Abstract: Single crystals of Bi3Mn1.9Te1.1O11 were prepared from NaCl+KCl flux. This compound adopts KSbO3-type crystal structure as evidenced by electron and single crystal X-ray diffraction analysis. The three-dimensional channel structure is formed by corner-sharing octahedral (Mn0.63Te0.37)2O10 dimers and two identical (Bi1)4(Bi2)2 interpenetrating lattices. The intra-dimer Mn/TeMn/Te distances in Bi3Mn1.9Te1.1O11 are short and are consistent with weak metalmetal interactions. The mixed oxidation state of manganese and the edge-sharing octahedral features are confirmed by X-ray near edge absorption spectroscopy measurements, which indicate Bi3(MnIII1.1MnIV0.8)TeVI1.1O11 with 57.7% Mn3+ and 42.3% Mn4+. The partial substitution of Te for Mn perturbs long-range magnetic interactions, thereby destroying the ferromagnetic ordering found in Bi3Mn3O11 (TC=150 K).

Abstract: La3Ni2SbO9 adopts a perovskite-related structure in which the six-coordinate cation sites are occupied alternately by Ni2+ and a disordered arrangement of Ni2+/Sb5+. A polycrystalline sample has been studied by neutron diffraction in applied magnetic fields of 0 <= H/kOe <= 50 at 5 K. In 0 kOe, weak magnetic Bragg scattering consistent with the adoption of a G-type ferrimagnetic structure is observed; the ordered component of the magnetic moment was found to be 0.89(7) mu(B) per Ni2+ cation. This increased to 1.60(3) mu(B) in a field of 50 kOe. Transmission electron microscopy revealed variations in the Ni:Sb ratio across crystallites of the sample. It is proposed that these composition variations disrupt the magnetic superexchange interactions within the compound, leading to domain formation and a reduced average moment. The application of a magnetic field aligns the magnetisation vectors across the crystal and the average moment measured by neutron diffraction increases accordingly. The role played by variations in the local chemical composition in determining the magnetic properties invites comparison with the behaviour of relaxor ferroelectrics. (C) 2014 Elsevier Inc. All rights reserved.

Abstract: Lake Tana is the most important freshwater lake in Ethiopia. Besides pressures on water quality resulting from urbanization and deforestation, the invasion of the exotic water hyacinth (Eichhornia crassipes) poses new threats to the ecosystem. Water hyacinth, endemic to South America, is widely considered as the world's worst aquatic invasive weed. In 2011, the weed appeared on the northern shores of Lake Tana, expanding in south-eastern direction. The lake area affected by water hyacinth was last estimated in 2015 at 34,500 ha, which equals 16% of the total lake surface. In this research, the benefits of water hyacinth control and eradication for the rural population inhabiting the northern and northeastern villages bordering Lake Tana, are investigated. In the area, the population largely depends on farming and fishing. An assessment of the total economic benefit of eradication was conducted. The stakeholder-centered approach led to measuring the willingness to contribute in labor and cash terms. Results showed smallholders in the study are willing to contribute over half-a-million euros annually. Costs of management actions can be weighed to the benefits, where further research is needed on the impact on other stakeholder groups. Moreover, wetland management should advance to explore multiple pathways in an integrated approach: water hyacinth control, water hyacinth utilization and sustainable waste water management. (C) 2020 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.

Abstract: In electron microscopy, the maximum a posteriori (MAP) probability rule has been introduced as a tool to determine the most probable atomic structure from high-resolution annular dark-field (ADF) scanning transmission electron microscopy (STEM) images exhibiting low contrast-to-noise ratio (CNR). Besides ADF imaging, STEM can also be applied in the annular bright-field (ABF) regime. The ABF STEM mode allows to directly visualize light-element atomic columns in the presence of heavy columns. Typically, light-element nanomaterials are sensitive to the electron beam, limiting the incoming electron dose in order to avoid beam damage and leading to images exhibiting low CNR. Therefore, it is of interest to apply the MAP probability rule not only to ADF STEM images, but to ABF STEM images as well. In this work, the methodology of the MAP rule, which combines statistical parameter estimation theory and model-order selection, is extended to be applied to simultaneously acquired ABF and ADF STEM images. For this, an extension of the commonly used parametric models in STEM is proposed. Hereby, the effect of specimen tilt has been taken into account, since small tilts from the crystal zone axis affect, especially, ABF STEM intensities. Using simulations as well as experimental data, it is shown that the proposed methodology can be successfully used to detect light elements in the presence of heavy elements.

