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.

High-spatial resolution functional chemistry of nitrogen compounds in the observed UK meteorite fall Winchcombe.

Organic matter in extraterrestrial samples is a complex material that might have played an important role in the delivery of prebiotic molecules to the early Earth. We report here on the identification of nitrogen-containing compounds such as amino acids and N-heterocycles within the recent observed meteorite fall Winchcombe by high-spatial resolution spectroscopy techniques. Although nitrogen contents of Winchcombe organic matter are low (N/C ~ 1-3%), we were able to detect the presence of these compounds using a low-noise direct electron detector. These biologically relevant molecules have therefore been tentatively found within a fresh, minimally processed meteorite sample by high spatial resolution techniques conserving the overall petrographic context. Carbon functional chemistry investigations show that sizes of aromatic domains are small and that abundances of carboxylic functional groups are low. Our observations demonstrate that Winchcombe represents an important addition to the collection of carbonaceous chondrites and still preserves pristine extraterrestrial organic matter.

Amorphous 1-D nanowires of calcium phosphate/pyrophosphate: A demonstration of oriented self-growth of amorphous minerals.

Amorphous inorganic solids are traditionally isotropic, thus, it is believed that they only grow in a non-preferential way without the assistance of regulators, leading to the morphologies of nanospheres or irregular aggregates of nanoparticles. However, in the presence of (ortho)phosphate (Pi) and pyrophosphate ions (PPi) which have synergistic roles in biomineralization, the highly elongated amorphous nanowires (denoted ACPPNs) form in a regulator-free aqueous solution (without templates, additives, organics, etc). Based on thorough characterization and tracking of the formation process (e.g., Cryo-TEM, spherical aberration correction high resolution TEM, solid state NMR, high energy resolution monochromated STEM-EELS), the microstructure and its preferential growth behavior are elucidated. In ACPPNs, amorphous calcium orthophosphate and amorphous calcium pyrophosphate are distributed at separated but close sites. The ACPPNs grow via either the preferential attachment of ∼2 nm nanoclusters in a 1-dimension way, or the transformation of bigger nanoparticles, indicating an inherent driving force-governed process. We propose that the anisotropy of ACPPNs microstructure, which is corroborated experimentally, causes their oriented growth. This study proves that, unlike the conventional view, amorphous minerals can form via oriented growth without external regulation, demonstrating a novel insight into the structures and growth behaviors of amorphous minerals.

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.

Dislocation and strain mapping in metamorphic parabolic-graded InGaAs buffers on GaAs.

We investigate different architectures for parabolic-graded InGaAs metamorphic buffers grown on GaAs using transmission electron microscopy techniques. The different architectures include InGaP and AlInGaAs/InGaP superlattices with different GaAs substrate misorientations and the inclusion of a strain balancing layer. Our results correlate: (i) the density and distribution of dislocations in the metamorphic buffer and (ii) the strain in the next layer preceding the metamorphic buffer, which varies for each type of architecture. Our findings indicate that the dislocation density in the lower region of the metamorphic layer ranges between 108 and 1010 cm-2, with AlInGaAs/InGaP superlattice samples exhibiting higher values compared to samples with InGaP films. We have identified two waves of dislocations, with threading dislocations typically located lower in the metamorphic buffer (~ 200-300 nm) in comparison to misfit dislocations. The measured localised strain values are in good agreement with theoretical predications. Overall, our results provide a systematic insight into the strain relaxation across different architectures, highlighting the various approaches that can be used to tailor strain in the active region of a metamorphic laser. Supplementary Information: The online version contains supplementary material available at 10.1007/s10853-023-08597-y.

High Power Factor Nb-Doped TiO2 Thermoelectric Thick Films: Toward Atomic Scale Defect Engineering of Crystallographic Shear Structures.

Donor-doped TiO2-based materials are promising thermoelectrics (TEs) due to their low cost and high stability at elevated temperatures. Herein, high-performance Nb-doped TiO2 thick films are fabricated by facile and scalable screen-printing techniques. Enhanced TE performance has been achieved by forming high-density crystallographic shear (CS) structures. All films exhibit the same matrix rutile structure but contain different nano-sized defect structures. Typically, in films with low Nb content, high concentrations of oxygen-deficient {121} CS planes are formed, while in films with high Nb content, a high density of twin boundaries are found. Through the use of strongly reducing atmospheres, a novel Al-segregated {210} CS structure is formed in films with higher Nb content. By advanced aberration-corrected scanning transmission electron microscopy techniques, we reveal the nature of the {210} CS structure at the nano-scale. These CS structures contain abundant oxygen vacancies and are believed to enable energy-filtering effects, leading to simultaneous enhancement of both the electrical conductivity and Seebeck coefficients. The optimized films exhibit a maximum power factor of 4.3 × 10-4 W m-1 K-2 at 673 K, the highest value for TiO2-based TE films at elevated temperatures. Our modulation strategy based on microstructure modification provides a novel route for atomic-level defect engineering which should guide the development of other TE materials.

