Low-Temperature ALD of SbOx /Sb2 Te3 Multilayers with Boosted Thermoelectric Performance.

Nanoscale superlattice (SL) structures have proven to be effective in enhancing the thermoelectric (TE) properties of thin films. Herein, the main phase of antimony telluride (Sb2 Te3 ) thin film with sub-nanometer layers of antimony oxide (SbOx ) is synthesized via atomic layer deposition (ALD) at a low temperature of 80 °C. The SL structure is tailored by varying the cycle numbers of Sb2 Te3 and SbOx . A remarkable power factor of 520.8 µW m-1 K-2 is attained at room temperature when the cycle ratio of SbOx and Sb2 Te3 is set at 1:1000 (i.e., SO:ST = 1:1000), corresponding to the highest electrical conductivity of 339.8 S cm-1 . The results indicate that at the largest thickness, corresponding to ten ALD cycles, the SbOx layers act as a potential barrier that filters out the low-energy charge carriers from contributing to the overall electrical conductivity. In addition to enhancing the scattering of the mid-to-long-wavelength at the SbOx /Sb2 Te3 interface, the presence of the SbOx sub-layer induces the confinement effect and strain forces in the Sb2 Te3 thin film, thereby effectively enhancing the Seebeck coefficient and reducing the thermal conductivity. These findings provide a new perspective on the design of SL-structured TE materials and devices.

Freestanding Nanolayers of a Wide-Gap Topological Insulator through Liquid-Phase Exfoliation.

The layered salt Bi14 Rh3 I9 is a weak three-dimensional (3D) topological insulator (TI), that is, a stack of two-dimensional (2D) TIs. It has a wide non-trivial band gap of 210 meV, which is generated by strong spin-orbit coupling, and possesses protected electronic edge-states. In the structure, charged layers of ∞ 2 [ (Bi4 Rh)3 I]2+ honeycombs and ∞ 1 [ Bi2 I8 ]2- chains alternate. The non-trivial topology of Bi14 Rh3 I9 is an inherent property of the 2D intermetallic fragment. Here, the exfoliation of Bi14 Rh3 I9 was performed using two different chemical approaches: (a) through a reaction with n-butyllithium and poly(vinylpyrrolidone), (b) through a reaction with betaine in dimethylformamide at 55 °C. The former yielded few-layer sheets of the new compound Bi12 Rh3 I, while the latter led to crystalline sheets of Bi14 Rh3 I9 with a thickness down to 5 nm and edge-lengths up to several ten microns. X-ray diffraction and electron microscopy proved that the structure of Bi14 Rh3 I9 remained intact. Thus, it was assumed that the particles are still TIs. Dispersions of these flakes now allow for next steps towards the envisioned applications in nanoelectronics, such as the study of quantum coherence in deposited films, the combination with superconducting particles or films for the generation of Majorana fermions, or studies on their behavior under the influence of magnetic or electric fields or in contact with various materials occurring in devices. The method presented generally allows to exfoliate layers with high specific charges and thus the use of layered starting materials beyond van der Waals crystals.

Direct Observation of Plasmon Band Formation and Delocalization in Quasi-Infinite Nanoparticle Chains.

Chains of metallic nanoparticles sustain strongly confined surface plasmons with relatively low dielectric losses. To exploit these properties in applications, such as waveguides, the fabrication of long chains of low disorder and a thorough understanding of the plasmon-mode properties, such as dispersion relations, are indispensable. Here, we use a wrinkled template for directed self-assembly to assemble chains of gold nanoparticles. With this up-scalable method, chain lengths from two particles (140 nm) to 20 particles (1500 nm) and beyond can be fabricated. Electron energy-loss spectroscopy supported by boundary element simulations, finite-difference time-domain, and a simplified dipole coupling model reveal the evolution of a band of plasmonic waveguide modes from degenerated single-particle modes in detail. In striking difference from plasmonic rod-like structures, the plasmon band is confined in excitation energy, which allows light manipulations below the diffraction limit. The non-degenerated surface plasmon modes show suppressed radiative losses for efficient energy propagation over a distance of 1500 nm.

