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.

Strategies for EELS Data Analysis. Introducing UMAP and HDBSCAN for Dimensionality Reduction and Clustering.

Hierarchical density-based spatial clustering of applications with noise (HDBSCAN) and uniform manifold approximation and projection (UMAP), two new state-of-the-art algorithms for clustering analysis, and dimensionality reduction, respectively, are proposed for the segmentation of core-loss electron energy loss spectroscopy (EELS) spectrum images. The performances of UMAP and HDBSCAN are systematically compared to the other clustering analysis approaches used in EELS in the literature using a known synthetic dataset. Better results are found for these new approaches. Furthermore, UMAP and HDBSCAN are showcased in a real experimental dataset from a core­shell nanoparticle of iron and manganese oxides, as well as the triple combination nonnegative matrix factorization­UMAP­HDBSCAN. The results obtained indicate how the complementary use of different combinations may be beneficial in a real-case scenario to attain a complete picture, as different algorithms highlight different aspects of the dataset studied.

Direct Evidence of a Graded Magnetic Interface in Bimagnetic Core/Shell Nanoparticles Using Electron Magnetic Circular Dichroism (EMCD).

Interfaces play a crucial role in composite magnetic materials and particularly in bimagnetic core/shell nanoparticles. However, resolving the microscopic magnetic structure of these nanoparticles is rather complex. Here, we investigate the local magnetization of antiferromagnetic/ferrimagnetic FeO/Fe3O4 core/shell nanocubes by electron magnetic circular dichroism (EMCD). The electron energy-loss spectroscopy (EELS) compositional analysis of the samples shows the presence of an oxidation gradient at the interface between the FeO core and the Fe3O4 shell. The EMCD measurements show that the nanoparticles are composed of four different zones with distinct magnetic moment in a concentric, onion-type, structure. These magnetic areas correlate spatially with the oxidation and composition gradient with the magnetic moment being largest at the surface and decreasing toward the core. The results show that the combination of EELS compositional mapping and EMCD can provide very valuable information on the inner magnetic structure and its correlation to the microstructure of magnetic nanoparticles.

Atomic-Scale Determination of Cation Inversion in Spinel-Based Oxide Nanoparticles.

The atomic structure of nanoparticles can be easily determined by transmission electron microscopy. However, obtaining atomic-resolution chemical information about the individual atomic columns is a rather challenging endeavor. Here, crystalline monodispersed spinel Fe3O4/Mn3O4 core-shell nanoparticles have been thoroughly characterized in a high-resolution scanning transmission electron microscope. Electron energy-loss spectroscopy (EELS) measurements performed with atomic resolution allow the direct mapping of the Mn2+/Mn3+ ions in the shell and the Fe2+/Fe3+ in the core structure. This enables a precise understanding of the core-shell interface and of the cation distribution in the crystalline lattice of the nanoparticles. Considering how the different oxidation states of transition metals are reflected in EELS, two methods of performing a local evaluation of the cation inversion in spinel lattices are introduced. Both methods allow the determination of the inversion parameter in the iron oxide core and manganese oxide shell, as well as detecting spatial variations in this parameter, with atomic resolution. X-ray absorption measurements on the whole sample confirm the presence of cation inversion. These results present a significant advance toward a better correlation of the structural and functional properties of nanostructured spinel oxides.

Electrostatic-Driven Gelation of Colloidal Nanocrystals.

The assembly of colloidal nanocrystals (NCs) is a unique strategy to produce porous materials with high crystallinity and unmatched control over structural and chemical parameters. This strategy has been demonstrated mostly for single-component nanomaterials. In the present work, we report the gelation of colloidal NC solutions driven by the electrostatic interaction of oppositely charged NCs. A key step for leading this strategy to success is to produce a stable colloidal solution of the positively charged component. We achieved this goal by functionalizing the NCs with inexpensive and nontoxic amino acids such as glutamine. We demonstrate the combination of positively and negatively charged NCs in proper concentrations to result in gels with a homogeneous distribution of the two compounds. In this way, porous nanocomposites with virtually any combination can be produced. We illustrate this approach by combining positively charged ceria NCs with negatively charged gold NCs to form Au-CeO2 gels. These gels were dried from supercritical CO2 to produce highly porous Au-CeO2 aerogels with specific surface areas of 120 m2 g-1. The formation of a proper interface is confirmed through the evaluation of nanocomposite catalytic activity toward CO oxidation. We further demonstrate the versatility of this strategy to produce porous metal chalcogenide-metal oxide and metal-metal chalcogenide nanocomposites by the examples of PbS-CeO2 and Au-PbS.

Surface Chemistry and Nano-/Microstructure Engineering on Photocatalytic In2S3 Nanocrystals.