Abstract: We present a quantitative method which allows us to reliably measure dynamic changes in the atomic structure of monatomic crystalline nanomaterials from a time series of atomic resolution annular dark field scanning transmission electron microscopy images. The approach is based on the so-called hidden Markov model and estimates the number of atoms in each atomic column of the nanomaterial in each frame of the time series. We discuss the origin of the improved performance for time series atom-counting as compared to the current state-of-the-art atom-counting procedures, and show that the so-called transition probabilities that describe the probability for an atomic column to lose or gain one or more atoms from frame to frame are particularly important. Using these transition probabilities, we show that the method can also be used to estimate the probability and cross section related to structural changes. Furthermore, we explore the possibilities for applying the method to time series recorded under variable environmental conditions. The method is shown to be promising for a reliable quantitative analysis of dynamic processes such as surface diffusion, adatom dynamics, beam effects, or in situ experiments.

Abstract: Lignin removal plays a crucial role in the efficient bioconversion of lignocellulose to fermentable sugars. As a delignification process, fungal pretreatment has gained great interest due to its environmental friendliness and low energy consumption. In our previous study, a positive linear correlation between acid-insoluble lignin degradation and the achievable enzymatic saccharification yield has been found, hereby highlighting the importance of the close follow-up of lignin degradation during the solid-state fungal pretreatment process. However, the standard quantification of lignin, which relies on the two-step acid hydrolysis of the biomass, is highly laborious and time-consuming. Vibrational spectroscopy has been proven as a fast and easy alternative; however, it has not been extensively researched on lignocellulose subjected to solid-state fungal pretreatment. Therefore, the present study examined the suitability of near-infrared spectroscopy (NIR) for the rapid and easy assessment of lignin content in poplar wood pretreated with Phanerochaete chrysosporium. Furthermore, the predictive power of the obtained calibration model and the recently published ATR-FTIR spectroscopy-based model were compared for the first time using the same fungus-treated wood data set. PLSR was used to correlate the NIR spectra to the acid-insoluble lignin contents (19.9%-27.1%) of pretreated wood. After normalization and second derivation, a PLSR model with a good coefficient of determination (RCV2 = 0.89) and a low root mean square error (RMSECV = 0.55%) were obtained despite the heterogeneous nature of the fungal solid-state fermentation. The performance of this PLSR model was comparably good to the one obtained by ATR-FTIR (RCV2 = 0.87) while it required more extensive spectral pre-processing. In conclusion, both methods will be highly useful for the high-throughput and user-friendly monitoring of lignin degradation in a solid-state fungal pretreatment-based biorefinery concept.

Abstract: Quantitative structure determination is needed in order to study and understand nanomaterials at the atomic scale. Materials characterisation resulting in precise structural information is a crucial point to understand the structure–property relation of materials. Counting the number of atoms and retrieving the 3D atomic structure of nanoparticles plays an important role here. In this paper, an overview will be given of the atom-counting methodology and its applications over the past decade. The procedure to count the number of atoms will be discussed in detail and it will be shown how the performance of the method can be further improved. Furthermore, advances toward mixed element nanostructures, 3D atomic modelling based on the atom-counting results, and quantifying the nanoparticle dynamics will be highlighted.

Abstract: Quantification of annular dark field (ADF) scanning transmission electron microscopy (STEM) images in terms
of composition or thickness often relies on probe-position integrated scattering cross sections (PPISCS). In
order to compare experimental PPISCS with theoretically predicted ones, expensive simulations are needed for
a given specimen, zone axis orientation, and a variety of microscope settings. The computation time of such
simulations can be in the order of hours using a single GPU card. ADF STEM simulations can be efficiently
parallelized using multiple GPUs, as the calculation of each pixel is independent of other pixels. However, most
research groups do not have the necessary hardware, and, in the best-case scenario, the simulation time will
only be reduced proportionally to the number of GPUs used. In this manuscript, we use a learning approach and
present a densely connected neural network that is able to perform real-time ADF STEM PPISCS predictions as
a function of atomic column thickness for most common face-centered cubic (fcc) crystals (i.e., Al, Cu, Pd, Ag,
Pt, Au and Pb) along [100] and [111] zone axis orientations, root-mean-square displacements, and microscope
parameters. The proposed architecture is parameter efficient and yields accurate predictions for the PPISCS
values for a wide range of input parameters that are commonly used for aberration-corrected transmission
electron microscopes.

Abstract: In this paper convexity constraints are derived for a background model of electron energy loss spectra (EELS) that is linear in the fitting parameters. The model outperforms a power-law both on experimental and simulated backgrounds, especially for wide energy ranges, and thus improves elemental quantification results. Owing to the model’s linearity, the constraints can be imposed through fitting by quadratic programming. This has important advantages over conventional nonlinear power-law fitting such as high speed and a guaranteed unique solution without need for initial parameters. As such, the need for user input is significantly reduced, which is essential for unsupervised treatment of large datasets. This is demonstrated on a demanding spectrum image of a semiconductor device sample with a high number of elements over a wide energy range.

