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: 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: Tailoring heat treatments for Laser Powder Bed Fusion (LPBF) processed materials is critical to ensure superior and repeatable material properties for high-end applications. This tailoring requires in-depth understanding of the LPBF-processed material. Therefore, the current study aims at unravelling the threefold interrelationship between the process (LPBF and heat treatment), the microstructure at different scales (macro-, meso-, micro-, and nano-scale), and the macroscopic material properties of AlSi10Mg. A similar solidification trajectory applies at different length scales when comparing the solidification of AlSi10Mg, ranging from mould-casting to rapid solidification (LPBF). The similarity in solidification trajectories triggers the reason why the Brody-Flemings cellular microsegregation solidification model could predict the cellular morphology of the LPBF as-printed microstructure. Where rapid solidification occurs at a much finer scale, the LPBF microstructure exhibits a significant grain refinement and a high degree of silicon (Si) supersaturation. This study has identified the grain refinement and Si supersaturation as critical assets of the as-printed microstructure, playing a vital role in achieving superior mechanical and thermal properties during heat treatment. Next, an electrical conductivity model could accurately predict the Si solute concentration in LPBF-processed and heat-treated AlSi10Mg and allows understanding the microstructural evolution during heat treatment. The LPBF-processed and heat-treated AlSi10Mg conditions (as-built (AB), direct-aged (DA), stress-relieved (SR), preheated (PH)) show an interesting range of superior mechanical properties (tensile strength: 300-450 MPa, elongation: 4-13%) compared to the mould-cast T6 reference condition.

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: Plasma reactors are interesting for gas-based chemical conversion but the fundamental relation between the plasma chemistry and selected conditions remains poorly understood. Apparent kinetic parameters for the loss and formation processes of individual components of gas conversion processes, can however be extracted by performing experiments in an extended residence time range (2–75 s) and fitting the gas composition to a firstorder kinetic model of the evolution towards partial chemical equilibrium (PCE). We specifically investigated the differences in kinetic characteristics and PCE state of the CO2 dissociation and CH4 reforming reactions in a dielectric barrier discharge reactor (DBD), how these are mutually affected when combining both gases in the dry reforming of methane (DRM) reaction, and how they change when a packing material (non-porous SiO2) is added to the reactor. We find that CO2 dissociation is characterized by a comparatively high reaction rate of 0.120 s−1 compared to CH4 reforming at 0.041 s−1; whereas CH4 reforming reaches higher equilibrium conversions, 82% compared to 53.6% for CO2 dissociation. Combining both feed gases makes the DRM reaction to proceed at a relatively high rate (0.088 s−1), and high conversion (75.4%) compared to CO2 dissociation, through accessing new chemical pathways between the products of CO2 and CH4. The addition of the packing material can also distinctly influence the conversion rate and position of the equilibrium, but its precise effect depends strongly on the gas composition. Comparing different CO2:CH4 ratios reveals the delicate balance of the combined chemistry. CO2 drives the loss reactions in DRM, whereas CH4 in the mixture suppresses back reactions. As a result, our methodology provides some of the insight necessary to systematically tune the conversion process.

Abstract: Detection of antigenic biomarkers present in trace amounts is of crucial importance for medical diagnosis. A parasitic disease, human toxocariasis, lacks an adequate diagnostic method despite its worldwide occurrence. The currently used serology tests may stay positive even years after a possibly unnoticed infection, whereas the direct detection of a re-infection or a still active infection remains a diagnostic challenge due to the low concentration of circulating parasitic antigens. We report a time-efficient sandwich immunosensor using small recombinant single-domain antibodies (nanobodies) derived from camelid heavy-chain antibodies specific to Toxocara canis antigens. An enhanced sensitivity to pg/mL levels is achieved by using a redox cycle consisting of a photocatalytic oxidation and electrochemical reduction steps. The photocatalytic oxidation is achieved by a photosensitizer generating singlet oxygen (1O2) that, in turn, readily reacts with p-nitrophenol enzymatically produced under alkaline conditions. The photooxidation produces benzoquinone that is electrochemically reduced to hydroquinone, generating an amperometric response. The light-driven process could be easily separated from the background, thus making amperometric detection more reliable. The proposed method for detection of the toxocariasis antigen marker shows superior performances compared to other detection schemes with the same nanobodies and outperforms by at least two orders of magnitude the assays based on regular antibodies, thus suggesting new opportunities for electrochemical immunoassays of challenging low levels of antigens.

