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: Direct photocatalytic reduction of CO2 has become an highly active field of research. It is thus of utmost importance to maintain an overview of the various materials used to sustain this process, find common trends, and, in this way, eventually improve the current conversions and selectivities. In particular, CO2 photoreduction using plasmonic photocatalysts under solar light has gained tremendous attention, and a wide variety of materials has been developed to reduce CO2 towards more practical gases or liquid fuels (CH4, CO, CH3OH/CH3CH2OH) in this manner. This Review therefore aims at providing insights in current developments of photocatalysts consisting of only plasmonic nanoparticles and semiconductor materials. By classifying recent studies based on product selectivity, this Review aims to unravel common trends that can provide effective information on ways to improve the photoreduction yield or possible means to shift the selectivity towards desired products, thus generating new ideas for the way forward.

Abstract: Computational fluid dynamics (CFD) applies numerical methods to solve transport phenomena problems. These include, for example, problems related to fluid flow comprising the Navier--Stokes transport equations for either compressible or incompressible fluids together with turbulence models and continuity equations for single and multi-component (reacting and inert) systems. The design space is first segmented into discrete volume elements (meshing). The finite volume method, the subject of this article, discretizes the equations in time and space to produce a set of non-linear algebraic expressions that are assigned to each volume element-cell. The system of equations is solved iteratively with algorithms like the semi-implicit method for pressure-linked equations (SIMPLE) and the pressure implicit splitting of operators (PISO). CFD is especially useful for testing multiple design elements because it is often faster and cheaper than experiments. The downside is that this numerical method is based on models that require validation to check their accuracy. According to a bibliometric analysis, the broad research domains in chemical engineering include: (1) dynamics and CFD-DEM (2) fluid flow, heat transfer and turbulence, (3) mass transfer and combustion, (4) ventilation and environment, and (5) design and optimization. Here, we review the basic theoretical concepts of CFD and illustrate how to set up a problem in the open-source software OpenFOAM to isomerize n-butane to i-butane in a notched reactor under turbulent conditions. We simulated the problem with 1000, 4000, and 16000 cells. According to the Richardson extrapolation, the simulation underestimates the adiabatic temperature rise by 7% with 16000 cells.

Abstract: Metal halide perovskite (MHP) quantum dots (QDs) offer immense potential for several areas of photonics research due to their easy and low-cost fabrication and excellent optoelectronic properties. However, practical applications of MHP QDs are limited by their poor stability and, in particular, their tendency to aggregate. Here, we develop a two-step double-solvent strategy to grow and confine CsPbBr3 QDs within the three-dimensional (3D) cavities of a mesoporous SBA-16 silica scaffold (CsPbBr3@SBA-16). Strong confinement and separation of the MHP QDs lead to a relatively uniform size distribution, narrow luminescence, and good ambient stability over 2 months. In addition, the CsPbBr3@SBA-16 presents a high activity and stability for visible-light-driven photocatalytic toluene C(sp(3))-H bond activation to produce benzaldehyde with similar to 730 mu mol g(-1) h(-1) yield rate and near-unity selectivity. Similarly, the structural stability of CsPbBr3@SBA-16 QDs is superior to that of both pure CsPbBr3 QDs and those confined in MCM-41 with 1D channels.

Abstract: Photoelectrochemical (PEC) sensing of phenolic compounds using singlet oxygen (1O2)-generating photocatalysts has emerged as a powerful detection tool. However, it is currently not known how experimental parameters, such as pH and applied potential, influence the generation of reactive oxygen species (ROS) and their photocurrents. In this article, the PEC response was studied over the 6 to 10 pH range using a rotating (ring) disk (R(R)DE) set-up in combination with quenchers, to identify the ROS formed upon illumination of a supported photosensitizer, F64PcZn. The photocurrents magnitude depended on the applied potential and the pH of the buffer solution. The anodic responses were caused by the oxidation of O2.−, generated due to the quenching of 1O2 with −OH and the reaction of 3O2 with [F64Pc(3-)Zn]. The cathodic responses were assigned to the reduction of 1O2 and O2.−, yielding H2O2. These insights may benefit 1O2 – based PEC sensing applications.

