Abstract: Although the heterogeneity of pyrolyzed Fe???N???C materials is known and has been reported previously, the atomic structure of the active sites and their detailed reaction mechanisms are still unknown. Here, we identified two pyridinic Fe???N4-like centers with different local C coordinates, i.e., FeN4C8 and FeN4C10, and studied their electrocatalytic activity for the nitrogen reduction reaction (NRR) based on density functional theory (DFT) calculations. We also discovered the influence of the adsorption of NH2 as a functional ligand on catalyst performance on the NRR. We confirmed that the NRR selectivity of the studied catalysts is essentially governed either by the local C coordination or by the dynamic structure associated with the FeII/FeIII. Our investigations indicate that the proposed traditional pyridinic FeN4C10 has higher catalytic activity and selectivity for the NRR than the robust FeN4C8 catalyst, while it may have outstanding activity for promoting other (electro)catalytic reactions. <comment>Superscript/Subscript Available</comment

Abstract: Multimodal contrast agents, which take advantage of different imaging modalities, have emerged as an interesting approach to overcome the technical limitations of individual techniques. We developed hybrid nanoparticles comprising an iron oxide core and an outer gold spiky layer, stabilized by a biocompatible polymeric shell. The combined magnetic and optical properties of the different components provide the required functionalities for magnetic resonance imaging (MRI), surface-enhanced Raman scattering (SERS), and fluorescence imaging. The fabrication of such hybrid nanoprobes comprised the adsorption of small gold nanoparticles onto premade iron oxide cores, followed by controlled growth of spiky gold shells. The gold layer thickness and branching degree (tip sharpness) can be controlled by modifying both the density of Au nanoparticle seeds on the iron oxide cores and the subsequent nanostar growth conditions. We additionally demonstrated the performance of these hybrid multifunctional nanoparticles as multimodal contrast agents for correlative imaging of in vitro cell models and ex vivo tissues.

Abstract: Co-digestion of organic waste and wastewater is receiving increased attention as a plausible waste management approach toward energy recovery. However, traditional anaerobic processes for co-digestion are particularly susceptible to severe organic loading rates (OLRs) under long-term treatment. To enhance technological feasi-bility, this work presented a two-stage Anaerobic Membrane Bioreactor (2 S-AnMBR) composed of a hydrolysis reactor (HR) followed by an anaerobic membrane bioreactor (AnMBR) for long-term co-digestion of food waste and kitchen wastewater. The OLRs were expanded from 4.5, 5.6, and 6.9 kg COD m- 3 d-1 to optimize biogas yield, nitrogen recovery, and membrane fouling at ambient temperatures of 25-32 degrees C. Results showed that specific methane production of UASB was 249 +/- 7 L CH4 kg-1 CODremoved at the OLR of 6.9 kg TCOD m- 3 d-1. Total Chemical Oxygen Demand (TCOD) loss by hydrolysis was 21.6% of the input TCOD load at the hydraulic retention time (HRT) of 2 days. However, low total volatile fatty acid concentrations were found in the AnMBR, indicating that a sufficiently high hydrolysis efficiency could be accomplished with a short HRT. Furthermore, using AnMBR structure consisting of an Upflow Anaerobic Sludge Blanket Reactor (UASB) followed by a side -stream ultrafiltration membrane alleviated cake membrane fouling. The wasted digestate from the AnMBR comprised 42-47% Total Kjeldahl Nitrogen (TKN) and 57-68% total phosphorous loading, making it suitable for use in soil amendments or fertilizers. Finally, the predominance of fine particles (D10 = 0.8 mu m) in the ultra -filtration membrane housing (UFMH) could lead to a faster increase in trans-membrane pressure during the filtration process.

