Abstract: Spectroscopic techniques combined with chemometrics are a promising tool for analysis of seized drug powders. In this study, the performance of three spectroscopic techniques [Mid-InfraRed (MIR), Raman and Near-InfraRed (NIR)] was compared. In total, 364 seized powders were analyzed and consisted of 276 cocaine powders (with concentrations ranging from 4 to 99 w%) and 88 powders without cocaine. A classification model (using Support Vector Machines [SVM] discriminant analysis) and a quantification model (using SVM regression) were constructed with each spectral dataset in order to discriminate cocaine powders from other powders and quantify cocaine in powders classified as cocaine positive. The performances of the models were compared with gas chromatography coupled with mass spectrometry (GC-MS) and gas chromatography with flame-ionization detection (GC-FID). Different evaluation criteria were used: number of false negatives (FNs), number of false positives (FPs), accuracy, root mean square error of cross-validation (RMSECV) and determination coefficients (R-2). Ten colored powders were excluded from the classification data set due to fluorescence background observed in Raman spectra. For the classification, the best accuracy (99.7%) was obtained with MIR spectra. With Raman and NIR spectra, the accuracy was 99.5% and 98.9%, respectively. For the quantification, the best results were obtained with NIR spectra. The cocaine content was determined with a RMSECV of 3.79% and a R-2 of 0.97. The performance of MIR and Raman to predict cocaine concentrations was lower than NIR, with RMSECV of 6.76% and 6.79%, respectively and both with a R-2 of 0.90. The three spectroscopic techniques can be applied for both classification and quantification of cocaine, but some differences in performance were detected. The best classification was obtained with MIR spectra. For quantification, however, the RMSECV of MIR and Raman was twice as high in comparison with NIR. Spectroscopic techniques combined with chemometrics can reduce the workload for confirmation analysis (e.g., chromatography based) and therefore save time and resources.

Abstract: A gel consists of a network of particles or molecules formed for example using the sol-gel process, by which a solution transforms into a porous solid. Particles or molecules in a gel are mainly organized on a scaffold that makes up a porous system. Quantized vortices in type-II superconductors mostly form spatially homogeneous ordered or amorphous solids. Here we present high-resolution imaging of the vortex lattice displaying dense vortex clusters separated by sparse or entirely vortex-free regions in beta-Bi2Pd superconductor. We find that the intervortex distance diverges upon decreasing the magnetic field and that vortex lattice images follow a multifractal behavior. These properties, characteristic of gels, establish the presence of a novel vortex distribution, distinctly different from the well-studied disordered and glassy phases observed in high-temperature and conventional superconductors. The observed behavior is caused by a scaffold of one-dimensional structural defects with enhanced stress close to the defects. The vortex gel might often occur in type-II superconductors at low magnetic fields. Such vortex distributions should allow to considerably simplify control over vortex positions and manipulation of quantum vortex states.

Abstract: We have developed an innovative methodology to overcome the lack of techniques for real-time assessment of degradable biomedical polymers at physiological conditions. The methodology was established by combining polymer characterization techniques with electrochemical sensors. The in vitro hydrolytic degradation of a series of aliphatic polyesters was evaluated by following the molar mass decrease and the mass loss at different incubation times while tracing pH and l-lactate released into the incubation media with customized miniaturized electrochemical sensors. The combination of different analytical approaches provided new insights into the mechanistic and kinetics aspects of the degradation of these biomedical materials. Although molar mass had to reach threshold values for soluble oligomers to be formed and specimens’ resorption to occur, the pH variation and l-lactate concentration were direct evidence of the resorption of the polymers and indicative of the extent of chain scission. Linear models were found for pH and released l-lactate as a function of mass loss for the l-lactide-based copolymers. The methodology should enable the sequential screening of degradable polymers at physiological conditions and has potential to be used for preclinical material’s evaluation aiming at reducing animal tests.