Abstract: Iridium oxide (IrOx) is one of the most efficient electrocatalysts for water oxidation reaction (WOR). Here, WOR electrocatalysis by 1.6 nm IrOx nanoparticles (NPs) electrophoretically deposited onto spectroscopic graphite (Gr) and basal plane highly ordered pyrolytic graphite (HOPG) was studied as a function of NPs' capping ligands and electrodeposition substrate. On Gr, OH-- and H2O-capped NPs exhibited close sub-monolayer surface coverages and specific electrocatalytic activity of 18.9-23.5 mA nmol(-1) of Ir-IV/V sites, at 1 V and pH 7. On HOPG, OH--capped NPs produced films with a diminished WOR activity of 5.17 +/- 2.40 mA nmol(-1). Electro-wettability-induced changes impeded electrophoretic deposition of H2O-capped NPs on HOPG, WOR currents being 25-fold lower than observed for OH--capped ones. The electrocatalysis efficiency correlated with hydrophilic properties of the substrate electrodes, affecting morphological and as a result catalytic properties of the formed IrOx films. These results, important both for studied and related carbon nanomaterials systems, allow fine-tuning of electrocatalysis by a proper choice of the substrate electrode.

Abstract: Complex transition-metal oxides exhibit a wide variety of chemical and physical properties which are a strong function the local electronic states of the transition-metal centres, as determined by a combination of metal oxidation state and local coordination environment. Topochemical reduction of the double perovskite oxide, LaSrCoRuO6, using Zr, yields LaSrCoRuO5. This reduced phase contains an ordered array of apex-linked square-based pyramidal Ru3+O5, square-planar Co1+O4 and octahedral Co3+O6 units, consistent with the coordination-geometry driven disproportionation of Co2+. Coordination-geometry driven disproportionation of d(7) transition-metal cations (e.g. Rh2+, Pd3+, Pt3+) is common in complex oxides containing 4d and 5d metals. However, the weak ligand field experienced by a 3d transition-metal such as cobalt leads to the expectation that d(7+) Co2+ should be stable to disproportionation in oxide environments, so the presence of Co1+O4 and Co3+O6 units in LaSrCoRuO5 is surprising. Low-temperature measurements indicate LaSrCoRuO5 adopts a ferromagnetically ordered state below 120 K due to couplings between S=(1)/(2) Ru3+ and S=1 Co1+.

Abstract: Optical-photothermal infrared (O-PTIR) spectroscopy is a recently developed technique that provides spectra comparable to traditional transmission FTIR spectroscopy with nanometric spatial resolution. Hence, O-PTIR is a promising candidate for the analysis of historical paintings, as well as other cultural heritage objects, but its potential has not yet been evaluated.

Abstract: In this work, the effects of Si-doping in Cu2ZnSnS4 are examined computationally and experimentally. The density functional theory calculations show that an increasing concentration of Si (from x = 0 to x = 1) yields a band gap rise due to shifting of the conduction band minimum towards higher energy states in the Cu2Zn(Sn1-xSix)S-4. CZTSiS thin film prepared by co-sputtering process shows Cu2Zn(Sn1-xSix)S-4 (Si-rich) and Cu2ZnSnS4 (S-rich) kesterite phases on the surface and in the bulk of the sample, respectively. A significant change in surface electronic properties is observed in CZTSiS thin film. Si-doping in CZTS inverts the band bending at grain-boundaries from downward to upward and the Fermi level of CZTSiS shifts upward. Further, the coating of the CdS and ZnO layer improves the photocurrent to approximate to 5.57 mA cm(-2) at -0.41 V-RHE in the CZTSiS/CdS/ZnO sample, which is 2.39 times higher than that of pure CZTS. The flat band potential increases from CZTS approximate to 0.43 V-RHE to CZTSiS/CdS/ZnO approximate to 1.31 V-RHE indicating the faster carrier separation process at the electrode-electrolyte interface in the latter sample. CdS/ZnO layers over CZTSiS significantly reduce the charge transfer resistance at the semiconductor-electrolyte interface.