Colloidal nanocrystals (NCs) compete with molecular catalysts in the field of homogenous catalysis, offering easier recyclability and a number of potentially advantageous functionalities, such as tunable band gaps, plasmonic properties, or a magnetic moment. Using high-throughput printing technologies, colloidal NCs can also be supported onto substrates to produce cost-effective electronic, optoelectronic, electrocatalytic, and sensing devices. For both catalytic and technological application, NC surface chemistry and supracrystal organization are key parameters determining final performance. Here, we study the influence of the surface ligands and the NC organization on the catalytic properties of In2S3, both as a colloid and as a supported layer. As a colloid, NCs stabilized by inorganic ligands show the highest photocatalytic activities, which we associate with their large and more accessible surfaces. On the other hand, when NCs are supported on a substrate, their organization becomes an essential parameter determining performance. For instance, NC-based films produced through a gelation process provided five-fold higher photocurrent densities than those obtained from dense films produced by the direct printing of NCs.

Effects of electric current on individual graphene oxide sheets combining in situ transmission electron microscopy and Raman spectroscopy.

Graphene oxide (GO) is currently the object of extensive research because of its potential use in mass production of graphene-based materials, but also due to its tunability which holds great promise for new nanoscale electronic devices and sensors. To obtain a better understanding of the role of GO in electronic nano-devices, the elucidation of the effects of electrical current on a single GO sheet is of great interest. In this work, in situ transmission electron microscopy is used to study the effects of the electrical current flow through single GO sheets using an scanning tunneling microscope holder. In order to correlate the applied current with the structural properties of GO, Raman spectroscopy is carried out and data analysis is used to obtain information regarding the reduction grade and the disorder degree of the GO sheets before and after the application of current.

Acetate-Induced Disassembly of Spherical Iron Oxide Nanoparticle Clusters into Monodispersed Core-Shell Structures upon Nanoemulsion Fusion.

It has been long known that the physical encapsulation of oleic acid-capped iron oxide nanoparticles (OA-IONPs) with the cetyltrimethylammonium (CTA+) surfactant induces the formation of spherical iron oxide nanoparticle clusters (IONPCs). However, the behavior and functional properties of IONPCs in chemical reactions have been largely neglected and are still not well-understood. Herein, we report an unconventional ligand-exchange function of IONPCs activated when dispersed in an ethyl acetate/acetate buffer system. The ligand exchange can successfully transform hydrophobic OA-IONP building blocks of IONPCs into highly hydrophilic, acetate-capped iron oxide nanoparticles (Ac-IONPs). More importantly, we demonstrate that the addition of silica precursors (tetraethyl orthosilicate and 3-aminopropyltriethoxysilane) to the acetate/oleate ligand-exchange reaction of the IONPs induces the disassembly of the IONPCs into monodispersed iron oxide-acetate-silica core-shell-shell (IONPs@acetate@SiO2) nanoparticles. Our observations evidence that the formation of IONPs@acetate@SiO2 nanoparticles is initiated by a unique micellar fusion mechanism between the Pickering-type emulsions of IONPCs and nanoemulsions of silica precursors formed under ethyl acetate buffered conditions. A dynamic rearrangement of the CTA+-oleate bilayer on the IONPC surfaces is proposed to be responsible for the templating process of the silica shells around the individual IONPs. In comparison to previously reported methods in the literature, our work provides a much more detailed experimental evidence of the silica-coating mechanism in a nanoemulsion system. Overall, ethyl acetate is proven to be a very efficient agent for an effortless preparation of monodispersed IONPs@acetate@SiO2 and hydrophilic Ac-IONPs from IONPCs.

3D Visualization of the Iron Oxidation State in FeO/Fe3O4 Core-Shell Nanocubes from Electron Energy Loss Tomography.

The physicochemical properties used in numerous advanced nanostructured devices are directly controlled by the oxidation states of their constituents. In this work we combine electron energy-loss spectroscopy, blind source separation, and computed tomography to reconstruct in three dimensions the distribution of Fe(2+) and Fe(3+) ions in a FeO/Fe3O4 core/shell cube-shaped nanoparticle with nanometric resolution. The results highlight the sharpness of the interface between both oxides and provide an average shell thickness, core volume, and average cube edge length measurements in agreement with the magnetic characterization of the sample.

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.

Density Functional Theory Modeling of Low-Loss Electron Energy-Loss Spectroscopy in Wurtzite III-Nitride Ternary Alloys.

