Abstract: For the isocratic ion chromatography (IC) separation of low-molecular-mass organic acids and inorganic anions three different anion-exchange columns were studied: IonPac AS14 (9 ìm particle size), Allsep A-2 (7 ìm particle size), and IC SI-50 4E (5 ìm particle size). A complete baseline separation for all analyzed anions (i.e., F−, acetate, formate, Cl−, NO2−, Br−, NO3−, HPO42− and SO42−) in one analytical cycle of shorter than 17 min was achieved on the IC SI-50 4E column, using an eluent mixture of 3.2 mM Na2CO3 and 1.0 mM NaHCO3 with a flow rate of 1.0 mL min−1. On the IonPac AS14 column, it was possible to separate acetate from inorganic anions in one run (i.e., less than 9 min), but not formate, under the following conditions: 3.5 mM Na2CO3 plus 1.0 mM NaHCO3 with a flow rate of 1.2 mL min−1. Therefore, it was necessary to adapt a second run with a 2.0 mM Na2B4O7 solution as an eluent under a flow rate of 0.8 mL min−1 for the separation of organic ions, which considerably enlarged the analysis time. For the Allsep A-2 column, using an eluent mixture of 1.2 mM Na2CO3 plus 1.5 mM NaHCO3 with a flow rate of 1.6 mL min−1, it was possible to separate almost all anions in one run within 25 min, except the fluoride-acetate critical pair. A Certified Multianion Standard Solution PRIMUS for IC was used for the validation of the analytical methods. The lowest RSDs (less than 1%) and the best LODs (0.02, 0.2, 0.16, 0.11, 0.06, 0.05, 0.04, 0.14 and 0.09 mg L−1 for F−, Ac−, For−, Cl−, NO2−, Br−, NO3−, HPO42− and SO42−, respectively) were achieved using the IC SI-50 4E column. This column was applied for the separation of concerned ions in environmental precipitation samples such as snow, hail and rainwater.

Abstract: By 2050, the world population will have considerably expanded and the life standard of many will increase, yielding a 50% higher demand in protein (FAO, 2011), and even increases of 82 and 102% for diary and meat products, respectively (Boland et al., 2013). To provide in this increasing demand we are highly dependent on our classical fertilizer to food chain which has a high environmental impact and lacks efficiency. Nutrient losses cause eutrophication and biodiversity loss and the input of resources is already beyond the boundaries of environmental sustainability (Steffen et al., 2015). Phosphate fertilizers are made from phosphate rock (apatite), of which the reserves are predicted to be depleted within 50 100 years if we continue business as usual (Cordell et al., 2009). Next to problems related to the unbalanced geopolitical distribution with dominance in China and Morocco, the decreasing quality of the remaining apatite will result in an increasing environmental impact of fertilizer production. Finally, our traditional food production model requires 30% of all ice-free land, 70% of all available freshwater and produces up to one third of the global greenhouse gas emission, of which 80 to 86% is linked to agricultural production (Vermeulen et al., 2012). To ensure food security, nutrient recovery from waste streams can provide an important strategy. In this context, struvite ( ) crystallisation may be applied to recover phosphorus, along with some nitrogen. Reusing these nutrients as agricultural fertilizer on the field will lead to considerable losses to the environment. In contrast, their use to cultivate micro-organisms, e.g. for single cell protein (SCP), offers to potential of a near perfect conversion efficiency (Moed et al., 2015). At this moment, microalgae represent the most developed type of SCP, and are a promising protein source due to their growth rate, high nutritional quality and extremely high nutrient usage efficiency (Becker, 2007). Reliable solubilisation data are essential to design a technological strategy for struvite dosage in bioreactors for SCP production. The effect on solubility and solubilisation rate of relevant physicochemical parameters was studied experimentally in aqueous solutions. Because pH and temperature greatly affect solubilisation kinetics they were set at a constant value of 7 and 20°C respectively. The effect of some parameters on struvite solubility was already studied (Bhuiyan et al., 2007; Ariyanto et al., 2014; Roncal-Herrero and Oelkers, 2011), but solubilisation rates were not yet considered and pH was not controlled at a constant value. The chemical parameters considered in this study include the concentration of different common ions ( and ), foreign ions ( and the chelating agent ethylenediaminetetraacetic acid, EDTA) present in micro-algal cultivation media as well as ionic strength (as set by NaCl). The main physical parameter included was contact surface, through variation in initial particle size and as well as in struvite dosage concentration.

