Abstract: It is a generally accepted idea that the particle size distribution strongly affects the optical spectra of colloidal plasmonic nanoparticles. It is often quoted as one of the main reasons while explaining the mismatch between the theoretical and experimental optical spectra of such nanoparticles. In this work, these aspects are critically analyzed by means of a bottom up statistical approach that considers variables such as mean, standard deviation and skewness of the nanoparticle size distribution independently from one another. By assuming normal and log-normal distributions of the particle size, the effect of the statistical parameters on the Mie analytical optical spectra of colloidal nanoparticles was studied. The effect of morphology was also studied numerically in order to understand to what extent it can play a role. It is our finding that the particle polydispersity, skewness and surface morphology in fact only weakly impact the optical spectra. While, the selection of suitable optical constants with regard to the crystallinity of the nanoparticles is a far more influential factor for correctly predicting both the plasmon band position and the plasmon bandwidth in theoretical simulations of the optical spectra. It is shown that the mean particle size can be correctly estimated directly from the plasmon band position, as it is the mean that determines the resonance wavelength. The standard deviation can on the other hand be estimated from the intensity distribution data obtained from dynamic light scattering experiments. The results reported herein clear the ambiguity around particle size distribution and optical response of colloidal plasmonic nanoparticles.

Abstract: It is well established that lipid aldehydes (LAs) are able to increase the permeability of cell membranes and induce their rupture. However, it is not yet clear how LAs are distributed in phase-separated membranes (PSMs), which are responsible for the transport of selected molecules and intracellular signaling. Thus, we investigate here the distribution of LAs in a PSM by coarse-grained molecular dynamics simulations. Our results reveal that LAs derived from mono-unsaturated lipids tend to accumulate at the interface between the liquid-ordered/liquiddisordered domains, whereas those derived from poly-unsaturated lipids remain in the liquid-disordered domain. These results are important for understanding the effects caused by oxidized lipids in membrane structure, properties and organization.

Abstract: Binding of the SARS-CoV-2 S-glycoprotein to cell receptors is vital for the entry of the virus into cells and subsequent infection. ACE2 is the main cell receptor for SARS-CoV-2, which can attach to the C-terminal receptor-binding domain (RBD) of the SARS-CoV-2 S-glycoprotein. The GRP78 receptor plays an anchoring role, which attaches to the RBD and increases the chance of other RBDs binding to ACE2. Although high levels of reactive oxygen and nitrogen species (RONS) are produced during viral infections, it is not clear how they affect the RBD structure and its binding to ACE2 and GRP78. In this research, we apply molecular dynamics simulations to study the effect of oxidation of the highly reactive cysteine (Cys) amino acids of the RBD on its binding to ACE2 and GRP78. The interaction energy of both ACE2 and GRP78 with the whole RBD, as well as with the RBD main regions, is compared in both the native and oxidized RBDs. Our results show that the interaction energy between the oxidized RBD and ACE2 is strengthened by 155 kJ/mol, increasing the binding of the RBD to ACE2 after oxidation. In addition, the interaction energy between the RBD and GRP78 is slightly increased by 8 kJ/mol after oxidation, but this difference is not significant. Overall, these findings highlight the role of RONS in the binding of the SARS-CoV-2 S-glycoprotein to host cell receptors and suggest an alternative mechanism by which RONS could modulate the entrance of viral particles into the cells.

Abstract: In the present work, the resolution and quantification of mixtures of different opiate compounds in the presence of common cutting agents using an electronic tongue (ET) is evaluated. More specifically, ternary mixtures of heroin, morphine and codeine were resolved in the presence of caffeine and paracetamol. To this aim, an array of three carbon screen-printed electrodes were modified with different ink-like solutions of graphite, cobalt (II) phthalocyanine and palladium, and their responses towards the different drugs were characterized by means of square wave voltammetry (SWV). Developed sensors showed a good performance with good linearity at the mu M level, LODs between 1.8 and 5.3 mu M for the 3 actual drugs, and relative standard deviation (RSD) ca. 2% for over 50 consecutive measurements. Next, a quantitative model that allowed the identification and quantification of the individual substances from the overlapped voltammograms was built using partial least squares regression (PLS) as the modeling tool. With this approach, quantification of the different drugs was achieved at the mu M level, with a total normalized root mean square error (NRMSE) of 0.084 for the test subset.

Abstract: N-Based fertilisers are paramount to support our still-growing world population. Current industrial N₂fixation is heavily fossil fuel-dependent, therefore, a lot of work is put into the development of fossil-free pathways. Plasma technology offers a fossil-free and flexible method for N₂fixation that is compatible with renewable energy sources. We present here a pulsed plasma jet for direct NO_{<italic>x</italic>}production from air. The pulsed power allows for a record-low energy consumption (EC) of 0.42 MJ (mol N)⁻¹. This is the lowest reported EC in plasma-based N₂fixation at atmospheric pressure thus far. We compare our experimental data with plasma chemistry modelling, and obtain very good agreement. Hence, we can use our model to explain the underlying mechanisms responsible for this low EC. The pulsed power and the corresponding pulsed gas temperature are the reason for the very low EC: they provide a strong vibrational–translational non-equilibrium and promote the non-thermal Zeldovich mechanism. This insight is important for the development of the next generation of plasma sources for energy-efficient NO_{<italic>x</italic>}production.