In the present work, the dielectric response of III-nitride semiconductors is studied using density functional theory (DFT) band structure calculations. The aim of this study is to improve our understanding of the features in the low-loss electron energy-loss spectra of ternary alloys, but the results are also relevant to optical and UV spectroscopy results. In addition, the dependence of the most remarkable features with composition is tested, i.e. applying Vegard's law to band gap and plasmon energy. For this purpose, three wurtzite ternary alloys, from the combination of binaries AlN, GaN, and InN, were simulated through a wide compositional range (i.e., Al x Ga1-x N, In x Al1-x N, and In x Ga1-x N, with x=[0,1]). For this DFT calculations, the standard tools found in Wien2k software were used. In order to improve the band structure description of these semiconductor compounds, the modified Becke-Johnson exchange-correlation potential was also used. Results from these calculations are presented, including band structure, density of states, and complex dielectric function for the whole compositional range. Larger, closer to experimental values, band gap energies are predicted using the novel potential, when compared with standard generalized gradient approximation. Moreover, a detailed analysis of the collective excitation features in the dielectric response reveals their compositional dependence, which sometimes departs from a linear behavior (bowing). Finally, an advantageous method for measuring the plasmon energy dependence from these calculations is explained.

Amorphous sub-nanometre Tb-doped SiO(x)N(y)/SiO2 superlattices for optoelectronics.

Amorphous sub-nanometre Tb-doped SiOxNy/SiO2 superlattices were fabricated by means of alternating deposition of 0.7 nm thick Tb-doped SiOxNy layers and of 0.9 nm thick SiO2 barrier layers in an electron-cyclotron-resonance plasma enhanced chemical vapour deposition system with in situ Tb-doping capability. High resolution transmission electron microscopy images showed a well-preserved superlattice morphology after annealing at a high temperature of 1000 °C. In addition, transparent indium tin oxide (ITO) electrodes were deposited by electron beam evaporation using a shadow mask approach to allow for the optoelectronic characterization of superlattices. Tb(3+) luminescent spectral features were obtained using three different excitation sources: UV laser excitation (photoluminescence (PL)), under a bias voltage (electroluminescence (EL)) and under a highly energetic electron beam (cathodoluminescence (CL)). All techniques displayed Tb(3+) inner transitions belonging to (5)D4 levels except for the CL spectrum, in which (5)D3 transition levels were also observed. Two competing mechanisms were proposed to explain the spectral differences observed between PL (or EL) and CL excitation: the population rate of the (5)D3 state and the non-radiative relaxation rate of the (5)D3-(5)D4 transition due to a resonant OH-mode. Moreover, the large number of interfaces (trapping sites) that electrons have to get through was identified as the main reason for observing a bulk-limited charge transport mechanism governed by Poole-Frenkel conduction in the J-V characteristic. Finally, a linear EL-J dependence was measured, with independent spectral shape and an EL onset voltage as low as 6.7 V. These amorphous sub-nanometre superlattices are meant to provide low-cost solutions in different areas including sensing, photovoltaics or photonics.

Oxide Wizard: an EELS application to characterize the white lines of transition metal edges.

Physicochemical properties of transition metal oxides are directly determined by the oxidation state of the metallic cations. To address the increasing need to accurately evaluate the oxidation states of transition metal oxide systems at the nanoscale, here we present "Oxide Wizard." This script for Digital Micrograph characterizes the energy-loss near-edge structure and the position of the transition metal edges in the electron energy-loss spectrum. These characteristics of the edges can be linked to the oxidation states of transition metals with high spatial resolution. The power of the script is demonstrated by mapping manganese oxidation states in Fe3O4/Mn3O4 core/shell nanoparticles with sub-nanometer resolution in real space.

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.

Comparative of machine learning classification strategies for electron energy loss spectroscopy: Support vector machines and artificial neural networks.

Machine Learning (ML) strategies applied to Scanning and conventional Transmission Electron Microscopy have become a valuable tool for analyzing the large volumes of data generated by various S/TEM techniques. In this work, we focus on Electron Energy Loss Spectroscopy (EELS) and study two ML techniques for classifying spectra in detail: Support Vector Machines (SVM) and Artificial Neural Networks (ANN). Firstly, we systematically analyze the optimal configurations and architectures for ANN classifiers using random search and the tree-structured Parzen estimator methods. Secondly, a new kernel strategy is introduced for the soft-margin SVMs, the cosine kernel, which offers a significant advantage over the previously studied kernels and other ML classification strategies. This kernel allows us to bypass the normalization of EEL spectra, achieving accurate classification. This result is highly relevant for the EELS community since we also assess the impact of common normalization techniques on our spectra using Uniform Manifold Approximation and Projection (UMAP), revealing a strong bias introduced in the spectra once normalized. In order to evaluate and study both classification strategies, we focus on determining the oxidation state of transition metals through their EEL spectra, examining which feature is more suitable for oxidation state classification: the oxygen K peak or the transition metal white lines. Subsequently, we compare the resistance to energy loss shifts for both classifiers and present a strategy to improve their resistance. The results of this study suggest the use of soft-margin SVMs for simpler EELS classification tasks with a limited number of spectra, as they provide performance comparable to ANNs while requiring lower computational resources and reduced training times. Conversely, ANNs are better suited for handling complex classification problems with extensive training data.