Abstract: The wearable revolution is already present in society through numerous gadgets. However, the contest remains in fully deployable wearable (bio)chemical sensing. Its use is constrained by the energy consumption which is provided by miniaturized batteries, limiting the autonomy of the device. Hence, the combination of materials and engineering efforts to develop sustainable energy management is paramount in the next generation of wearable self-powered electrochemical devices (WeSPEDs). In this direction, this review highlights for the first time the incorporation of innovative energy harvesting technologies with top-notch wearable self-powered sensors and low-powered electrochemical sensors toward battery-free and self-sustainable devices for health and wellbeing management. First, current elements such as wearable designs, electrochemical sensors, energy harvesters and storage, and user interfaces that conform WeSPEDs are depicted. Importantly, the bottlenecks in the development of WeSPEDs from an analytical perspective, product side, and power needs are carefully addressed. Subsequently, energy harvesting opportunities to power wearable electrochemical sensors are discussed. Finally, key findings that will enable the next generation of wearable devices are proposed. Overall, this review aims to bring new strategies for an energy-balanced deployment of WeSPEDs for successful monitoring of (bio)chemical parameters of the body toward personalized, predictive, and importantly, preventive healthcare.

Abstract: Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1].   The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions.   We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration.   Database Details: – Covers all elements (Z: 1-108) and all edges – Large energy range: 0.01 – 4000 eV – Large momentum range: 0.05 -50 Å-1 – Fine log sampling: 128 points for energy and 256 points for momentum – Data format: GOSH [3]   Calculation Details: – Single atoms only; solid-state effects are not considered – Unoccupied states before continuum states of ionization are not considered; no fine structure – Plane Wave Born Approximation – Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when – core-shell electron is excited – Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances – Both large and small component contributions of Dirac solutions are included in GOS – Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference.   Version 1.1 release note: – Update to be consistent with GOSH data format [3], all the edges are now within a single hdf5 file. A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å. Great thanks to Gulio Guzzinati for his suggestions and sending conversion script.  Version 1.2 release note: – Add “File Type / File version” information [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689.

Abstract: We present a large dataset containing simulated core-loss electron energy loss spectroscopy (EELS) spectra with the elemental content as ground-truth labels. Additionally we present some neural networks trained on this data for element identification.  The simulated dataset contains zero padded core-loss spectra from 0 to 3072 eV, which represents 107 core-loss edges through all 80 elements from Be up to Bi. The core-loss edges are calculated from the generalised oscillator strength (GOS) database presented by Zhang et al.[1] Generic fine structures using lifetime broadened peaks are used to imitate fine structure due to solid-state effects in experimental spectra. Generic low-loss regions are used to imitate the effect of multiple scattering. Each spectrum contains at least one edge of a given query element and possibly additional edges depending on samples drawn from The Materials Project [2]. The dataset contains for each of the 80 elements: 7000 training spectra, 1500 test spectra, 600 validation spectra and 100 spectra representing only the query element. This results in a total 736 000 labeled spectra. Code on how to  – read the simulated data – transform HDF5 format to TFRecord format – train and evaluate neural networks using the simulated data – use the trained networks for automated element identification is available on GitHub at arnoannys/EELS_ID A full report on the simulation of the dataset and the training and evaluation of the neural networks can be found at:                    Annys, A., Jannis, D. & Verbeeck, J. Deep learning for automated materials characterisation in core-loss electron energy loss spectroscopy. Sci Rep 13, 13724 (2023). https://doi.org/10.1038/s41598-023-40943-7 [1] Zezhong Zhang, Ivan Lobato, Daen Jannis, Johan Verbeeck, Sandra Van Aert, & Peter Nellist. (2023). Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7729585 [2] Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier, Wei Chen, William Davidson Richards, Stephen Dacek, Shreyas Cholia, Dan Gunter, David Skinner, Gerbrand Ceder, Kristin A. Persson; Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. APL Mater 1 July 2013; 1 (1): 011002. [https://doi.org/10.1063/1.4812323](https://doi.org/10.1063/1.4812323)