Abstract: Quantitative PCR (qPCR) is broadly used as the gold standard to quantify microbial community fractions in environmental microbiology and biotechnology. Benchmarking efforts to ensure the comparability of qPCR data for environmental bioprocesses are still scarce. Also, for partial nitritation/anammox (PN/A) systems systematic investigations are still missing, rendering meta-analysis of reported trends and generic insights potentially precarious. We report a baseline investigation of the variability of qPCR-based analyses for microbial communities applied to PN/A systems. Round-robin testing was performed for three PN/A biomass samples in six laboratories, using the respective in-house DNA extraction and qPCR protocols. The concentration of extracted DNA was significantly different between labs, ranged between 2.7 and 328 ng mg−1 wet biomass. The variability among the qPCR abundance data of different labs was very high (1−7 log fold) but differed for different target microbial guilds. DNA extraction caused maximum variation (3–7 log fold), followed by the primers (1–3 log fold). These insights will guide environmental scientists and engineers as well as treatment plant operators in the interpretation of qPCR data.

Abstract: Air pollution caused by particulate matter (PM) is a well-known health issue in urban environments. Urban green infrastructure offers opportunities as a nature-based solution to urban PM pollution. Green walls have advantages over other types of urban green infrastructure, since they can be applied to the enormous available wall area in cities and since they do not interfere with the prevailing ventilation resulting in elevated PM levels. However, this has raised questions about the effectiveness of GW in removing PM and this could explain the limited applicability of green walls to tackle PM pollution. Nevertheless, it is suggested that green walls have a significant unexploited potential and this review article aims to address current knowledge gaps and to propose future research requirements for the implementation of green walls to mitigate urban PM pollution. An in-depth analysis is given of the mechanisms behind PM deposition and the influence of vegetation properties on this process, as well as the practices followed to model PM dispersion and deposition. It was suggested that particle deposition on green walls depends on the green wall species, pollution level, and the residence time of PM in a street (canyon). Rainfall plays an important role in the PM pathway, although it is not a necessary requirement to sustain PM deposition on plant leaves. There are still some discrepancies in the literature about the ideal plant characteristics for PM deposition in terms of the macro- and microstructures that require further investigation, especially in comparison with tree and shrub species. In addition, extensively validated models are required to accurately calculate the impact of green walls on air flow and the PM concentration on site.

Abstract: Colloidal nanoparticles (NPs) including nanowires and nanosheets made by chemical methods involve many organic ligands. When the structure of NPs is investigated via transmission electron microscopy (TEM), the organic ligands act as a source for e-beam induced deposition and this causes substantial build-up of carbon layers in the investigated areas, which is typically referred to as “contamination” in the eld of electron mi- croscopy. This contamination is often more severe for scanning TEM, a technique that is based on a focused electron beam and hence higher electron dose rate. In this paper, we report a simple and effective method to clean drop-cast TEM grids that contain NPs with ligands. Using a combination of activated carbon and ethanol, this method effectively reduces the amount of ligands on TEM grids, and therefore greatly improves the quality of electron microscopy images and subsequent analytical measurements. This ef cient and facile method can be helpful during electron microscopy investigation of different kinds of nanomaterials that suffer from ligand- induced contamination.

Abstract: In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, for which a 3D mesh means the inverse process of estimating shapes from projections. In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization. We view the forward projection as a rendering process, and make it differentiable by extending recent work in differentiable rendering. We use the proposed forward model to reconstruct 3D shapes directly from projections. Experimental results for single-object problems show that the proposed method outperforms traditional voxel-based methods on noisy simulated data. We also apply the proposed method on electron tomography images of nanoparticles to demonstrate the applicability of the method on real data.

Abstract: This current review focuses on contributions to amphetamine-type substances (ATS) analysis. This type of synthetic illicit drugs has been increasingly present worldwide reaching 5% of the market on illicit drugs in 2019. The increment of their production in many clandestine laboratories and easy distribution among society are two of the main concerns towards the battle against synthetic drugs. Therefore, the first part of this review details the classification and mechanism of action of ATS in the human body. Second, the pharmacological and toxicological effects of ATS on human health are described to motivate the need of early detection of ATS. Subsequently, the most used laboratory-based and portable methods are presented and critically discussed along the review. Finally, a careful discussion on the advantages and disadvantages of portable techniques employed on the field are addressed as potential tools for on-site ATS detection by law enforcement officers.

