Abstract: Natural deep eutectic solvents (NADES) are mixtures of naturally derived compounds with a significantly decreased melting point due to the specific interactions among the constituents. NADES have benign properties (low volatility, flammability, toxicity, cost) and tailorable physicochemical properties (by altering the type and molar ratio of constituents), hence they are often considered as a green alternative to common organic solvents. Modeling the relation between their composition and properties is crucial though, both for understanding and predicting their behavior. Several efforts were done to this end, yet this review aims at structuring the present knowledge as an outline for future research. First, we reviewed the key properties of NADES and relate them to their structure based on the available experimental data. Second, we reviewed available modeling methods applicable to NADES. At the molecular level, density functional theory and molecular dynamics allow interpreting density differences and vibrational spectra, and computation of interaction energies. Additionally, properties at the level of the bulk media can be explained and predicted by semi-empirical methods based on ab initio methods (COSMO-RS) and equation of state models (PC-SAFT). Finally, methods based on large datasets are discussed; models based on group contribution methods and machine learning. A combination of bulk media and dataset modeling allows qualitative prediction and interpretation of phase equilibria properties on the one hand, and quantitative prediction of melting point, density, viscosity, surface tension and refractive indices on the other hand. In our view, multiscale modeling, combining the molecular and macroscale methods, will strongly enhance the predictability of NADES properties and their interaction with solutes, yielding truly tailorable solvents to accommodate (bio)chemical reactions.

Abstract: Packed bed dielectric barrier discharge (PB-DBD) plasma reactors are very promising for various plasma catalysis applications, but the exact mechanisms of plasma-catalyst interaction are far from understood, because the plasma discharge and catalyst/packing properties are mutually dependent. To better understand the effect of packing dielectric material on the electrical plasma properties, we study here a single bead DBD plasma reactor operating in dry air, with beads of different dielectric constant and for different applied voltages, by means of fluid modelling validated by optical imaging experiments. Our study reveals that the plasma in the single bead DBD reactor can manifest itself in two different modalities, i.e. (a) polar discharges at the bead poles in contact with the electrodes, and (b) a streamer discharge caused by surface ionization waves, which bridges the gas gap. Beads with high dielectric constant result in localised electric field enhancement and hence yield a reduction of the applied voltage required for plasma production. At low applied voltage, the discharge appears as polar discharges between the bead and the electrodes, and upon higher voltage it undergoes a transition into a bridging streamer discharge. The transition voltage to the streamer mode rises for beads with higher dielectric constant. These observations are important for plasma catalysis applications. A higher dielectric constant yields a higher electric field and thus higher average electron energy and density, giving rise to more reactive species, but it also yields a confined discharge near the contact points of packing beads, limiting the interaction area between the catalyst and the active plasma species. In addition, our model reveals that the dielectric bead behaves as a capacitor and traps charges, which can explain the significant occurrence of partial discharging in PB-DBDs and non-parallelogram shaped Lissajous plots. Hence, equivalent circuit modelling of PB-DBDs should take into account the role of packing beads in charge trapping as a capacitor.

Abstract: In this chapter, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high-resolution annular dark-field (ADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. We show that this method can be applied to nanocrystals of arbitrary shape, size, and atom type. The validity of the atom-counting results is confirmed by means of detailed image simulations and it is shown that the high sensitivity of our method enables us to count atoms with single atom sensitivity.

Abstract: An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic-resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighboring columns, enabling the analysis of a large field of view. To provide end-users with this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license. In this chapter, this efficient algorithm is applied to three different nanostructures for which the analysis of a large field of view is required.

Abstract: In this work, the effects of Si-doping in Cu2ZnSnS4 are examined computationally and experimentally. The density functional theory calculations show that an increasing concentration of Si (from x = 0 to x = 1) yields a band gap rise due to shifting of the conduction band minimum towards higher energy states in the Cu2Zn(Sn1-xSix)S-4. CZTSiS thin film prepared by co-sputtering process shows Cu2Zn(Sn1-xSix)S-4 (Si-rich) and Cu2ZnSnS4 (S-rich) kesterite phases on the surface and in the bulk of the sample, respectively. A significant change in surface electronic properties is observed in CZTSiS thin film. Si-doping in CZTS inverts the band bending at grain-boundaries from downward to upward and the Fermi level of CZTSiS shifts upward. Further, the coating of the CdS and ZnO layer improves the photocurrent to approximate to 5.57 mA cm(-2) at -0.41 V-RHE in the CZTSiS/CdS/ZnO sample, which is 2.39 times higher than that of pure CZTS. The flat band potential increases from CZTS approximate to 0.43 V-RHE to CZTSiS/CdS/ZnO approximate to 1.31 V-RHE indicating the faster carrier separation process at the electrode-electrolyte interface in the latter sample. CdS/ZnO layers over CZTSiS significantly reduce the charge transfer resistance at the semiconductor-electrolyte interface.

Abstract: The maximum a posteriori (MAP) probability rule for atom column detection can also be used as a tool to evaluate the relation between scanning transmission electron microscopy (STEM) image quality and atom detectability. In this chapter, a new image-quality measure is proposed that correlates well with atom detectability, namely the integrated contrast-to-noise ratio (ICNR). Furthermore, the working principle of the MAP probability rule is described in detail showing a close relation to the principles of model-selection methods.