Abstract: To understand the structure–property relationship of nanostructures, reliably quantifying parameters, such as the number of atoms along the projection direction, is important. Advanced statistical methodologies have made it possible to count the number of atoms for monotype crystalline nanoparticles from a single ADF STEM image. Recent developments enable one to simultaneously acquire multiple ADF STEM images. Here, we present an extended statistics-based method for atom counting from a combination of multiple statistically independent ADF STEM images reconstructed from non-overlapping annular detector collection regions which improves the accuracy and allows one to retrieve precise atom-counts, especially for images acquired with low electron doses and multiple element structures.

Abstract: Ptychography provides high dose efficiency images that can reveal light elements next to heavy atoms. However, despite ptychography having an otherwise single signed contrast transfer function, contrast reversals can occur when the projected potential becomes strong for both direct and iterative inversion ptychography methods. It has recently been shown that these reversals can often be counteracted in direct ptychography methods by adapting the focus. Here we provide an explanation of why the best contrast is often found with the probe focused to the middle of the sample. The phase contribution due to defocus at each sample slice above and below the central plane in this configuration effectively cancels out, which can prevent contrast reversals when dynamical scattering effects are not overly strong. In addition we show that the convergence angle can be an important consideration for removal of contrast reversals in relatively thin samples.

Abstract: Moiré fringes are used throughout a wide variety of applications in physics and
engineering to bring out small variations in an underlying lattice by comparing with another reference lattice. This method was recently demonstrated in Scanning Transmission Electron Microscopy imaging to provide local strain measurement in crystals by comparing the crystal lattice with the scanning raster that then serves as the reference. The images obtained in this way contain a beating fringe pattern with a local period that represents the deviation of the lattice from the reference. In order to obtain the actual strain value, a region containing a full period of the fringe is required, which results in a compromise between strain sensitivity and spatial resolution. In this paper we propose an advanced setup making use of an optimised scanning pattern and a novel phase stepping demodulation scheme. We demonstrate the novel method on a series of 16 nm Si-Ge semiconductor FinFET devices in which strain plays a crucial role in modulating the charge carrier mobility. The obtained results are compared with both Nano-beam diffraction and the recently proposed Bessel beam diffraction technique. The setup provides a much improved spatial resolution over conventional moiré imaging in STEM while at the same time being fast and requiring no specialised diffraction camera as opposed to the diffraction techniques we compare to.

Abstract: Si/Si(1 − x − y)GexCy superlattices are used in the construction of new microelectronic architectures such as multichannel transistors. The introduction of carbon in SiGe allows for compensation of the strain and to avoid plastic relaxation. However, the formation of incoherent β-SiC clusters during annealing limits the processability of SiGeC. This precipitation leads to a modification of the strain in the alloy due to the reduction of the substitutional carbon content. Here, we investigated the strain in annealed Si/Si0.744Ge0.244C0.012 superlattices grown by reduced pressure chemical vapour deposition using dark-field electron holography. The variation of the substitutional C content was calculated by correlating the results with finite-element simulations. The obtained values were then compared with Fourier-transformed infrared spectrometry measurements. It was shown that after annealing for 2 min at 1050 °C carbon no longer has any influence on strain in the superlattice, which behaves like pure SiGe. However, a significant proportion of substitutional C atoms remain in a third-nearest neighbour (3nn) configuration. It was deduced that the influence of 3nn C on strain is negligible and that only isolated atoms have a significant contribution. It was also proposed that the 3nn configuration is an intermediary step during the formation of SiC clusters.

Abstract: Carboxylic acids and sodium carboxylates are used to protect metals against aqueous and atmospheric corrosion. In this paper, we describe the application of a layer of copper carboxylate on the surface of a copper electrode by means of cyclic voltammetry technique and tests which measure the corresponding resistance to aqueous corrosion. Unlike the soaking process, which also forms a film on the surface, the use of cyclic voltammetry allows one to follow the deposition process of the copper carboxylates onto the electrode. The modified electrodes have been characterised with infrared spectroscopy. In addition, the corrosion resistance of the film has been investigated using polarisation resistance and Tafel plot measurements.

Abstract: The SiC/Al composites have been fabricated by a vacuum hot pressing (VHP) process in order to study the effect of interface evolution on the global thermal conductivity (TC). By optimizing the VHP parameters of sintering temperature and time, the three different kinds of SiC/Al interface configurations, that is, non-bonded, diffusion-bonded, and reaction-bonded interfaces, are formed and identified by measurement of relative density, X-ray diffraction, scanning and (high-resolution) transmission electron microscopy. The VHPed composite sintered at 655 °C for 60 min is fully dense and presents a tightly-adhered and clean SiC/Al interface at the nanoscale, the ideal diffusion-bonded interface being the most favorable for minimizing interfacial thermal resistance, which in turn results in the highest TC of around 270 W/mK.