Localization and Directionality of Surface Transport in Bi2Te3 Ordered 3D Nanonetworks.

The resistance of an ordered 3D-Bi2Te3 nanowire nanonetwork was studied at low temperatures. Below 50 K the increase in resistance was found to be compatible with the Anderson model for localization, considering that conduction takes place in individual parallel channels across the whole sample. Angle-dependent magnetoresistance measurements showed a distinctive weak antilocalization characteristic with a double feature that we could associate with transport along two perpendicular directions, dictated by the spatial arrangement of the nanowires. The coherence length obtained from the Hikami-Larkin-Nagaoka model was about 700 nm across transversal nanowires, which corresponded to approximately 10 nanowire junctions. Along the individual nanowires, the coherence length was greatly reduced to about 100 nm. The observed localization effects could be the reason for the enhancement of the Seebeck coefficient observed in the 3D-Bi2Te3 nanowire nanonetwork compared to individual nanowires.

Understanding the Anisotropy in the Electrical Conductivity of CuPtB-type Ordered GaInP Thin Films by Combining In Situ TEM Biasing and First Principles Calculations.

In this work, the effect of CuPtB ordering on the optoelectronic properties of Ga0.5In0.5P is studied by combining in situ transmission electron microscopy measurements and density functional theory (DFT) calculations. GaInP layers were grown by metal organic vapor phase epitaxy with a CuPtB single-variant-induced ordering due to the intentional misorientation of the Ge(001) substrate. Moreover, the degree of order was controlled using Sb as the surfactant without changing other growth parameters. The presence of antiphase ordered domain boundaries (APDBs) between the ordered domains is studied as a function of the order parameter. The in situ electrical measurements on a set of samples with controlled degree of order evidence a clear anisotropic electrical conductivity at the nanoscale between the [110] and [1-10] orientations, which is discussed in terms of the presence of APDBs as a function of the degree of order. Additionally, DFT calculations allow to determine the differences in the optoelectronic properties of the compound with and without ordering through the determination of the dielectric function. Finally, the anisotropy of the electrical conductivity for the ordered case is also discussed in terms of the effective mass calculated from the band structure on specific k-paths. By comparing the experimental measurements and the theoretical calculations, two factors have been presented as the main contributors of the electric conductivity anisotropy of CuPtB-type ordered GaInP thin films: antiphase boundaries that separate domains with uniform order (APDBs) and the anisotropy of the effective mass due to the alternating of In/Ga rich planes.

Spontaneous Hetero-attachment of Single-Component Colloidal Precursors for the Synthesis of Asymmetric Au-Ag2X (X = S, Se) Heterodimers.

Finding simple, easily controlled, and flexible synthetic routes for the preparation of ternary and hybrid nanostructured semiconductors is always highly desirable, especially to fulfill the requirements for mass production to enable application to many fields such as optoelectronics, thermoelectricity, and catalysis. Moreover, understanding the underlying reaction mechanisms is equally important, offering a starting point for its extrapolation from one system to another. In this work, we developed a new and more straightforward colloidal synthetic way to form hybrid Au-Ag2X (X = S, Se) nanoparticles under mild conditions through the reaction of Au and Ag2X nanostructured precursors in solution. At the solid-solid interface between metallic domains and the binary chalcogenide domains, a small fraction of a ternary AuAg3X2 phase was observed to have grown as a consequence of a solid-state electrochemical reaction, as confirmed by computational studies. Thus, the formation of stable ternary phases drives the selective hetero-attachment of Au and Ag2X nanoparticles in solution, consolidates the interface between their domains, and stabilizes the whole hybrid Au-Ag2X systems.

Effectiveness of nitrogen incorporation to enhance the photoelectrochemical activity of nanostructured TiO2:NH3 versus H2-N2 annealing.

Highly ordered TiO(2) nanohole layers were synthesized by anodic oxidation of titanium foils using ethylene glycol and ammonium fluoride as the electrolyte. The effectiveness of different methods, namely annealing at 500 °C in NH(3) and in H(2) diluted in N(2), to incorporate nitrogen into TiO(2) and thus extend its photoelectrochemical (PEC) activity to the visible range was studied. The intra-gap levels introduced by both processes were identified by means of XPS and PL measurements. Water splitting experiments demonstrated that annealing in H(2) improved the photocatalytic activity of pure TiO(2), while annealing in ammonia led to a decrease in the PEC performance.

Mapping the Magnetic Coupling of Self-Assembled Fe3O4 Nanocubes by Electron Holography.

The nanoscale magnetic configuration of self-assembled groups of magnetite 40 nm cubic nanoparticles has been investigated by means of electron holography in the transmission electron microscope (TEM). The arrangement of the cubes in the form of chains driven by the alignment of their dipoles of single nanocubes is assessed by the measured in-plane magnetic induction maps, in good agreement with theoretical calculations.