Abstract: The emergence of new psychoactive drugs in the market demands rapid and accurate tools for the on‐site classification of illegal and legal compounds with similar structures. Herein, a novel method for the classification of synthetic cathinones (SC) is presented based on their electrochemical profile. First, the electrochemical profile of five common SC (i.e., mephedrone, ethcathinone, methylone, butylone and 4‐chloro‐alpha‐pyrrolidinovalerophenone) is collected to build calibration curves using square wave voltammetry on graphite screen‐printed electrodes (SPE). Second, the elucidation of the oxidation pathways, obtained by liquid chromatography‐high resolution mass spectrometry, allows the pairing of the oxidation products to the SC electrochemical profile, providing a selective and robust classification. Additionally, the effect of common adulterants and illicit drugs on the electrochemical profile of the SC is explored. Interestingly, a cathodic pretreatment of the SPE allows the selective detection of each SC in presence of electroactive adulterants. Finally, the electrochemical approach is validated with gas‐chromatography‐mass spectrometry by analyzing 26 confiscated samples from seizures and illegal webshops. Overall, the electrochemical method exhibits a successful classification of SC including structural derivatives, a crucial attribute in an ever‐diversifying drug market.

Abstract: A better understanding of the drivers of the economic, environmental, and social sustainability of emerging (biobased) technologies and products in early development phases can help decision-makers to identify sustainability hurdles and opportunities. Furthermore, it guides additional research and development efforts and investment decisions, that will, ultimately, lead to more sustainable products and technologies entering a market. To this end, this study developed a novel techno-sustainability assessment (TSA) framework with a demonstration on a biobased chemical application. The integrated TSA compares the potential sustainability performance of different (technology) scenarios and helps to make better-informed decisions by evaluating and trading-off sustainability impacts in one holistic framework. The TSA combines methods for comprehensive indicator selection and integration of technological and country-specific data with environmental, economic, and social data. Multi-criteria decision analysis (MCDA) is used to address data uncertainty and to enable scenario comparison if indicators are expressed in different units. A hierarchical, stochastic outranking approach is followed that compares different weighting schemes and preference structures to check for the robustness of the results. The integrated TSA framework is demonstrated on an application for which the sustainability of a production and harvesting plant of microalgae-based food colorants is assessed. For a set of scenarios that vary with regard to the algae feedstock, production technology, and location, the sustainability performance is quantified and compared, and the underlying reasons for this performance are explored.

Abstract: This work contributes to a new generalized empirical correlation for predicting methane (CH4) hydrate equilibrium conditions in pure water. Unlike the conventional thermodynamic approach that involves complex reckoning, the proposed empirical equation is developed by regressing 215 experimental data points from the literature and validating with 45 data points for predicting methane hydrate equilibrium conditions in pure water. The new correlation is proposed for a temperature and pressure range of 273.2–303.48 K and 2.63–72.26 MPa, respectively. The accuracy and performance of the proposed correlation is quantitatively evaluated using statistical error analysis. The proposed correlation was able to estimate CH4 hydrate equilibrium conditions satisfactorily with an R2 of 0.99987. The overall error analysis for the proposed correlation shows fair agreement with the experimental data reported within the literature. Concurrently, the new correlation showed better performance in predicting equilibrium conditions compared to those calculated by other empirical correlations available in the literature within the investigated range. In addition, the proposed empirical equation is also checked to evaluate its efficacy in fitting each set of experimental binary/ternary methane hydrates (BTMH) and binary hydrogen hydrates (BHH) for an accurate representation of equilibrium data over a wide range of composition, pressure, and temperature conditions. A maximum percentage deviation of 0.58% and 0.24% was observed between experimental and calculated equilibrium conditions for BTMH and BHH, respectively.