Plasmonic properties of aluminium nanowires in amorphous silicon.

Plasmonic structures can help enhance optical activity in the ultraviolet (UV) region and therefore enhancing photocatalytic reactions and the detection of organic and biological species. Most plasmonic structures are composed of Ag or Au. However, producing structures small enough for optical activity in the UV region has proved difficult. In this study, we demonstrate that aluminium nanowires are an excellent alternative. We investigated the plasmonic properties of the Al nanowires as well as the optoelectronic properties of the surroundinga - Simatrix by combining scanning transmission electron microscopy imaging, electron energy loss spectroscopy and electrodynamic modelling. We have found that the Al nanowires have distinct plasmonic modes in the UV and far UV region, from 0.75 eV to 13 eV. In addition, simulated results found that the size and spacing of the Al nanowires, as well as the embedding material were shown to have a large impact on the type of surface plasmon energies that can be generated in the material. Using electromagnetic modelling, we have identified the modes and illustrated how they could be tuned further.

Controlling the Thermoelectric Behavior of La-Doped SrTiO3 through Processing and Addition of Graphene Oxide.

The addition of graphene has been reported as a potential route to enhance the thermoelectric performance of SrTiO3. However, the interplay between processing parameters and graphene addition complicates understanding this enhancement. Herein, we examine the effects of processing parameters and graphene addition on the thermoelectric performance of La-doped SrTiO3 (LSTO). Briefly, two types of graphene oxide (GO) at different oxidation degrees were used, while the LSTO pellets were densified under two conditions with different reducing strengths (with/without using oxygen-scavenging carbon powder bed muffling). Raman imaging of the LSTO green body and sintered pellets suggests that the added GO sacrificially reacts with the lattice oxygen, which creates more oxygen vacancies and improves electrical conductivity regardless of the processing conditions. The addition of mildly oxidized electrochemical GO (EGO) yields better performance than the conventional heavily oxidized chemical GO (CGO). Moreover, we found that muffling the green body with an oxygen-scavenging carbon powder bed during sintering is vital to achieving a single-crystal-like temperature dependence of electrical conductivity, implying that a highly reducing environment is critical for eliminating the grain boundary barriers. Combining 1.0 wt % EGO addition with a highly reducing environment leads to the highest electrical conductivity of 2395 S cm-1 and power factor of 2525µW m-1 K-2 at 300 K, with an improved average zT value across the operating temperature range of 300-867 K. STEM-EELS maps of the optimized sample show a pronounced depletion of Sr and evident deficiency of O and La at the grain boundary region. Theoretical modeling using a two-phase model implies that the addition of GO can effectively improve carrier mobility in the grain boundary phase. This work provides guidance for the development of high-performance thermoelectric ceramic oxides.

Towards 3D characterisation of site-controlled InGaAs pyramidal QDs at the nanoscale.

In this work, we report an extensive investigation via transmission electron microscopy (TEM) techniques of InGaAs/GaAs pyramidal quantum dots (PQDs), a unique site-controlled family of quantum emitters that have proven to be excellent sources of single and entangled photons. The most striking features of this system, originating from their peculiar fabrication process, include their inherently 3-dimensional nature and their interconnection to a series of nanostructures that are formed alongside them, such as quantum wells and quantum wires. We present structural and chemical data from cross-sectional and plan view samples of both single and stacked PQDs structures. Our findings identify (i) the shape of the dot, being hexagonal and not triangular as previously assumed, (ii) the chemical distribution at the facets and QD area, displaying clear Indium diffusion, and (iii) a near absence of Aluminium (from the AlAs marker) at the bottom of the growth profile. Our results shed light on previously unreported structural and chemical features of PQDs, which is of extreme relevance for further development of this family of quantum emitters. Supplementary Information: The online version contains supplementary material available at 10.1007/s10853-022-07654-2.