Abstract: The neutron flux distribution in the vicinity of 30, 20 and 10 mm diameter targets is measured by irradiating concentric ring-type iron monitors at different distances from the target and counting the induced56Mn activity. Considering the many uncertainties, satisfactory agreement was found between theory and experiment.

Abstract: Difficulties in the production of lignin from rice straw because of high silica content in the recovered lignin reduce its recovery yield and applications as bio-fuel and aromatic chemicals. Therefore, the objective of this study is to develop a novel method to reduce the silica content in lignin from rice straw more effectively and selectively. The method is established by monitoring the precipitation behavior as well as the chemical structure of precipitate by single-stage acidification at different pH values of black liquor collected from the alkaline treatment of rice straw. The result illustrates the significant influence of pH on the physical and chemical properties of the precipitate and the supernatant. The simple two-step acidification of the black liquor at pilot-scale by sulfuric acid 20w/v% is applied to recover lignin at pH 9 and pH 3 and gives a percentage of silica removal as high as 94.38%. Following the developed process, the high-quality lignin could be produced from abundant rice straw at the industrial-scale.

Abstract: Various theoretical and experimental methods are utilized to investigate the thermal conductivity of nanostructured materials; this is a critical parameter to increase performance of thermoelectric devices. Among these methods, equilibrium molecular dynamics (EMD) is an accurate technique to predict lattice thermal conductivity. In this study, by means of systematic EMD simulations, thermal conductivity of bulk Si-Ge structures (pristine, alloy and superlattice) and their nanostructured one dimensional forms with square and circular cross-section geometries (asymmetric and symmetric) are calculated for different crystallographic directions. A comprehensive temperature analysis is evaluated for selected structures as well. The results show that one-dimensional structures are superior candidates in terms of their low lattice thermal conductivity and thermal conductivity tunability by nanostructuring, such as by diameter modulation, interface roughness, periodicity and number of interfaces. We find that thermal conductivity decreases with smaller diameters or cross section areas. Furthermore, interface roughness decreases thermal conductivity with a profound impact. Moreover, we predicted that there is a specific periodicity that gives minimum thermal conductivity in symmetric superlattice structures. The decreasing thermal conductivity is due to the reducing phonon movement in the system due to the effect of the number of interfaces that determine regimes of ballistic and wave transport phenomena. In some nanostructures, such as nanowire superlattices, thermal conductivity of the Si/Ge system can be reduced to nearly twice that of an amorphous silicon thermal conductivity. Additionally, it is found that one crystal orientation, <100>, is better than the <111> crystal orientation in one-dimensional and bulk SiGe systems. Our results clearly point out the importance of lattice thermal conductivity engineering in bulk and nanostructures to produce high-performance thermoelectric materials.

Abstract: Understanding chemical reactivity and magnetism of 3<italic>d</italic>transition metal nanoparticles is of fundamental interest for applications in fields ranging from spintronics to catalysis. Here, we present an atomistic picture of the early stage of the oxidation mechanism and its impact on the magnetism of Co nanoparticles. Our experiments reveal a two-step process characterized by (i) the initial formation of small CoO crystallites across the nanoparticle surface, until their coalescence leads to structural completion of the oxide shell passivating the metallic core; (ii) progressive conversion of the CoO shell to Co₃O₄and void formation due to the nanoscale Kirkendall effect. The Co nanoparticles remain highly reactive toward oxygen during phase (i), demonstrating the absence of a pressure gap whereby a low reactivity at low pressures is postulated. Our results provide an important benchmark for the development of theoretical models for the chemical reactivity in catalysis and magnetism during metal oxidation at the nanoscale.