Abstract: We calculate the Curie temperature of layered ferromagnets, chromium tri-iodide (CrI3), chromium tri-bromide (CrBr3), chromium germanium tri-telluride (CrGeTe3), and the Ned temperature of a layered antiferromagnet iron di-chloride (FeCl2), using first-principles density functional theory calculations and Monte Carlo simulations. We develop a computational method to model the magnetic interactions in layered magnetic materials and calculate their critical temperature. We provide a unified method to obtain the magnetic exchange parameters (J) for an effective Heisenberg Hamiltonian from first principles, taking into account both the magnetic ansiotropy as well as the out-of-plane interactions. We obtain the magnetic phase change behavior, in particular the critical temperature, from the susceptibility and the specific-heat, calculated using the three-dimensional Monte Carlo (METROPOLIS) algorithm. The calculated Curie temperatures for ferromagnetic materials (CrI3, CrBr3, and CrGeTe3), match well with experimental values. We show that the interlayer interaction in bulk CrI3 with R (3) over bar stacking is significantly stronger than the C2/m stacking, in line with experimental observations. We show that the strong interlayer interaction in R (3) over bar CrI3 results in a competition between the in-plane and the out-of-plane magnetic easy axes. Finally, we calculate the Ned temperature of FeCl2 to be 47 +/- 8 K and show that the magnetic phase transition in FeCl2 occurs in two steps with a high-temperature intralayer ferromagnetic phase transition and a low-temperature interlayer antiferromagnetic phase transition.

Abstract: We present a computational model to model the magnetic structure of two-dimensional (2D) dilute-magnetic-semiconductors (DMS) both the monolayers and multilayers using first-principles density functional theory (DFT), as well as their magnetic phase transition as a function of temperature using Monte-Carlo simulations. Using our method, we model the magnetic structure of bulk, bilayer, and monolayer MoS2 substitutionally doped with Fe atoms. We find that the out-of-plane interaction in bilayer MoS2 is weakly ferromagnetic, whereas in bulk MoS2 it is strongly anti-ferromagnetic. Finally, we show that the magnetic order is more robust in bilayer Fe-doped MoS2 compared to the monolayer and results in a room-temperature FM at an atomic substitution of 14-16%.

Abstract: This article describes the development of an electrochemical screening strategy for 3,4-methylenedioxymethamphetamine (MDMA), the regular psychoactive compound in ecstasy (XTC) pills. We have investigated the specific electrochemical profile of MDMA and its electro-oxidation mechanisms at disposable graphite screen-printed electrodes. We have proved that the formation of a radical cation and subsequent reactions are indeed responsible for the electrode surface passivation, as evidenced by using electron paramagnetic resonance spectroscopy and electrochemistry. Thereafter, pure cutting agents and MDMA as well as simulated binary mixtures of compounds with MDMA were subjected to square wave voltammetry at pH 7 to understand the characteristic electrochemical profile. An additional measurement at pH 12 was able to resolve false positives and negatives occurring at pH 7. Finally, validation of the screening strategy was done by measuring a set of ecstasy street samples. Overall, our proposed electrochemical screening strategy has been demonstrated for the rapid, sensitive, and selective detection of MDMA, resolving most of the false positives and negatives given by the traditional Marquis color tests, thus exhibiting remarkable promises for the on-site screening of MDMA.

Abstract: Reaction of (2,3,9,10,16,17,23,24-octabutylphthalocyaninato)lanthanide(iii) acetylacetonates ((Bu)PcLn(acac), 1a-c, Ln = Lu (a), Eu (b), La (c)) with a tetrakis(5,7-bis(4-tert-butylphenyl)-6H-1,4-diazepino)[2,3-b,g,l,q]porphyrazine ligand ((tBuPh)DzPzH(2), 2) produced sandwich compounds ((tBuPh)DzPz)Ln(Pc-Bu) (3a-c), which represent the first heteroleptic double-deckers incorporating both Pc and DzPz decks. A combination of high-resolution mass spectrometry, UV-Vis/NIR, MCD, and H-1 NMR spectroscopy, and square-wave voltammetry provided unambiguous characterization of target complexes 3 indicating that their spectral and electrochemical properties are generally intermediate with respect to their homoleptic relatives. Based on the data of solution-state H-1-H-1 NMR (COSY, NOESY) correlation spectroscopy supported by DFT calculations, a dimerization tendency of compounds 3 proportional to the Ln(iii) ion size was found. The spectroelectrochemical study of 3 and the corresponding homoleptic double-deckers revealed a pronounced tendency to aggregation of the one-electron oxidized forms of DzPz-containing double-decker complexes compared to homoleptic Pc(2)Ln compounds.