Elucidation of Metal Local Environments in Single-Atom Catalysts Based on Carbon Nitrides.

The ability to tailor the properties of metal centers in single-atom heterogeneous catalysts depends on the availability of advanced approaches for characterization of their structure. Except for specific host materials with well-defined metal adsorption sites, determining the local atomic environment remains a crucial challenge, often relying heavily on simulations. This article reports an advanced analysis of platinum atoms stabilized on poly(triazine imide), a nanocrystalline form of carbon nitride. The approach discriminates the distribution of surface coordination sites in the host, the evolution of metal coordination at different stages during the synthesis of the material, and the potential locations of metal atoms within the lattice. Consistent with density functional theory predictions, simultaneous high-resolution imaging in high-angle annular dark field and bright field modes experimentally confirms the preferred localization of platinum in-plane in the corners of the triangular cavities. X-ray absorption spectroscopy (XAS), X-ray photoelectron spectroscopy (XPS), and dynamic nuclear polarization enhanced 15 N nuclear magnetic resonance (DNP-NMR) spectroscopies coupled with density functional theory (DFT) simulations reveal that the predominant metal species comprise Pt(II) bound to three nitrogen atoms and one chlorine atom inside the coordination sites. The findings, which narrow the gap between experimental and theoretical elucidation, contribute to the improved structural understanding and provide a benchmark for exploring the speciation of single-atom catalysts based on carbon nitrides.

Automated Image Analysis for Single-Atom Detection in Catalytic Materials by Transmission Electron Microscopy.

Single-atom catalytic sites may have existed in all supported transition metal catalysts since their first application. Yet, interest in the design of single-atom heterogeneous catalysts (SACs) only really grew when advances in transmission electron microscopy (TEM) permitted direct confirmation of metal site isolation. While atomic-resolution imaging remains a central characterization tool, poor statistical significance, reproducibility, and interoperability limit its scope for deriving robust characteristics about these frontier catalytic materials. Here, we introduce a customized deep-learning method for automated atom detection in image analysis, a rate-limiting step toward high-throughput TEM. Platinum atoms stabilized on a functionalized carbon support with a challenging irregular three-dimensional morphology serve as a practically relevant test system with promising scope in thermo- and electrochemical applications. The model detects over 20,000 atomic positions for the statistical analysis of important properties for establishing structure-performance relations over nanostructured catalysts, like the surface density, proximity, clustering extent, and dispersion uniformity of supported metal species. Good performance obtained on direct application of the model to an iron SAC based on carbon nitride demonstrates its generalizability for single-atom detection on carbon-related materials. The approach establishes a route to integrate artificial intelligence into routine TEM workflows. It accelerates image processing times by orders of magnitude and reduces human bias by providing an uncertainty analysis that is not readily quantifiable in manual atom identification, improving standardization and scalability.

Electrostatically Driven Polarization Flop and Strain-Induced Curvature in Free-Standing Ferroelectric Superlattices.

The combination of strain and electrostatic engineering in epitaxial heterostructures of ferroelectric oxides offers many possibilities for inducing new phases, complex polar topologies, and enhanced electrical properties. However, the dominant effect of substrate clamping can also limit the electromechanical response and often leaves electrostatics to play a secondary role. Releasing the mechanical constraint imposed by the substrate can not only dramatically alter the balance between elastic and electrostatic forces, enabling them to compete on par with each other, but also activates new mechanical degrees of freedom, such as the macroscopic curvature of the heterostructure. In this work, an electrostatically driven transition from a predominantly out-of-plane polarized to an in-plane polarized state is observed when a PbTiO3 /SrTiO3 superlattice with a SrRuO3 bottom electrode is released from its substrate. In turn, this polarization rotation modifies the lattice parameter mismatch between the superlattice and the thin SrRuO3 layer, causing the heterostructure to curl up into microtubes. Through a combination of synchrotron-based scanning X-ray diffraction imaging, Raman scattering, piezoresponse force microscopy, and scanning transmission electron microscopy, the crystalline structure and domain patterns of the curved superlattices are investigated, revealing a strong anisotropy in the domain structure and a complex mechanism for strain accommodation.

Controlling the Thermoelectric Properties of Nb-Doped TiO2 Ceramics through Engineering Defect Structures.