Abstract: Egg geometry can be described using Preston's equation, which has seldom been used to calculate egg volume (V) and surface area (S) to explore S versus V scaling relationships. Herein, we provide an explicit re-expression of Preston's equation (designated as EPE) to calculate V and S, assuming that an egg is a solid of revolution. The side (longitudinal) profiles of 2221 eggs of six avian species were digitized, and the EPE was used to describe each egg profile. The volumes of 486 eggs from two avian species predicted by the EPE were compared with those obtained using water displacement in graduated cylinders. There was no significant difference in V using the two methods, which verified the utility of the EPE and the hypothesis that eggs are solids of revolution. The data also indicated that V is proportional to the product of egg length (L) and maximum width (W) squared. A 2/3-power scaling relationship between S and V for each species was observed, that is, S is proportional to (LW2)(2/3). These results can be extended to describe the shapes of the eggs of other species to study the evolution of avian (and perhaps reptilian) eggs.

Abstract: Electron energy loss spectroscopy (EELS) is a well established technique in electron microscopy that yields information on the elemental content of a sample in a very direct manner. One of the persisting limitations of EELS is the requirement for manual identification of core-loss edges and their corresponding elements. This can be especially bothersome in spectrum imaging, where a large amount of spectra are recorded when spatially scanning over a sample area. This paper introduces a synthetic dataset with 736,000 labeled EELS spectra, computed from available generalized oscillator strength tables, that represents 107 K, L, M or N core-loss edges and 80 chemical elements. Generic lifetime broadened peaks are used to mimic the fine structure due to band structure effects present in experimental core-loss edges. The proposed dataset is used to train and evaluate a series of neural network architectures, being a multilayer perceptron, a convolutional neural network, a U-Net, a residual neural network, a vision transformer and a compact convolutional transformer. An ensemble of neural networks is used to further increase performance. The ensemble network is used to demonstrate fully automated elemental mapping in a spectrum image, both by directly mapping the predicted elemental content and by using the predicted content as input for a physical model-based mapping.

Abstract: Two electrochemical methodologies, i.e. flowchart and dual-sensor, were developed to aid law enforcement present at festivals to obtain a rapid indication of the presence of four illicit drugs in suspicious samples encountered.

Abstract: Advanced electron microscopy techniques, including scanning electron microscopes (SEM), scanning transmission electron microscopes (STEM), and transmission electron microscopes (TEM), have revolutionized imaging capabilities. However, achieving high-quality experimental images remains a challenge due to various distortions stemming from the instrumentation and external factors. These distortions, introduced at different stages of imaging, hinder the extraction of reliable quantitative insights. In this paper, we will discuss the main sources of distortion in TEM and S(T)EM images, develop models to describe them, and propose a method to correct these distortions using a convolutional neural network. We validate the effectiveness of our method on a range of simulated and experimental images, demonstrating its ability to significantly enhance the signal-to-noise ratio. This improvement leads to a more reliable extraction of quantitative structural information from the images. In summary, our findings offer a robust framework to enhance the quality of electron microscopy images, which in turn supports progress in structural analysis and quantification in materials science and biology.

Abstract: In this study, we explore the possibility to use deep learning for the reconstruction of phase images from 4D scanning transmission electron microscopy (4D-STEM) data. The process can be divided into two main steps. First, the complex electron wave function is recovered for a convergent beam electron diffraction pattern (CBED) using a convolutional neural network (CNN). Subsequently, a corresponding patch of the phase object is recovered using the phase object approximation. Repeating this for each scan position in a 4D-STEM dataset and combining the patches by complex summation yields the full-phase object. Each patch is recovered from a kernel of 3x3 adjacent CBEDs only, which eliminates common, large memory requirements and enables live processing during an experiment. The machine learning pipeline, data generation, and the reconstruction algorithm are presented. We demonstrate that the CNN can retrieve phase information beyond the aperture angle, enabling super-resolution imaging. The image contrast formation is evaluated showing a dependence on the thickness and atomic column type. Columns containing light and heavy elements can be imaged simultaneously and are distinguishable. The combination of super-resolution, good noise robustness, and intuitive image contrast characteristics makes the approach unique among live imaging methods in 4D-STEM.