Abstract: The crystallization of nanomaterials is a primary source of solid-state, photonic structures. Thus, a detailed understanding of this process is of paramount importance for the successful application of photonic nanomaterials in emerging optoelectronic technologies. While colloidal crystallization has been thoroughly studied, for example, with advanced in situ electron microscopy methods, the noncolloidal crystallization (freezing) of nanoparticles (NPs) remains so far unexplored. To fill this gap, in this work, we present proof-of principle experiments decoding a crystallization of reconfigurable assemblies of NPs at a solid state. The chosen material corresponds to an excellent testing bed, as it enables both in situ and ex situ investigation using X-ray diffraction (XRD), transmission electron microscopy (TEM), high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), atomic force microscopy (AFM), and optical spectroscopy in visible and ultraviolet range (UV−vis) techniques. In particular, ensemble measurements with small-angle XRD highlighted the dependence of the correlation length in the NPs assemblies on the number of heating/cooling cycles and the rate of cooling. Ex situ TEM imaging further supported these results by revealing a dependence of domain size and structure on the sample preparation route and by showing we can control the domain size over 2 orders of magnitude. The application of HAADF-STEM tomography, combined with in situ thermal control, provided three-dimensional single-particle level information on the positional order evolution within assemblies. This combination of real and reciprocal space provides insightful information on the anisotropic, reversibly reconfigurable assemblies of NPs. TEM measurements also highlighted the importance of interfaces in the polydomain structure of nanoparticle solids, allowing us to understand experimentally observed differences in UV−vis extinction spectra of the differently prepared crystallites. Overall, the obtained results show that the combination of in situ heating HAADF-STEM tomography with XRD and ex situ TEM techniques is a powerful approach to study nanoparticle freezing processes and to reveal the crucial impact of disorder in the solid-state aggregates of NPs on their plasmonic properties.

Abstract: In situ TEM is a valuable technique to offer novel insights in the behavior of nanomaterials under various conditions. However, interpretation of in situ experiments is not straightforward since the electron beam can impact the outcome of such measurements. For example, ligands surrounding metal nanoparticles transform into a protective carbon layer upon electron beam irradiation and may impact the apparent thermal stability during in situ heating experiments. In this work, we explore the effect of different treatments typically proposed to remove such ligands. We found that plasma treatment prior to heating experiments for Au nanorods and nanostars increased the apparent thermal stability of the nanoparticles, while an activated carbon treatment resulted in a decrease of the observed thermal stability. Treatment with HCl barely changed the experimental outcome. These results demonstrate the importance of carefully selecting pre-treatments procedures during in situ heating experiments.

Abstract: Industrial production of HCN from NH3 and CH4 not only uses precious Pt or Pt−Rh catalysts but also requires extremely high temperatures (∼1600 K). From an energetic, operational, and safety perspective, a drastic decrease in temperature is highly desirable. Here, we report ammonia reforming of methane for the production of HCN and H2 at 673 K by the combination of CH4/NH3 plasma and a supported Cu/silicalite-1 catalyst. 30% CH4 conversion has been achieved with 79% HCN selectivity. Catalyst characterization and plasma diagnostics reveal that the excellent reaction performance is attributed to metallic Cu active sites. In addition, we propose a possible reaction pathway, viz. E-R reactions with N, NH, NH2, and CH radicals produced in the plasma, for the production of HCN, based on density functional theory calculations. Importantly, the Cu/silicalite-1 catalyst costs less than 5% of the commercial Pt mesh catalyst.

Abstract: γ- and δ-alumina are popular catalyst support materials. Using a hydrothermal synthesis method starting from aluminum nitrate and urea in diluted solution, spherical core–shell particles with a uniform particle size of about 1 μm were synthesized. Upon calcination at 1000 °C, the particles adopted a core–shell structure with a γ-alumina core and δ-alumina shell as evidenced by 2D and 3D electron microscopy and²⁷Al magic angle spinning nuclear magnetic resonance spectroscopy. The spherical alumina particles were loaded with Pt nanoparticles with an average size below 1 nm using the strong electrostatic adsorption method. Electron microscopy and energy dispersive X-ray spectroscopy revealed a homogeneous platinum dispersion over the alumina surface. These platinum loaded alumina spheres were used as a model catalyst for bifunctional catalysis. Physical mixtures of Pt/alumina spheres and spherical zeolite particles are equivalent to catalysts with platinum deposited on the zeolite itself facilitating the investigation of the catalyst components individually. The spherical alumina particles are very convenient supports for obtaining a homogeneous distribution of highly dispersed platinum nanoparticles. Obtaining such a small Pt particle size is challenging on other support materials such as zeolites. The here reported and well-characterized Pt/alumina spheres can be combined with any zeolite and used as a bifunctional model catalyst. This is an interesting strategy for the examination of the acid catalytic function without the interference of the supported platinum metal on the investigated acid material.