Abstract: The development of biomass pretreatment approaches that, next to (hemi)cellulose valorization, aim at the conversion of lignin to chemicals is essential for the long-term success of a biorefinery. Herein, we discuss a dithionite-assisted organosolv fractionation (DAOF) of lignocellulose in n-butanol and water to produce cellulosic pulp and mono-/oligo-aromatics. The study frames the technicalities of this biorefinery process and relates them to the features of the obtained product streams. We comprehensively identify and quantify all products of interest: solid pulp (acid hydrolysis-HPLC, ATR-FTIR, XRD, SEM, enzymatic hydrolysis-HPLC), lignin derivatives (GPC, GC-MS/FID, 1H-13C HSQC NMR, ICP-AES), and carbohydrate derivatives (HPLC). These results were used for inspecting the economic feasibility of DAOF. In the best process configuration, a high yield of monophenolics was reached (~20%, based on acid insoluble lignin in birch sawdust). Various other lignocellulosic feedstocks were also explored, showing that DAOF is particularly effective on hardwood and herbaceous biomass. Overall, this study demonstrates that DAOF is a viable fractionation method for the sustainable upgrading of lignocellulosic biomass.

Abstract: Theoretical studies on molecule-metal surface reactions have so far been limited to small surface unit cells due to computational costs. Here, for the first time molecular dynamics simulations on very large surface unit cells at the level of density functional theory are performed, allowing a direct comparison to experiments performed on a curved crystal. Specifically, the reaction of D-2 on a curved Pt crystal is investigated with a neural network potential (NNP). The developed NNP is also accurate for surface unit cells considerably larger than those that have been included in the training data, allowing dynamical simulations on very large surface unit cells that otherwise would have been intractable. Important and complex aspects of the reaction mechanism are discovered such as diffusion and a shadow effect of the step. Furthermore, conclusions from simulations on smaller surface unit cells cannot always be transfered to larger surface unit cells, limiting the applicability of theoretical studies of smaller surface unit cells to heterogeneous catalysts with small defect densities.

Abstract: Lignosulfonate-based bioactive coatings as soil improvers for lawns were developed using laccase as a biocatalyst. Incorporation of glycerol, xylitol and sorbitol as plasticizers considerably reduced the brittleness of the synthesized coatings of marine carbonate granules while thermal enzyme inactivation at 100 degrees C enabled the production of stable coatings. Heat inactivation produced stable coatings with a molecular weight of 2000 kDa and a viscosity of 4.5 x 10(-3) Pas. The desired plasticity for the spray coating of soil improver granules was achieved by the addition of 2.7% of xylitol. Agriculture beneficial microorganisms (four different Bacillus species) were integrated into the coatings. The stable coatings protected the marine calcium carbonate granules, maintained the viability of the microorganisms and showed no toxic effects on the germination and growth of model plants including corn, wheat, salad, and tomato despite a slight delay in germination. Moreover, the coatings reduced the dust formation of soil improvers by 70%. CO2 emission analysis showed potential for the reduction of up to 3.4 kg CO2-eq. kg(-1) product, making it a viable alternative to fossil-based coatings.

Abstract: To gain full control over the growth of carbon nanotubes (CNTs) using plasma-enhanced chemical vapor deposition (PECVD), a thorough understanding of the underlying plasma-catalyst mechanisms is required. Oxygen-containing species are often used as or added to the growth precursor gas, but these species also yield various radicals and ions, which may simultaneously etch the CNT during the growth. At present, the effect of these reactive species on the growth onset has not yet been thoroughly investigated. We here report on the etching mechanism of incipient CNT structures from OH and O radicals as derived from combined (reactive) molecular dynamics (MD) and force-bias Monte Carlo (tfMC) simulations. Our results indicate that the oxygen-containing radicals initiate a dissociation process. In particular, we show how the oxygen species weaken the interaction between the CNT and the nanocluster. As a result of this weakened interaction, the CNT closes off and dissociates from the cluster in the form of a fullerene. Beyond the specific systems studied in this work, these results are generically important in the context of PECVD-based growth of CNTs using oxygen-containing precursors.