Mapping Chemical Bonds in Semiconductor Devices by Monitoring the Shifts of EELS Edges.

Scanning transmission electron microscopy (STEM) in combination with electron energy-loss spectroscopy (EELS) can deliver information about variations of bonding at the nm scale. This is typically performed by analyzing the electron-loss near edge structure (ELNES) of given EELS edges. The present paper demonstrates an alternative way of a bonding examination through monitoring the EELS onset positions. Two conditions are essential for their accurate measurement. One (hardware) is using the dual EELS instrumentation that provides near simultaneous acquisition of low-loss and core-loss spectra. Another (software) is the least-square fitting of observed spectra to a reference spectrum. The combination of these hardware and software techniques reveals the positions of EELS onsets with the precision sufficient for mapping tiny variations of bonding. The paper shows that the method is capable of helping to solve practical tasks of nanoscale engineering like the analysis of modern CMOS devices.

Development of oxidation-resistant and electrically conductive coating of Ti-Al-C system for the lightweight interconnects of solid oxide fuel cells.

The paper studies oxidation resistance and electrical conductivity of dense coatings produced by vacuum-arc deposition technique on α-titanium thin (0.1 mm) substrate using a hot pressed Ti2AlC-TiC target. The coatings were deposited at low (7 mA/cm2) and high (15 mA/cm2) current densities on the substrate and marked LCD and HCD, respectively. This provided different local chemical and phase compositions of the coatings. It was found that phase compositions of the coatings differ from that of the target. The HCD coating has high oxidation resistance evaluated in terms of the specific weight gain (Δm/S = 0.06 mg/cm2) as well as high surface electrical conductivity (σ = 1.23·106 S/m) after long-term (1000 h) holding at 600 °C in the air due to the formation of an over thin (450 nm) Ti-Al-(C, O, N) near-surface layer. The thin titanium substrate with such Ti-Al-C coating is recommended as a lightweight interconnect of an intermediate-temperature solid oxide fuel cell.

Extraction of physically meaningful endmembers from STEM spectrum-images combining geometrical and statistical approaches.

This article addresses extraction of physically meaningful information from STEM EELS and EDX spectrum-images using methods of Multivariate Statistical Analysis. The problem is interpreted in terms of data distribution in a multi-dimensional factor space, which allows for a straightforward and intuitively clear comparison of various approaches. A new computationally efficient and robust method for finding physically meaningful endmembers in spectrum-image datasets is presented. The method combines the geometrical approach of Vertex Component Analysis with the statistical approach of Bayesian inference. The algorithm is described in detail at an example of EELS spectrum-imaging of a multi-compound CMOS transistor.

Optimal principal component analysis of STEM XEDS spectrum images.

STEM XEDS spectrum images can be drastically denoised by application of the principal component analysis (PCA). This paper looks inside the PCA workflow step by step on an example of a complex semiconductor structure consisting of a number of different phases. Typical problems distorting the principal components decomposition are highlighted and solutions for the successful PCA are described. Particular attention is paid to the optimal truncation of principal components in the course of reconstructing denoised data. A novel accurate and robust method, which overperforms the existing truncation methods is suggested for the first time and described in details.

On the loss of information in PCA of spectrum-images.

Principal Component Analysis (PCA) can drastically denoise STEM spectrum-images but might distort or cut off the important variations in data. The present paper analyzes various approaches to estimate such deviations and compares them with the simulated data. A spiked covariance model by Nadler (2008) appears to be most appropriated for application in STEM spectrum-imaging.

Enhancement of noisy EDX HRSTEM spectrum-images by combination of filtering and PCA.