Abstract: Time evolution of precipitates related to age-hardening in Ti-2.3 wt pct Cu alloys was investigated by electron microscopy. In isothermal aging at 723 K, the hardness increases continuously owing to precipitation strengthening, whereas in two-step aging where the aging temperature is switched from 673 K to 873 K after 100 hours, the hardness is found to drastically drop after the aging temperature switches. In isothermal aging, metastable and stable precipitates are independently nucleated, whereas characteristic V-shaped clusters of precipitates are observed during the two-step aging. It is revealed by atomic-scale observations that the V-shaped clusters are composed of metastable and stable precipitates and each type of precipitate has a different orientation relationship with the alpha phase: (10 (3) over bar)//(0001)(alpha) and [0 (1) over bar0]//respectively. The drop in hardness during two-step aging can be explained by a synergistic effect of decreased precipitation strengthening and solid solution strengthening. (C) The Minerals, Metals & Materials Society and ASM International 2021

Abstract: In this chapter, the principles of statistical parameter estimation theory for a quantitative analysis of atomic-resolution electron microscopy images are introduced. Within this framework, electron microscopy images are described by a parametric statistical model. Here, parametric models are introduced for different types of electron microscopy images: reconstructed exit waves, annular dark-field (ADF) scanning transmission electron microscopy (STEM) images, and simultaneously acquired ADF and annular bright-field (ABF) STEM images. Furthermore, the Cramér-Rao lower bound (CRLB) is introduced, i.e. a theoretical lower bound on the variance of any unbiased estimator. This CRLB is used to quantify the precision of the structure parameters of interest, such as the atomic column positions and the integrated atomic column intensities.

Abstract: The pursuit of two-dimensional (2D) borides, MBenes, has proven to be challenging, not the least because of the lack of a suitable precursor prone to the deintercalation. Here, we studied room-temperature topochemical deintercalation of lithium from the layered polymorphs of the LiNiB compound with a considerable amount of Li stored in between [NiB] layers (33 at. % Li). Deintercalation of Li leads to novel metastable borides (Li similar to 0.5NiB) with unique crystal structures. Partial removal of Li is accomplished by exposing the parent phases to air, water, or dilute HCl under ambient conditions. Scanning transmission electron microscopy and solid-state Li-7 and B-1(1) NMR spectroscopy, combined with X-ray pair distribution function (PDF) analysis and DFT calculations, were utilized to elucidate the novel structures of (Li similar to 0.5NiB) and the mechanism of Li-deintercalation. We have shown that the deintercalation of Li proceeds via a “zip-lock” mechanism, leading to the condensation of single [NiB] layers into double or triple layers bound via covalent bonds, resulting in structural fragments with Li[NiB](2) and Li[NiB](3) compositions. The crystal structure of Li similar to 0.5NiB is best described as an intergrowth of the ordered single [NiB], double [NiB](2), or triple [NiB](3) layers alternating with single Li layers; this explains its structural complexity. The formation of double or triple [NiB] layers induces a change in the magnetic behavior from temperature-independent paramagnets in the parent LiNiB compounds to the spin-glassiness in the deintercalated Li similar to 0.5NiB counterparts. LiNiB compounds showcase the potential to access a plethora of unique materials, including 2D MBenes (NiB).

Abstract: Single-shot structured light profilometry (SLP) aims at reconstructing the 3D height map of an object from a single deformed fringe pattern and has long been the ultimate goal in fringe projection profilometry. Recently, deep learning was introduced into SLP setups to replace the task-specific algorithm of fringe demodulation with a dedicated neural network. Research on deep learning-based profilometry has made considerable progress in a short amount of time due to the rapid development of general neural network strategies and to the transferrable nature of deep learning techniques to a wide array of application fields. The selection of the employed loss function has received very little to no attention in the recently reported deep learning-based SLP setups. In this paper, we demonstrate the significant impact of loss function selection on height map prediction accuracy, we evaluate the performance of a range of commonly used loss functions and we propose a new mixed gradient loss function that yields a higher 3D surface reconstruction accuracy than any previously used loss functions.

Abstract: Atomic arrangements in the mixed-valence oxide U3O7 are refined from high-resolution neutron scattering data. The crystallographic model describes a long-range structural order in a U60O140 primitive cell (space group P42/n) containing distorted cuboctahedral oxygen clusters. By combining experimental data and electronic structure calculations accounting for spin–orbit interactions, we provide robust evidence of an interplay between charge localization and the magnetic moments carried by the uranium atoms. The calculations predict U3O7 to be a semiconducting solid with a band gap of close to 0.32 eV, and a more pronounced charge-transfer insulator behavior as compared to the well-known Mott insulator UO2. Most uranium ions (56 out of 60) occur in 9-fold and 10-fold coordinated environments, surrounding the oxygen clusters, and have a tetravalent (24 out of 60) or pentavalent (32 out of 60) state. The remaining uranium ions (4 out of 60) are not contiguous to the oxygen cuboctahedra and have a very compact, 8-fold coordinated environment with two short (2 × 1.93(3) Å) “oxo-type” bonds. The higher Hirshfeld charge and the diamagnetic character point to a hexavalent state for these four uranium ions. Hence, the valence state distribution corresponds to 24/60 × U(IV) + 32/60 U(V) + 4/60 U(VI). The tetravalent and pentavalent uranium ions are predicted to carry noncollinear magnetic moments (with amplitudes of 1.6 and 0.8 μB, respectively), resulting in canted ferromagnetic order in characteristic layers within the overall fluorite-related structure.