Abstract: Synchrotron radiation (SR)-based X-ray methods are powerful analytical tools for several purposes. They are widely used to probe the degradation mechanisms of inorganic artists' pigments in paintings, including chrome yellows (PbCr1-xSxO4; 0 <= x <= 0.8), a class of compounds often found in Van Gogh masterpieces. However, the high intensity and brightness of SR beams raise important issues regarding the potential damage inflicted on the analyzed samples. A thorough knowledge of the SR X-ray sensitivity of each class of pigment in the painting matrix is therefore required to find analytical strategies that seek to minimize the damage for preserving the integrity of the analyzed samples and to avoid data misinterpretation. Here, we employ a combination of Cr K-edge X-ray absorption near-edge structure spectroscopy, Cr-K-beta X-ray emission spectroscopy, and X-ray diffraction to monitor and quantify the effects of SR X-rays on the stability of chrome yellows and related Cr compounds and to define mitigation strategies. We found that the SR X-ray beam exposure induces changes in the oxidation state and local coordination environment of Cr ions and leads to a loss of the compound's crystalline structure. The extent of X-ray damage depends on some intrinsic properties of the samples (chemical composition of the pigment and the presence/absence and nature of the binder). It can be minimized by optimizing the overall fluence/dose released to the samples and by working in vacuum and under cryogenic conditions.

Abstract: A novel type of activated carbon fiber filter was developed for indoor air purification. The filter is equipped with electrodes for thermo-electrical regeneration at the point of saturation. The electrodes are arranged in such a way that the filter forms a pleated structure with an electrode in the tip of each pleat. This allows for a uniform temperature distribution on the filter surface during the regeneration process and the pleated structure reduces the overall pressure drop across the filter. The latter was validated by Computational Fluid Dynamics, using Darcy-Forchheimer parameters derived in previous work. The CFD model was further used to perform a virtual sensitivity study in search for the optimal ACF filter design by varying the pleat length, pleat height and filter thickness. Finally, adsorption and desorption properties were investigated with acetaldehyde and toluene as model compounds. Freundlich and Langmuir adsorption parameters, derived in previous work were successfully validated with a Multiphysics model.

Abstract: The quantum electrostatic heterostructure (QEH) model allows for efficient computation of the dielectric screening properties of layered van der Waals (vdW)-bonded heterostructures in terms of the dielectric functions of the individual two-dimensional (2D) layers. Here, we extend the QEH model by including (1) contributions to the dielectric function from infrared active phonons in the 2D layers, (2) screening from homogeneous bulk substrates, and (3) intraband screening from free carriers in doped 2D semiconductor layers. We demonstrate the potential of the extended QEH model by calculating the dispersion of coupled phonons in multilayer stacks of hexagonal boron-nitride (hBN), the strong hybridization of plasmons and optical phonons in graphene/hBN heterostructures, the effect of substrate screening on the exciton series of monolayer MoS2, and the properties of hyperbolic plasmons in a doped phosphorene sheet. The new QEH code is distributed as a Python package with a simple command line interface and a comprehensive library of dielectric building blocks for the most common 2D materials, providing an efficient open platform for dielectric modeling of realistic vdW heterostructures.

Abstract: Illicit drugs use and abuse remains an increasing challenge for worldwide authorities and, therefore, it is important to have accurate methods to detect them in seized samples, biological fluids and wastewaters. They are recently classified as the latest group of emerging pollutants as their consumption increased tremendously in recent years. Nanomaterials have gained much attention over the last decade in the development of sensors for a myriad of applications. The applicability of these nanomaterials, functionalized or not, significantly increases and it is therefore highly suitable for use in the detection of illicit drugs. We have assessed the suitability of various nanoplatforms, such as graphene (GPH), multi-walled carbon nanotubes (MWCNTs), gold nanoparticles (AuNPs) and platinum nanoparticles (PtNPs) for the electrochemical detection of illicit drugs. GPH and MWCNTs were chosen as the most suitable platforms and cocaine, 3,4-methylendioxymethamfetamine (MDMA), 3-methylmethcathinone (MMC) and alpha-pyrrolidinovalerophenone (PVP) were tested. Due to the hydrophobicity of the nanomaterials-based platforms which led to low signals, two strategies were followed namely, pretreatment of the electrodes in sulfuric acid by cyclic voltammetry and addition of Tween 20 to the detection buffer. Both strategies led to an increase in the oxidation signal of illicit drugs. Binary mixtures of illicit drugs with common adulterants found in street samples were also investigated. The proposed strategies allowed the sensitive detection of illicit drugs in the presence of most adulterants. The suitability of the proposed sensors for the detection of illicit drugs in spiked wastewaters was finally assessed.