STEM spectrum-imaging with collecting EDX signal is considered in view of the extraction of maximum information from very noisy data. It is emphasized that spectrum-images with weak EDX signal often suffer from information loss in the course of PCA treatment. The loss occurs when the level of random noise exceeds a certain threshold. Weighted PCA, though potentially helpful in isolation of meaningful variations from noise, might provoke the complete loss of information in the situation of weak EDX signal. Filtering datasets prior PCA can improve the situation and recover the lost information. In particular, Gaussian kernel filters are found to be efficient. A new filter useful in the case of sparse atomic-resolution EDX spectrum-images is suggested.

Why Principal Component Analysis of STEM spectrum-images results in "abstract", uninterpretable loadings?

Principal Component Analysis (PCA) can improve dramatically the treatment of large STEM spectrum-images by finding the directions (loadings) of highest data variance in the factor space and projecting the data on these directions. Loadings typically do not show clear physical meanings, thus the interpretation of PCA results is difficult. This work investigates the potential reasons for appearing such counterintuitive PCA outputs. The following reasons are identified: (i) missing the step of centering the data in the PCA pre-treatment, (ii) complexity of data variations inconsistent with the orthogonality restrictions of PCA, (iii) non-linearity caused either by chemical variations or by the peculiarities of the spectra formation, and (iv) inaccuracy in extracting major PCA components. In many cases, the PCA treatment can be altered in such a way that the intuitively clear loadings are delivered.

Materials characterisation by angle-resolved scanning transmission electron microscopy.

Solid-state properties such as strain or chemical composition often leave characteristic fingerprints in the angular dependence of electron scattering. Scanning transmission electron microscopy (STEM) is dedicated to probe scattered intensity with atomic resolution, but it drastically lacks angular resolution. Here we report both a setup to exploit the explicit angular dependence of scattered intensity and applications of angle-resolved STEM to semiconductor nanostructures. Our method is applied to measure nitrogen content and specimen thickness in a GaNxAs1-x layer independently at atomic resolution by evaluating two dedicated angular intervals. We demonstrate contrast formation due to strain and composition in a Si- based metal-oxide semiconductor field effect transistor (MOSFET) with GexSi1-x stressors as a function of the angles used for imaging. To shed light on the validity of current theoretical approaches this data is compared with theory, namely the Rutherford approach and contemporary multislice simulations. Inconsistency is found for the Rutherford model in the whole angular range of 16-255 mrad. Contrary, the multislice simulations are applicable for angles larger than 35 mrad whereas a significant mismatch is observed at lower angles. This limitation of established simulations is discussed particularly on the basis of inelastic scattering.

Elemental mapping of multilayered structures: a method to reconstruct 2D chemical maps from a set of 1D line scans.

We introduce a method to characterize the chemical distribution in nanostructures using STEM and affiliated spectroscopy techniques. The method is applicable to any nanostructure where the continuous layers of arbitrary geometry and dimensions can be identified. The key feature of the suggested approach is digital warping of the original STEM image into the quasi-1D image. The chemical profiles of high resolution and high signal-to-noise ratio can be extracted from the minimal set of the STEM spectroscopy data while minimizing material damage during acquisitions. Finally, the 2D chemical maps of the area of interest are reconstructed.

Cross-section transmission electron microscopy characterization of the near-surface structure of medical Nitinol superelastic tubing.

The application of Nitinol in a wide variety of medical implants is progressively increasing because of its unique mechanical properties, durability and biocompatibility. However, as Nitinol consists of about 50 at.% of toxic Ni, certain applications are still hindered by the concern of free Ni release in the surrounding tissue. The latter is controlled by the structure of near-surface layers and can be strongly affected by various surface treatments. A proper application of advanced cross-section sample preparation techniques allows us to characterize the Nitinol near-surface structure down to the nanoscale by means of transmission electron microscopy (TEM). Elemental maps of the Ti, O and Ni distribution, concentration profiles, quantification of composition as well as atomic resolution images at the surface of a Nitinol tubing are presented and the results obtained with different sample preparation and analytical characterization techniques are compared. In addition to a strong decrease of Ni towards the surface of the oxide layer and a Ti depleted layer underneath the oxide, also a possible transformation from TiO to TiO(2) is documented.