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: 3D characterization of assemblies of nanoparticles is of great importance to determine their structure-property connection. Such investigations become increasingly more challenging when the assemblies become larger and more compact. In this paper, we propose an optimized approach for electron tomography to minimize artefacts related to beam broadening in High Angle Annular Dark-Field Scanning Transmission Electron Microscopy mode. These artefacts are typically present at one side of the reconstructed 3D data set for thick nanoparticle assemblies. To overcome this problem, we propose a procedure in which two tomographic tilt series of the same sample are acquired. After acquiring the first series, the sample is flipped over 180o, and a second tilt series is acquired. By merging the two reconstructions, blurring in the reconstructed volume is minimized. Next, this approach is combined with an advanced three-dimensional reconstruction algorithm yielding quantitative structural information. Here, the approach is applied to a thick and compact assembly of spherical Au nanoparticles, but the methodology can we used to investigate a broad range of samples.

Abstract: Forensic drug laboratories are confronted with increasing amounts of drugs and a demand for faster results that are directly available on-site. In addition, the drug market is getting more complex with hundreds of new psychoactive substances (NPS) entering the market in recent years. Rapid and on-scene presumptive drug testing therefore faces a shift from manual colorimetric tests towards approaches that can detect a wider range of components and process results automatically. Electrochemical detection offers these desired characteristics, making it a suitable candidate for on-site drug detection. In this study, a two-step electrochemical sensor is introduced for the detection of MDMA and 2C-B. Firstly, a direct electrochemical analysis was performed to detect MDMA. Validation experiments on over 70 substances revealed that 2C-B was the only frequently encountered drug that gave a false positive result for MDMA in this first analysis. A second step using in-situ derivatization was subsequently introduced. To this end, formaldehyde was used for N-methylation of 2C-B thereby enhancing its electrochemical profile. The enriched electrochemical fingerprint in the second step allowed for clear differentiation between MDMA and 2C-B. The applicability of this approach was demonstrated with 71 ecstasy tablets seized by the Amsterdam Police. The MDMA/2C-B sensor correctly identified all 39 MDMA-containing tablets and 10 out of 11 tablets containing 2C-B. Most notably, correct results were also obtained for dark colored tablets in which both spectroscopic analysis and colorimetric tests failed due to obscured signals.

Abstract: The electrochemical behavior of some of the most relevant endocrine-disrupting phenols using unmodified carbon screen-printed electrodes (SPEs) is described for the first time. Experiments were made to assess the electrochemical behavior of phenol (PHOH), pentachlorophenol (PCP), 4-tert octylphenol (OP) and bisphenol A (BPA) and their determination in the most favorable conditions, using voltammetric methods such as cyclic voltammetry (CV), linear sweep voltammetry (LSV) and square wave voltammetry (SWV) in Britton Robinson (BR) buffer. Further, the usefulness of the electrochemical approach was validated with real samples from a local river and was compared to commercial phenols test kit, which is commonly used for on-site screening in industrial streams and wastewaters. Finally, the approach was compared with a lab-bench standard method using real samples, i.e., high-performance liquid chromatography with a photodiode array detector (HPLC-DAD).

Abstract: We introduce a simple enhanced sampling approach for the calculation of free energy differences and barriers along a one-dimensional reaction coordinate. First, a small number of short nonequilibrium simulations are carried out along the reaction coordinate, and the Jarzynski equality is used to learn an approximate free energy surface from the nonequilibrium work distribution. This free energy estimate is represented in a compact form as an artificial neural network and used as an external bias potential to accelerate rare events in a subsequent molecular dynamics simulation. The final free energy estimate is then obtained by reweighting the equilibrium probability distribution of the reaction coordinate sampled under the influence of the external bias. We apply our reweighted Jarzynski sampling recipe to four processes of varying scales and complexities.spanning chemical reaction in the gas phase, pair association in solution, and droplet nucleation in supersaturated vapor. In all cases, we find reweighted Jarzynski sampling to be a very efficient strategy, resulting in rapid convergence of the free energy to high precision.

