurements. We showed that the main first-charge plateau is a twophase process where a new phase is created. This extra phase apparition was confirmed by Electron Energy Loss Spectroscopy (EELS) spectra interpretation. Therefore, Squid magnetic measurements allow a 1st cycle mechanism proposition.Evolutions after cycling test (50 cycles) have also been investigated using advanced microscopy tools (High Resolution STEM EELS spectrum imaging). The stability of the spinel defect structure is pointed out to explain the material ageing and the electrochemical performances decrease on cycling.Others synthesis routes were developed, especially solvothermal way enabling a better primary particles size, composition and morphology control. This synthesis route depends on many input parameters such as pH, temperature, duration… We used the methodology of the design of experiments that allows minimizing the number of experiences to optimize the synthesis and understand the effect of the main parameters of the synthesis. Higher performances and cycling behaviour have been obtained and further understanding studies are under progress to match with experimental observations.

Synthesis and Understanding of Layered Li-Rich Nickel Manganese Oxides for High Voltage Lithium Ion Batteries

In the search for high capacity cathode materials for Li-ion batteries, layered oxides with the general formula Li(LiXMnYMZ)O2 (M=Ni, Mn, Mg, ...) either described as xLi2MnO3 · yLiMO2 are receiving much attention. These oxides are characterised by the presence of lithium in the transition metal layers, and high Mn content, leading to high capacities up to 250mAh.g-1. However, upon cycling, they present complex structural changes that are still misunderstood. In this context, our group worked jointly on synthesis development and understanding of the structure evolution occurring into the lithium rich layered cathode material Li1.2Mn0.61Ni0.18Mg0.01O2.The first step was to study one material synthesized using a solid state route. 1st cycle characterization was investigated by XANES, in situ XRD and SQUID magnetic measurements. We showed that the main first-charge plateau is a twophase process where a new phase is created. This extra phase apparition was confirmed by Electron Energy Loss Spectroscopy (EELS) spectra interpretation. Therefore, Squid magnetic measurements allow a 1st cycle mechanism proposition.Evolutions after cycling test (50 cycles) have also been investigated using advanced microscopy tools (High Resolution STEM EELS spectrum imaging). The stability of the spinel defect structure is pointed out to explain the material ageing and the electrochemical performances decrease on cycling.Others synthesis routes were developed, especially solvothermal way enabling a better primary particles size, composition and morphology control. Higher performances and cycling behaviour have been obtained and further understanding studies are under progress to match with experimental observations.

EELS tomography in multiferroic nanocomposites: from spectrum images to the spectrum volume.

Electron Energy Loss Spectroscopy (EELS) in a transmission electron microscope offers the possibility of extracting high accuracy maps of composition and electronic properties through EELS spectrum images (EELS-SI). Acquiring EELS-SI for different tilt angles, a 3D tomographic reconstruction of EELS information can be achieved. In the present work we show that an EELS spectrum volume (EELS-SV), a 4D dataset where every voxel contains a full EELS spectrum, can be reconstructed from the EELS-SI tilt series by the application of multivariate analysis. We apply this novel approach to characterize a nanocomposite material consisting of CoFe2O4 nanocolumns embedded in a BiFeO3 matrix grown on a LaNiO3 buffered LaAlO3 (001) substrate.

Insight into the Compositional and Structural Nano Features of AlN/GaN DBRs by EELS-HAADF

III-V nitride (AlGa)N distributed Bragg reflector devices are characterized by combined high-angle annular dark-field (HAADF) and electron energy loss spectroscopy (EELS) in the scanning transmission electron microscope. Besides the complete structural characterization of the AlN and GaN layers, the formation of AlGaN transient layers is revealed using Vegard law on profiles of the position of the bulk plasmon peak maximum. This result is confirmed by comparison of experimental and simulated HAADF intensities. In addition, we present an advantageous method for the characterization of nano-feature structures using low-loss EELS spectrum image (EEL-SI) analysis. Information from the materials in the sample is extracted from these EEL-SI at high spatial resolution.The log-ratio formula is used to calculate the relative thickness, related to the electron inelastic mean free path. Fitting of the bulk plasmon is performed using a damped plasmon model (DPM) equation. The maximum of this peak is related to the chemical composition variation using the previous Vegard law analysis. In addition, within the context of the DPM, information regarding the structural properties of the material can be obtained from the lifetime of the oscillation. Three anomalous segregation regions are characterized, revealing formation of metallic Al islands.

Removing the effects of elastic and thermal scattering from electron energy-loss spectroscopic data

Electron energy-loss spectroscopy (EELS) studies in scanning transmission electron microscopy are widely used to investigate the location and bonding of atoms in condensed matter. However, the interpretation of EELS data is complicated by multiple elastic and thermal diffuse scattering of the probing electrons. Here, we present a method for removing these effects from recorded EELS spectrum images, producing visually interpretable elemental maps and enabling direct comparison of the spectral data with established first-principles energy-loss fine structure calculations.