Abstract: The COVID-19 pandemic had large repercussions for our economy and organizations. Improved resilience can give organizations the ability to withstand crises and build back better and faster. This article assesses resilience of organizations and sole proprietorships in the context of the COVID-19 pandemic with eight circular strategies as explanatory variables. Furthermore, these eight circular strategies are also used to assess the organizations' and sole proprietorships' resilience outside of the COVID-19 pandemic. This analysis is conducted to explain how circular strategies can help companies and sole proprietorships maintain stability. The analysis was performed by means of a survey conducted between May and June 2020 in Flanders (Belgium), using a sample of 542 respondents. After performing a regression analysis combined with expert opinions collected through interviews, we find that companies and sole proprietorships with a higher circularity score have a significantly higher resilience score during crises and during normal times, compared to less circular companies. Furthermore, we find that the size of the company does not matter during a crisis to adapt and react flexibly, while it is important when there is no crisis. Finally, we argue that it is the combination of different circular strategies which yields to the highest results for the organizations' resilience and we provide policy recommendations based on the most asked support measures.

Abstract: LNMO (LiNi0.5Mn1.5O4-delta) is a high-energy density positive electrode material for lithium ion batteries. Unfortunately, it suffers from capacity loss and impedance rise during cycling due to electrolyte oxidation and electrode/electrolyte interface instabilities at high operating voltages. Here, a solution-gel synthesis route was used to coat 0.5-2.5 mu m LNMO particles with amorphous Li-Ti-O (LTO) for improved Li conduction, surface structural stability and cyclability. High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) analysis coupled with energy dispersive X-ray (EDX) showed Ti-rich amorphous coatings/islands or Ti-rich spinel layers on many of the LTO-modified LNMO facets, with a thickness varying from about 1 to 10 nm. The surface modification in the form of amorphous islands was mostly possible on high-energy crystal facets. Physicochemical observations were used to propose a molecular mechanism for the surface modification, combining insights from metalorganic chemistry with the crystallographic properties of LNMO. The improvements in functional properties were investigated in half cells. The cell impedance increased faster for the bare LNMO compared to amorphous LTO modified LNMO, resulting in R-ct values as high as 1247 Omega (after 1000 cycles) for bare LNMO, against 216 Omega for the modified material. At 10C, the modified material boosted a 15% increase in average discharge capacity. The improvements in electrochemical performance were attributed to the increase in electrochemically active surface area, as well as to improved HF-scavenging, resulting in the formation of protective byproducts, generating a more stable interface during prolonged cycling.

Abstract: The catalytic performance of heterogeneous catalysts can be tuned by modulation of the size and structure of supported transition metals, which are typically regarded as the active sites. In single-atom metal catalysts, the support itself can strongly affect the catalytic properties. Here, we demonstrate that the size of cerium dioxide (CeO2) support governs the reactivity of atomically dispersed palladium (Pd) in carbon monoxide (CO) oxidation. Catalysts with small CeO2 nanocrystals (~4 nanometers) exhibit unusually high activity in a CO-rich reaction feed, whereas catalysts with medium-size CeO2 (~8 nanometers) are preferred for lean conditions. Detailed spectroscopic investigations reveal support size–dependent redox properties of the Pd-CeO2 interface.

Abstract: The Night Watch, one of the most famous masterpieces by Rembrandt, is the subject of a large research and conservation project. For the conservation treatment, it is of great importance to understand its current condition. Correlated nano-tomography using x-ray fluorescence and ptychography revealed a-so far unknown-lead-containing “layer”, which likely acts as a protective impregnation layer applied on the canvas before the quartz-clay ground was applied. This layer might explain the presence of lead soap protrusions in areas where no other lead components are present. In addition to the three-dimensional elemental mapping, ptychography visualizes and quantifies components not detectable by hard x-ray fluorescence such as the organic fraction and quartz. The first-time use of this combination of synchrotron-based techniques on a historic paint micro-sample shows it to be an important tool to better interpret the results of noninvasive imaging techniques operating on the macroscale.

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: We present a 48-element programmable phase plate for coherent electron waves produced by a combination of photolithography and focused ion beam. This brings the highly successful concept of wavefront shaping from light optics into the realm of electron optics and provides an important new degree of freedom to prepare electron quantum states. The phase plate chip is mounted on an aperture rod placed in the C2 plane of a transmission electron microscope operating in the 100-300 kV range. The phase plate's behavior is characterized by a Gerchberg-Saxton algorithm, showing a phase sensitivity of 0.075 rad/mV at 300 kV, with a phase resolution of approximately 3x10e−3π. In addition, we provide a brief overview of possible use cases and support it with both simulated and experimental results.