Abstract: Gels are a popular cleaning method for paper conservators and a lot of research has been done concerning gel cleaning of paper objects over the last 15 years. Despite the close interconnection between the conservation fields of paper and photographic material, research on using gels for cleaning photographs is very scarce. However, gels can provide an excellent cleaning method for photographic material. Cleaning silver gelatine prints with aqueous solvents is very complex due to the hydrophilic properties and fragility of the gelatine layer which makes mechanical cleaning difficult. The properties of gels ensure better control over the flow and evaporation of the solvent, facilitating the cleaning process. This study is the first insight into the viability of using gellan gum gel and polyvinyl acetate-borax (PVAc-borax) gel to clean contaminants from the surface of silver gelatine photographs. It is based on self-made samples that were artificially aged and contaminated with soot. Water, ethanol (EtOH), and Kodak Photo-flo were studied as solvents to remove the soot from the silver gelatine-based prints. These solvents were loaded into the aforementioned gels and applied to the samples in two different methods. These gel cleaning methods were subsequently compared with traditional cleaning methods. In addition, the usage of cyclomethicone D4 as a protective mask for the gelatine layer was studied. Measuring methods used to evaluate the cleaning were visual comparison, microscopic observation, and densitometry. ATR-FTIR measurements were also conducted to investigate potential side-effects of the cleaning methods on the prints, such as unwanted chemical transformations or the presence of gel residues after the treatments. Most of the gel cleaning methods within this study proved to be inadequate, with the exception of the gellan gum gel loaded with 30% EtOH. It was used as a granulated gel applied mechanically on a print saturated with cyclomethicone (octamethylcyclotetrasiloxane D4). Cyclomethicone proved to be a very effective protective barrier for the water-sensitive gelatine layer with minimal reduction in cleaning effectiveness.

Abstract: Weak interlayer van der Waals (vdW) bonding has significant impact on the surface/interface structure, electronic properties, and transport properties of vdW layered materials. Unraveling the complex atomistic dynamics and structural evolution at vdW surfaces is therefore critical for the design and synthesis of the next-generation vdW layered materials. Here, we show that Ge/Bi cation diffusion along the vdW gap in layered GeBi2Te4 (GBT) can be directly observed using in situ heating scanning transmission electron microscopy (STEM). The cation concentration variation during diffusion was correlated with the local Te-6 octahedron distortion based on a quantitative analysis of the atomic column intensity and position in time-elapsed STEM images. The in-plane cation diffusion leads to out-of-plane surface etching through complex structural evolutions involving the formation and propagation of a non-centrosymmetric GeTe2 triple layer surface reconstruction on fresh vdW surfaces, and GBT subsurface reconstruction from a septuple layer to a quintuple layer. Our results provide atomistic insight into the cation diffusion and surface reconstruction in vdW layered materials. Weak interlayer van der Waals (vdW) bonding has significant impact on the structure and properties of vdW layered materials. Here authors use in-situ aberration-corrected ADF-STEM for an atomistic insight into the cation diffusion in the vdW gaps and the etching of vdW surfaces at high temperatures.

Abstract: Recent experiments demonstrated that proton transport through graphene electrodes can be accelerated by over an order of magnitude with low intensity illumination. Here we show that this photo-effect can be suppressed for a tuneable fraction of the infra-red spectrum by applying a voltage bias. Using photocurrent measurements and Raman spectroscopy, we show that such fraction can be selected by tuning the Fermi energy of electrons in graphene with a bias, a phenomenon controlled by Pauli blocking of photo-excited electrons. These findings demonstrate a dependence between graphene's electronic and proton transport properties and provide fundamental insights into molecularly thin electrode-electrolyte interfaces and their interaction with light. Recent experiments have shown that proton transport through graphene electrodes can be promoted by light, but the understanding of this phenomenon remains unclear. Here, the authors report the electrical tunability of this photo-effect, showing a connection between graphene electronic and proton transport properties.