Abstract: The synthesis of gold nanorods requires the presence of symmetry-breaking and shape-directing additives, among which bromide ions and quaternary ammonium surfactants have been reported as essential. As a result, hexadecyltrimethylammonium bromide (CTAB) has been selected as the most efficient surfactant to direct anisotropic growth. One of the difficulties arising from this selection is the low solubility of CTAB in water at room temperature, and therefore the seeded growth of gold nanorods is usually performed at 25 degrees C or above, which has restricted so far the analysis of kinetic effects derived from lower temperatures. We report a systematic study of the synthesis of gold nanorods from pentatwinned seeds using hexadecyltrimethylammonium chloride (CTAC) as the principal surfactant and a low concentration of bromide as shape-directing agent. Under these conditions, the synthesis can be performed at temperatures as low as 8 degrees C, and the corresponding kinetic effects can be studied, resulting in temperature-controlled aspect ratio tunability.

Abstract: This work reports the use of modified screen-printed carbon electrodes (SPCEs) for the identification of three drugs of abuse and two habitual cutting agents, caffeine and paracetamol, combining voltammetric sensing and chemometrics. In order to achieve this goal, codeine, heroin and morphine were subjected to Square Wave Voltammetry (SWV) at pH 7, in order to elucidate their electrochemical fingerprints. The optimized SPCEs electrode array, which have a differentiated response for the three oxidizable compounds, was derived from Carbon, Prussian blue, Cobalt (II) phthalocyanine, Copper (II) oxide, Polypyrrole and Palladium nanoparticles ink-modified carbon electrodes. Finally, Principal Component Analysis (PCA) coupled with Silhouette parameter assessment was used to select the most suitable combination of sensors for identification of drugs of abuse in presence of cutting agents.

Abstract: Plasma catalysis is an emerging new technology for the electrification and downscaling of NH3 synthesis. Increasing attention is being paid to the optimization of plasma catalysis with respect to the plasma conditions, the catalyst material, and their mutual interaction. In this work we use microkinetic models to study how the total conversion process is impacted by the combination of different plasma conditions and transition metal catalysts. We study how plasma-generated radicals and vibrationally excited N2 (present in a dielectric barrier discharge plasma) interact with the catalyst and impact the NH3 turnover frequencies (TOFs). Both filamentary and uniform plasmas are studied, based on plasma chemistry models that provided plasma phase speciation and vibrational distribution functions. The Langmuir−Hinshelwood reaction rate coefficients (i.e., adsorption reactions and subsequent reactions among adsorbates) are determined using conventional scaling relations. An additional set of Eley−Rideal reactions (i.e., direct reactions of plasma radicals with adsorbates) was added and a sensitivity analysis on the assumed reaction rate coefficients was performed. We first show the impact of different vibrational distribution functions on the catalytic dissociation of N2 and subsequent production of NH3, and we gradually include more radical reactions, to illustrate the contribution of these species and their corresponding reaction pathways. Analysis over a large range of catalysts indicates that different transition metals (metals such as Rh, Ni, Pt, and Pd) optimize the NH3TOFs depending on the population of the vibrational levels of N2. At higher concentrations of plasma-generated radicals, the NH3 TOFs become less dependent on the catalyst material, due to radical adsorptions on the more noble catalysts and Eley−Rideal reactions on the less noble catalysts.

Abstract: The evaluation of nucleation rates from molecular dynamics trajectories is hampered by the slow nucleation time scale and impact of finite size effects. Here, we show that accurate nucleation rates can be obtained in a very general fashion relying only on the free energy barrier, transition state theory, and a simple dynamical correction for diffusive recrossing. In this setup, the time scale problem is overcome by using enhanced sampling methods, in casu metadynamics, whereas the impact of finite size effects can be naturally circumvented by reconstructing the free energy surface from an appropriate ensemble. Approximations from classical nucleation theory are avoided. We demonstrate the accuracy of the approach by calculating macroscopic rates of droplet nucleation from argon vapor, spanning 16 orders of magnitude and in excellent agreement with literature results, all from simulations of very small (512 atom) systems.

Abstract: Vortex reactors take advantage of the synergy between enhanced heat and mass transfer rates and multifunctional phenomena at different temporal and spatial scales. Proof-of-concept experiments with our novel and innovative STAtor-Rotor VOrtex Chamber (STARVOC) confirm its advantageous features for the sustainable production of chemicals and fuels. STARVOC is a high-g contactor that uses carrier flow (gas or liquid) tangential injection to drive a rotor attached to low-friction bearings. The vortex chamber inside the rotor contains a secondary phase or phases, such as a solids bed, a liquid layer, or a suspension. Carrier fluid passes through the perforated rotor wall and contacts a densely and uniformly distributed secondary phase with enhanced slip velocities. Experiments focused on pressure profiles, rotor angular velocity, and solids azimuthal velocity. With air as the carrier fluid and different solid particle beds as the secondary phase, STARVOC reached bed azimuthal velocities up to four-fold compared to those reached in Gas-Solid Vortex Units with fully static geometry. These results show its potential to improve interfacial heat and mass transfer rates and take advantage of flow energy and angular momentum. Due to its process intensification capabilities, STARVOC is a promising alternative for the state-of-the-art chemical industry.