Abstract: Methamphetamine (MAP) is a highly addictive and illegal stimulant drug that has a significant impact on the central nervous system. Its detection in biological and street samples is crucial for various organizations involved in forensic medicine, anti-drug efforts, and clinical diagnosis. In recent years, nanotechnology and nanomaterials have played a significant role in the development of analytical sensors for MAP detection. In this study, a fast, simple, and cost-effective electrochemical sensor is presented that is used for the sensitive detection of MAP in confiscated street samples with a complex matrix. The optimized screen-printed sensor based on a carbon working electrode modified with graphene demonstrated an excellent limit of detection, good sensitivity, and a wide dynamic range (1–500 μM) for the target illicit drug both for standard solutions and real samples (seized samples, tap water, and wastewater samples). It can detect MAP at concentrations as low as 300 nM in real samples. This limit of detection is suitable for the rapid preliminary screening of suspicious samples in customs, ports, airports, and on the street. Furthermore, the sensor exhibits a good recovery rate, indicating its reliability and repeatability. This quality is crucial for ensuring consistent and accurate results during screening processes.

Abstract: Out-of-equilibrium self-assembly of metal nanoparticles (NPs) has been devised using different types of strategies and fuels, but the achievement of finite 3D structures with a controlled morphology through this assembly mode is still rare. Here we used a spherical peptide-gold superstructure (PAuSS) as a template to control the out-of-equilibrium self-assembly of Au NPs, obtaining a transient 3D branched Au-nanoshell (BAuNS) stabilized by sodium dodecyl sulphate (SDS). The BAuNS dismantled upon concentration gradient equilibration over time in the solution, leading to NPs disassembly. Notably, BAuNS assembly and disassembly favoured temporary interparticle plasmonic coupling, leading to a remarkable oscillation of their optical properties.

Abstract: The colloidal synthesis of functional nanoparticles has gained tremendous scientific attention in the last decades. In parallel to these advancements, another rapidly growing area is the self-assembly or self-organization of these colloidal nanoparticles. First, the organization of nanoparticles into ordered structures is important for obtaining functional interfaces that extend or even amplify the intrinsic properties of the constituting nanoparticles at a larger scale. The synthesis of large-scale interfaces using complex or intricately designed nanostructures as building blocks, requires highly controllable self-assembly techniques down to the nanoscale. In certain cases, for example, when dealing with plasmonic nanoparticles, the assembly of the nanoparticles further enhances their properties by coupling phenomena. In other cases, the process of self-assembly itself is useful in the final application such as in sensing and drug delivery, amongst others. In view of the growing importance of this field, this review provides a comprehensive overview of the recent developments in the field of nanoparticle self-assembly and their applications. For clarity, the self-assembled nanostructures are classified into two broad categories: finite clusters/patterns, and infinite films. Different state-of-the-art techniques to obtain these nanostructures are discussed in detail, before discussing the applications where the self-assembly significantly enhances the performance of the process.

Abstract: Lignin determination in lignocellulose with the conventional two-step acid hydrolysis method is highly laborious and time-consuming. However, its quantification is crucial to monitor fungal pretreatment of wood, as the increase of acid-insoluble lignin (AIL) degradation linearly correlates with the achievable enzymatic saccharification yield. Therefore, in this study, a new attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy method was developed to track fungal delignification in an easy and rapid manner. Partial least square regression (PLSR) with cross-validation (CV) was applied to correlate the ATR-FTIR spectra with the AIL content (19.9%–27.1%). After variable selection and normalization, a PLSR model with a high coefficient of determination (

Abstract: Gian Giacomo Inchiocchio (1604-1656), better known as Barbelli, was one of the main exponents of Lombard painting of the seventeenth century. A large body of work is attributed to him, encompassing a wide range of drawings, murals, and oil paintings. However, despite his broad production, there are still many open questions regarding his painting techniques and materials. In this paper, a multi-analytical study of the cycle Stories of the life of Saint George that originally decorated the presbytery of the parish church of Casaletto Vaprio (Cremona, Italy) was performed, combining non-invasive techniques with the characterisation of selected micro samples. Results show that Barbelli used a very limited number of inorganic pigments, often mixing them together to create different colours and shades. Remains of caseinate and degradation products (i.e. weddellite and whewellite) related to the strappo intervention were also highlighted. The study helped to decipher the materials and technique of this painting, providing data that can be used as a reference to study his extensive production.