Abstract: The illicit consumption of heroin is an increasing concern in our society. For this reason, rapid analytical methods to seize heroin samples in the field are of paramount importance to hinder drug trafficking, and thus prevent the availability of heroin in the drug market. The present work reports on the enriched electrochemical fingerprint of heroin, allowing its selective detection in street samples, based on the use of electrochemical pretreated screen printed electrodes (p-SPE). The voltammetric identification is built on two oxidation peaks of both heroin and its degradation product 6-monoacetylmorphine (6-MAM), generated in alkaline conditions. Interestingly, an anodic pretreatment of the screen printed electrodes (SPE) shifts the peak potential of paracetamol (the most encountered cutting agent in heroin seizures), allowing the detection of 6-MAM peak, overlapping with the paracetamol signal in the case of untreated SPE. Subsequently, the characterization of the p-SPE with scanning electron microscopy, cyclic voltammetry, electrochemical impedance spectroscopy, Raman and Fourier transform infrared (FTIR) spectroscopy is provided to demonstrate local changes on the surface of the electrode. From an analytical perspective, p-SPE provide higher sensitivity (0.019 μA μM-1), excellent reproducibility (6-MAM, RSD = 2.85%, and heroin RSD = 0.91%, n = 5) and lower limits of detection (LOD) (5.2 μM) in comparison to untreated SPE. The proposed protocol which integrates a tailor-made script is interrogated against common cutting agents, and finally, validated with the screening of 14 street samples, also analyzed by standard methods. Besides, a comparison with portable spectroscopic techniques on the confiscated samples shows the better performance of the electrochemical strategy. Overall, this sensing approach offers promising results for the rapid on-site profiling of suspicious heroin samples, also in the presence of paracetamol.

Abstract: Bridging the gap between complex signal data output and clear interpretation by non-expert end-users is a major challenge many scientists face when converting their scientific technology into a real-life application. Currently, pattern recognition algorithms are the most frequently encountered signal data interpretation algorithms to close this gap, not in the least because of their straight-forward implementation via convenient software packages. Paradoxically, just because their implementation is so straight-forward, it becomes cumbersome to integrate the expert's domain-specific knowledge. In this work, a novel signal data interpretation approach is presented that uses this domain-specific knowledge as its fundament, thereby fully exploiting the unique expertise of the scientist. The new approach applies data preprocessing in an innovative way that transcends its usual purpose and is easy to translate into a software application. Multiple case studies illustrate the straight-forward application of the novel approach. Ultimately, the approach is highly suited for integration in various (bio)analytical applications that require interpretation of signal data.

Abstract: Research in plasma reactor designs is developing rapidly as plasma technology is gaining increasing interest for sustainable gas conversion applications, like the conversion of greenhouse gases into value-added chemicals and renewable fuels, and fixation of N₂from air into precursors of mineral fertilizer. As plasma is generated by electric power and can easily be switched on/off, these applications allows for efficient conversion and energy storage of intermittent renewable electricity. In this paper, we present a new comprehensive modelling approach for the design and development of gliding arc plasma reactors, which reveals the fluid dynamics, the arc behaviour and the plasma chemistry by solving a unique combination of five complementary models. This results in a complete description of the plasma process, which allows one to efficiently evaluate the performance of a reactor and indicate possible design improvements before actually building it. We demonstrate the capabilities of this method for an experimentally validated study of plasma-based NO_xformation in a rotating gliding arc reactor, which is gaining increasing interest as a flexible, electricity-driven alternative for the Haber–Bosch process. The model demonstrates the importance of the vortex flow and the presence of a recirculation zone in the reactor, as well as the formation of hot spots in the plasma near the cathode pin and the anode wall that are responsible for most of the NO_xformation. The model also reveals the underlying plasma chemistry and the vibrational non-equilibrium that exists due to the fast cooling during each arc rotation. Good agreement with experimental measurements on the studied reactor design proves the predictive capabilities of our modelling approach.

Abstract: Nitrogen oxides (NOx) and particulate matter (PM) currently are the main pollutants emitted by diesel engines. While there is a start in using hybrid and electric cars, ships will still be fueled by mineral oil products. In the quest to achieve zero-pollution and carbon-free shipping, alternative forms of energy carriers must be found to replace the commonly used mineral oil products. One of the possible alternative fuels is biodiesel. This paper explores the optimization of the composition of biodiesel in order to reduce the concentration of particulate matter and NOx in exhaust gases of a one-cylinder diesel generator.

Abstract: Nowadays, lasers are commonly applied in spectrochemical analysis methods, for sampling, plasma formation or a combination of both. Despite the numerous investigations that have been performed on these applications, the underlying processes are still insufficiently understood. In order to fasten progress in the field and in honor of the lifework of professor Rick Russo, we here provide a brief overview of the fundamental mechanisms in lasermatter interaction as proposed in literature, and throw the spotlight on some aspects that have not received much attention yet. For an organized discussion, we choose laser ablation, laser desorption and the associated gaseous plasma formation as the central processes in this perspective article, based on a classification of the laserbased spectrochemical analysis techniques and the corresponding laser-matter interaction regimes. First, we put the looking glass over the excitation and thermalization mechanisms in the laser-irradiated condensed phase, for which we propose the so-called multi-plasma model. This novel model can be understood as an extension of the well-known two-temperature model, featuring multiple thermodynamic dimensions, each of which corresponds to a quasi-particle type. Next, the focus is placed on the mass transfer and ionization mechanisms, after which we shortly highlight the possible role of anisotropic and magnetic effects in the laser-excited material. We hope this perspective article motivates more fundamental research on laser-matter interaction, as a continuation of the lifework of Rick Russo.