Abstract: Drought is a persistent, sluggish natural disaster in developing countries that has generated a financial burden and an unstable climate. Farmers should adopt early warning systems (EWS) in their strategies for monitoring drought to reduce its serious consequences. However, farmers in developing countries are reluctant to use EWS as their management strategies. Hence, the aim of this study was to investigate the decision of farmers to use climate knowledge through the model of farming activity in Kermanshah Township, Iran. A surveyor questionnaire was used to gather data from 370 wheat farmers using random sampling methods inmulti-stage clusters. Results revealed that the decision to use climate information is affected by personal factors, attitude towards climate information, objectives of using climate information, and external/physical farming factors. The result of this study has implications for drought management practitioners. To be specific, the results can aid policymakers to design early alert programs to minimize the risk of drought and thus move from conventional to climate smart agriculture. (C) 2020 Elsevier B.V. All rights reserved.

Abstract: A database-driven approach combined with ab initio density functional theory (DFT) simulations is used to identify and simulate alternative ferroelectric materials beyond Hf(Zr)O-2. The database-driven screening method identifies a class of wurtzite ferroelectric materials. DFT simulations of wurtzite magnesium chalcogenides, including MgS, MgSe, and MgTe, show their potential to achieve improved ferroelectric (FE) stability, simple atomistic unit cell structure, and large FE polarization. Strain engineering can effectively modulate the FE switching barrier height for facilitating FE switching. The effect of the piezoelectric property on the FE switching barrier heights is also examined.

Abstract: The use of a photocatalyst (photosensitizer) which produces singlet oxygen instead of enzymes for oxidizing analytes creates opportunities for designing cost-efficient and sensitive photoelectrochemical sensors. We report that perfluoroisopropyl-substituted zinc phthalocyanine (F64PcZn) interacts specifically with a complex phenolic compound, the antibiotic rifampicin (RIF), but not with hydroquinone or another complex phenolic compound, the antibiotic doxycycline. The specificity is imparted by the selective preconcentration of RIF in the photocatalytic layer, as revealed by electrochemical and optical measurements, complemented by molecular modeling that confirms the important role of a hydrophobic cavity formed by the iso-perfluoropropyl groups of the photocatalyst. The preconcentration effect favorably enhances the RIF photoelectrochemical detection limit as well as sensitivity to nanomolar (ppb) concentrations, LOD = 7 nM (6 ppb) and 2.8 A.M-1.cm(-2), respectively. The selectivity to RIF, retained in the photosensitizer layer, is further enhanced by the selective removal of all unretained phenols via simple washing of the electrodes with pure buffer. The utility of the sensor for analyzing municipal wastewater was demonstrated. This first demonstration of enhanced selectivity and sensitivity due to intrinsic interactions of a molecular photocatalyst (photosensitizer) with an analyte, without use of a biorecognition element, may allow the design of related, robust, simple, and viable sensors.

Abstract: Three-dimensional topological insulators are exotic materials with unique properties. Tetradymite type binary chalcogenides of bismuth and antimony, as well as their mixed crystals, belong to prototypical TIs. Potential device applications of these materials require in-depth knowledge of their stability in the ambient atmosphere and other media maintained during their processing. Here we investigated the reactivity of mixed crystals with anion substitution, Bi-2(Se1-xTex)(3) and Sb2(Se1-xTex)(3), towards molecular oxygen using both in situ and ex situ X-ray photoelectron spectroscopy. The results indicate that, in contrast to cation substitution, partial substitution of tellurium by selenium atoms leads to anomalously high surface reactivity, which even exceeds that of the most reactive binary constituent. We attribute this effect to anion ordering that essentially modifies the bond geometry, especially the respective bond angles as modeled by DFT.