Abstract: Plasma degradation is one of the most effective methods for the abatement of greenhouse gas sulfur hexafluoride
(SF6). To evaluate the potential of MgO as a catalyst in plasma degradation, we investigate the catalytic properties
of MgO on SF6 adsorption and activation by density functional theory (DFT) where the O-defective and
hydroxylated surfaces are considered as two typical plasma-generated surfaces. Our results show that perfect
MgO (001) and (111) surfaces cannot interact with SF6 and only physical adsorption happens. In case of Odefective
MgO surfaces, the O vacancy is the most stable adsorption site. SF6 undergoes a decomposition to SF5
and F over the O-defective MgO (001) surface and undergoes an elongation of the bottom S-F bond over the Odefective
(111) surface. Besides, SF6 shows a physically adsorption at the stepsite of the MgO (001) surface,
accompanied by small changes in its bond angle and length. Furthermore, SF6 is found to be physically and
chemically adsorbed over 0.5 and 1.0 ML (monolayer) H-covered O-terminated MgO (111) surfaces, respectively.
The SF6 molecule undergoes a self-decomposition on the 1.0 ML hydroxylated surface via a surface bonding
process. This study shows that defective and hydroxylated MgO surfaces have the surface capacities for SF6
activation, which shows that MgO has potential as packing material in SF6 waste treatment in packed-bed
plasmas.

Abstract: Air quality currently poses a major risk for human health. Currently, diesel is widely used as fuel and is a significant source of nitrogen oxides (NOx) and particulate matter (PM), both hazardous to human health. A good alternative for mineral diesel is biodiesel, not only for the improvement of hazardous components in the exhaust gases but also because it can be produced in view of a circular economy. Biodiesel consists of a mix of different fatty acid methyl esters, which can react with oxygen. As a consequence, the oxidation stability of biodiesel has to be studied, because the oxidation of biodiesel could affect the performance of the engine due to the wear of injectors and fuel pumps. The oxidation stability could also affect the quality of the exhaust gases due to increases in NOx and PM. The basic question we try to answer in this communication is: 'Can we find an optimal fatty acid composition in order to have a maximal oxidation stability?' In this article, we try to find the optimal fatty acid composition according to the five most common fatty acid methyl esters present in biodiesel in order to reach a maximal oxidation stability. The measurements and statistical analysis show, however, that there is no useful regression model because there are statistically significant two- and three-way interactions among the different fatty acids.

Abstract: Preston's equation is a general model describing the egg shape of birds. The parameters of Preston's equation are usually estimated after re-expressing it as the Todd-Smart equation and scaling the egg's actual length to two. This method assumes that the straight line through the two points on an egg's profile separated by the maximum distance (i.e., the longest axis of an egg's profile) is the mid-line. It hypothesizes that the photographed egg's profile is perfectly bilaterally symmetrical, which seldom holds true because of photographic errors and placement errors. The existing parameter estimation method for Preston's equation considers an angle of deviation for the longest axis of an egg's profile from the mid-line, which decreases prediction errors to a certain degree. Nevertheless, this method cannot provide an accurate estimate of the coordinates of the egg's center, and it leads to sub-optimal parameter estimation. Thus, it is better to account for the possible asymmetry between the two sides of an egg's profile along its mid-line when fitting egg-shape data. In this paper, we propose a method based on the optimization algorithm (optimPE) to fit egg-shape data and better estimate the parameters of Preston's equation by automatically searching for the optimal mid-line of an egg's profile and testing its validity using profiles of 59 bird eggs spanning a wide range of existing egg shapes. We further compared this method with the existing one based on multiple linear regression (lmPE). This study demonstrated the ability of the optimPE method to estimate numerical values of the parameters of Preston's equation and provide the theoretical egg length (i.e., the distance between two ends of the mid-line of an egg's profile) and the egg's maximum breadth. This provides a valuable approach for comparing egg shapes among conspecifics or across different species, or even different classes (e.g., birds and reptiles), in future investigations.