Abstract: Two-dimensional crystals with angstrom-scale pores are widely considered as candidates for a next generation of molecular separation technologies aiming to provide extreme, exponentially large selectivity combined with high flow rates. No such pores have been demonstrated experimentally. Here we study gas transport through individual graphene pores created by low intensity exposure to low kV electrons. Helium and hydrogen permeate easily through these pores whereas larger species such as xenon and methane are practically blocked. Permeating gases experience activation barriers that increase quadratically with molecules' kinetic diameter, and the effective diameter of the created pores is estimated as similar to 2 angstroms, about one missing carbon ring. Our work reveals stringent conditions for achieving the long sought-after exponential selectivity using porous two-dimensional membranes and suggests limits on their possible performance. Two-dimensional membranes with angstrom-sized pores are predicted to combine high permeability with exceptional selectivity, but experimental demonstration has been challenging. Here the authors realize angstrom-sized pores in monolayer graphene and demonstrate gas transport with activation barriers increasing quadratically with the molecular kinetic diameter.

Abstract: Aptamers have come in the spotlight as bio-mimetic molecular recognition elements in the field of biomedicine due to various applications in diagnostics, drug delivery, therapeutics, and pharmaceutical analysis. Aptamers are composed of nucleic acid strands (DNA or RNA) that can specifically interact in a three-dimensional tailored design with the target molecule. The basic method to generate aptamers is Systematic Evolution of Ligands by Exponential Enrichment (SELEX). Recent technological advances in aptamer selection allow for faster and cheaper production of a new generation of high-affinity aptamers compared to the traditional SELEX, which can last up to several months. Rigorous characterization performed by multiple research groups endorsed several well-defined aptamer sequences. Binding affinity, nature of the biomolecular interactions and structural characterization are of paramount importance for aptamer screening and development of applications. However, remarkable challenges still need to be dealt with before the aptamers can make great contributions to the biomedical field. Poor specificity and sensitivity, questionable clinical use, low drug loading, in vivo stability and toxicity are only some of the identified challenges. This review accounts for the 30th celebration of the SELEX technology underlining the most important aptamers' achievements in the biomedical field within mostly the past five years. Aptamers' advantages over antibodies are discussed. Because of potential clinical translational utility, insights of remarkable developments in aptamer-based methods for diagnosis and monitoring of disease biomarkers and pharmaceuticals are discussed focusing on the recent studies (2015-2020). The current challenges and promising opportunities for aptamers for therapeutic and theragnostic purposes are also presented. (C) 2021 Elsevier Ltd. All rights reserved.

Abstract: The urgency for a protein transition towards more sustainable solutions is one of the major societal challenges. Microbial protein is one of the alternative routes, in which land- and fossil-free production should be targeted. The photohydrogenotrophic growth of purple bacteria, which builds on the H2– and CO2-economy, is unexplored for its microbial protein potential. The three tested species (Rhodobacter capsulatus, Rhodobacter sphaeroides and Rhodopseudomonas palustris) obtained promising growth rates (2.3–2.7 d−1 at 28°C) and protein productivities (0.09–0.12 g protein L−1 d−1), rendering them likely faster and more productive than microalgae. The achieved protein yields (2.6–2.9 g protein g−1 H2) transcended the ones of aerobic hydrogen oxidizing bacteria. Furthermore, all species provided full dietary protein matches for humans and their fatty acid content was dominated by vaccenic acid (82–86%). Given its kinetic and nutritional performance we recommend to consider Rhodobacter capsulatus as a high-potential sustainable source of microbial food.

Abstract: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, with 85% of all lung cancer reported as NSCLC. Moreover, there are no effective treatments in advanced NSCLC. This study shows for the first time that oral administration of plasma-treated water (PTW) can cure advanced NSCLC. The cold plasma in water generates a cocktail of reactive species, and oral administration of this cocktail to mice showed no toxicities even at the highest dose of PTW, after a single dose and repeated doses for 28 d in mice. In vivo studies reveal that PTW showed favorable anticancer effects on chemo-resistant lung cancer, similarly to gefitinib treatment as a reference drug in a chemo-resistant NSCLC model. The anticancer activities of PTW seem to be involved in inhibiting proliferation and angiogenesis and enhancing apoptosis in the cancer cells. Interestingly, the PTW contributes to enhanced immune response and improved cachexia in the model.