Abstract: Excitonic properties of Ge2H2 and Sn2H2, also known as Xanes, are investigated within the effective mass model. A perpendicularly applied magnetic field induces a negative shift on the exciton center-of-mass kinetic energy that is approximately quadratic with its momentum, thus pushing down the exciton dispersion curve and flattening it. This can be interpreted as an increase in the effective mass of the magneto-exciton, tunable by the field intensity. Our results show that in low effective mass two-dimensional semiconductors, such as Xanes, the applied magnetic field allows one to tune the magneto-exciton effective mass over a wide range of values.

Abstract: Determining the three-dimensional (3D) atomic structure of nanoparticles (NPs) is critical to understand their structure-dependent properties. It is hereby important to perform such analyses under conditions relevant for the envisioned application. Here, we investigate the 3D structure of supported Au NPs at high temperature, which is of importance to understand their behavior during catalytic reactions. To overcome limitations related to conventional high-resolution electron tomography at high temperature, 3D characterization of NPs with atomic resolution has been performed by applying atom-counting using atomic resolution annular darkfield scanning transmission electron microscopy (ADF STEM) images followed by structural relaxation. However, at high temperatures, thermal displacements, which affect the ADF STEM intensities, should be taken into account. Moreover, it is very likely that the structure of a NP investigated at elevated temperature deviates from a ground state configuration, which is difficult to determine using purely computational energy minimization approaches. In this paper, we therefore propose an optimized approach using an iterative local minima search algorithm followed by molecular dynamics (MD) structural relaxation of candidate structures associated with each local minimum. In this manner, it becomes possible to investigate the 3D atomic structure of supported NPs, which may deviate from their ground state configuration.

Abstract: Advances in controlling energy migration pathways in core-shell lanthanide (Ln)-based hetero-nanocrystals (HNCs) have relied heavily on assumptions about how optically active centers are distributed within individual HNCs. In this article, it is demonstrated that different types of interface patterns can be formed depending on shell growth conditions. Such interface patterns are not only identified but also characterized with spatial resolution ranging from the nanometer- to the atomic-scale. In the most favorable cases, atomic-scale resolved maps of individual particles are obtained. It is also demonstrated that, for the same type of core-shell architecture, the interface pattern can be engineered with thicknesses of just 1 nm up to several tens of nanometers. Total alloying between the core and shell domains is also possible when using ultra-small particles as seeds. Finally, with different types of interface patterns (same architecture and chemical composition of the core and shell domains) it is possible to modify the output color (yellow, red, and green-yellow) or change (improvement or degradation) the absolute upconversion quantum yield. The results presented in this article introduce an important paradigm shift and pave the way toward the emergence of a new generation of core-shell Ln-based HNCs with better control over their atomic-scale organization.

Abstract: Amphetamine (AMP) is posing critical issues in our society being one of the most encountered drugs-of-abuse in the current illicit market. The continuous drug production in Europe urges the development of new tools for the rapid on-site determination of illicit drugs such as AMP. However, the direct electrochemical detection of AMP is a challenge because the molecule is non-electroactive at the potential window of conventional graphite SPEs. For this reason, a derivatization step is needed to convert the primary amine into an electroactive oxidizable group. Herein, the rapid electrochemical detection of AMP in seized samples based on the derivatization by 1,2-naphthoquinone-4-sulfonate (NQS) is presented by using square wave voltammetry (SWV) at graphite screen-printed electrodes (SPEs). First, a detailed optimization of the key parameters and the analytical performance is provided. The method showed a sensitivity of 7.9 µA mM-1 within a linear range from 50 to 500 µM, a limit of detection of 22.2 µM, and excellent reproducibility (RSD = 4.3%, n = 5 at 500 µM). Subsequently, the effect of NQS on common cutting agents for the selective detection of AMP is addressed. The comparison of the method with drugs-of-abuse containing secondary and tertiary amines confirms the selectivity of the method. Finally, the concept is applied to quantify AMP in 20 seized samples provided by forensic laboratories, exhibiting an accuracy of 97.3 ± 10.5%. Overall, the fast analysis of samples with the electrochemical profiling of derivatized AMP exhibits a straightforward on-site screening aiming to facilitate the tasks of law enforcement agents in the field.

Abstract: In this work, we report an anomalous phenomenon on superelastic cycling of NiTi shape memory alloys when deforming at the temperature close to the border of superelastic window. New unexpected effects are found-(i) critical stress for inducing martensite transformation during the second loading cycle is higher than that of the first cycle; ( ii ) the plateau stress of the second cycle decreases to the original level when the strain overcomes the limit of the first cycle; ( iii ) transition from good superelasticity in the first cycle to fully irreversible strain in the second. We propose that defects generated during the first superelastic cycle close to the border of superelastic window impede following stress-induced martensitic transformations, leading to the increase of critical stress beyond yield stress of the B2 matrix, and thus functional fatigue of NiTi alloys. (c) 2021 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.