Donor-doped TiO2 ceramics are promising high-temperature oxide thermoelectrics. Highly dense (1 - x)TiO2-xNb2O5 (0.005 ≤ x ≤ 0.06) ceramics were prepared by a single-step, mixed-oxide route under reducing conditions. The microstructures contained polygonal-shaped grains with uniform grain size distributions. Subgrain structures were formed in samples with low Nb contents by the interlacing of rutile and higher-order Magnéli phases, reflecting the high density of shear planes and oxygen vacancies. Samples prepared with a higher Nb content showed no subgrain structures but high densities of planar defects and lower concentrations of oxygen vacancies. Through optimizing the concentration of point defects and line defects, the carrier concentration and electrical conductivity were enhanced, yielding a much improved power factor of 5.3 × 10-4 W m-1 K-2 at 823 K; lattice thermal conductivity was significantly reduced by enhanced phonon scattering. A low, temperature-stable thermal conductivity of 2.6 W m-1 K-1 was achieved, leading to a ZT value of 0.17 at 873 K for compositions with x = 0.06, the highest ZT value reported for single Nb-doped TiO2 ceramics without the use of spark plasma sintering (SPS). We demonstrate the control of the thermoelectric properties of Nb-doped TiO2 ceramics through the development of balanced defect structures, which could guide the development of future oxide thermoelectric materials.

A primordial 15N-depleted organic component detected within the carbonaceous chondrite Maribo.

We report on the detection of primordial organic matter within the carbonaceous chondrite Maribo that is distinct from the majority of organics found in extraterrestrial samples. We have applied high-spatial resolution techniques to obtain C-N isotopic compositions, chemical, and structural information of this material. The organic matter is depleted in 15N relative to the terrestrial value at around δ15N ~ -200‰, close to compositions in the local interstellar medium. Morphological investigations by electron microscopy revealed that the material consists of µm- to sub-µm-sized diffuse particles dispersed within the meteorite matrix. Electron energy loss and synchrotron X-ray absorption near-edge structure spectroscopies show that the carbon functional chemistry is dominated by aromatic and C=O bonding environments similar to primordial organics from other carbonaceous chondrites. The nitrogen functional chemistry is characterized by C-N double and triple bonding environments distinct from what is usually found in 15N-enriched organics from aqueously altered carbonaceous chondrites. Our investigations demonstrate that Maribo represents one of the least altered CM chondrite breccias found to date and contains primordial organic matter, probably originating in the interstellar medium.

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.

Self-Nanostructuring 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.

Subwavelength Spatially Resolved Coordination Chemistry of Metal-Organic Framework Glass Blends.

Microstructured metal-organic framework (MOF) glasses have been produced by combining two amorphous MOFs. However, the electronic structure of these materials has not been interrogated at the length scales of the chemical domains formed in these glasses. Here, we report a subwavelength spatially resolved physicochemical analysis of the electronic states at visible and UV energies in a blend of two zeolitic imidazolate frameworks (ZIFs), ZIF-4-Co and ZIF-62-Zn. By combining spectroscopy at visible and UV energies as well as at core ionization energies in electron energy loss spectroscopy in the scanning transmission electron microscope with density functional theory calculations, we show that domains less than 200 nm in size retain the electronic structure of the precursor crystalline ZIF phases. Prototypical signatures of coordination chemistry including d- d transitions in ZIF-4-Co are assigned and mapped with nanoscale precision.

Scalable Patterning of Encapsulated Black Phosphorus.

Atomically thin black phosphorus (BP) has attracted considerable interest due to its unique properties, such as an infrared band gap that depends on the number of layers and excellent electronic transport characteristics. This material is known to be sensitive to light and oxygen and degrades in air unless protected with an encapsulation barrier, limiting its exploitation in electrical devices. We present a new scalable technique for nanopatterning few layered BP by direct electron beam exposure of encapsulated crystals, achieving a spatial resolution down to 6 nm. By encapsulating the BP with single layer graphene or hexagonal boron nitride (hBN), we show that a focused electron probe can be used to produce controllable local oxidation of BP through nanometre size defects created in the encapsulation layer by the electron impact. We have tested the approach in the scanning transmission electron microscope (STEM) and using industry standard electron beam lithography (EBL). Etched regions of the BP are stabilized by a thin passivation layer and demonstrate typical insulating behavior as measured at 300 and 4.3 K. This new scalable approach to nanopatterning of thin air sensitive crystals has the potential to facilitate their wider use for a variety of sensing and electronics applications.