Abstract: Illicit drug consumption is a worldwide worrying phenomenon that troubles modern society. For this reason, law enforcement agencies (LEAs) are placing tremendous efforts into tackling the spreading of such substances among our community. New sensing technologies can facilitate the LEAs duties by providing portable and affordable analytical devices. Herein, we present for the first time a sensitive and low-cost electrochemical method, i.e. square-wave adsorptive stripping voltammetry on carbon screen-printed electrodes (SPE), for the detection of five illicit drugs (i.e. cocaine, heroin, 3,4-methylenedioxymethamphetamine, 4-chloro-alpha-pyrrolidinovalerophenone, and ketamine) in oral fluid by the aid of a surfactant. Particularly, the surfactant is adsorbed at the carbon electrode’s surface and yields the adsorption of illicit drug molecules, allowing for an enhanced electrochemical signal in comparison to surfactant-free media. First, the surfactant-mediated behavior is deeply explored at the SPE by cyclic voltammetry, electrochemical impedance spectroscopy, and Fourier-transform infrared spectroscopy. Subsequently, the electrochemical behavior of the five illicit drugs is studied and optimized to render optimal analytical performance. Accordingly, the analytical system exhibited a wide linear concentration range from 1 to 30 µM with sub-micromolar limits of detection and high sensitivity. This performance is similar to other reported electrochemical sensors, but with the advantage of using an unmodified SPE, thus avoiding costly and complex functionalization of the SPE. Finally, the methodology was evaluated in diluted oral fluid samples spiked with illicit drugs. Overall, this work describes a simple, rapid, portable, and sensitive method for the detection of illicit drugs aiming to provide oral fluid testing opportunities to LEAs.

Abstract: The added value of supervised Machine Learning (ML) methods to determine the Absolute Configuration (AC) of compounds from their Vibrational Circular Dichroism (VCD) spectra was explored. Among all ML methods considered, Random Forest (RF) and Feedforward Neural Network (FNN) yield the best performance for identification of the AC. At its best, FNN allows near-perfect AC determination, with accuracy of prediction up to 0.995, while RF combines good predictive accuracy (up to 0.940) with the ability to identify the spectral areas important for the identification of the AC. No loss in performance of either model is observed as long as the spectral sampling interval used does not exceed the spectral bandwidth. Increasing the sampling interval proves to be the best method to lower the dimensionality of the input data, thereby decreasing the computational cost associated with the training of the models.

Abstract: High-performance thermoelectric materials are critical in recuperating the thermal losses in various machinery and promising in renewable energy applications. In this respect, the search for novel thermoelectric materials has attracted considerable attention. In particular, low dimensional materials have been proposed as potential candidates due to their unique and controllable thermal and electronic transport properties. The considerable potential of several two-dimensional materials as thermoelectric devices has already been uncovered and many new candidates that merit further research have been suggested. In this regard, we comprehensively investigate the thermoelectric coefficients and electronic fitness function (EFF) of a large family of structurally isotropic and anisotropic two-dimensional layered materials using density functional theory combined with semi-classical Boltzmann transport theory. With this high-throughput screening, we bring to light additional 2D crystals that haven't been previously classified as favorable TE materials. We predict that Pb2Se2, GeS2, As-2, NiS2, Hf2O6, Zr2O6, AsBrS, ISbTe, ISbSe, AsISe, and AsITe are promising isotropic thermoelectric materials due to their considerably high EFF values. In addition to these materials, Hf2Br4, Zr2Br4, Hf2Cl4, Zr2Cl4, Hf2O6, Zr(2)O(6)and Os(2)O(4)exhibit strong anisotropy and possess prominently high EFF values.

Abstract: An enclosed interface that joins a direct analysis in real time (DART) probe, solid-phase microextraction (SPME) fiber, and the inlet of a high-resolution mass spectrometer is described. Unlike other systems to couple SPME sampling to ambient mass spectrometry, the interface is able to perform discrete analyses on different areas of a single SPME fiber device for up to three technical replicate measurements of one sampling event. Inlet flow speed and desorption temperature are optimized, and reproducibility is demonstrated between replicate analyses on the same derivatized SPME fiber and with sequential fiber sampling events, yielding analyte measurement center of variance (CV) from 3 to 6%. Conditioning is also performed with the enclosed DART. The interface is a straightforward addition to commercially available technologies, and machine diagrams for custom components operated with SPME/DART/MS equipment are included.