Abstract: Plasmonic catalysis in the colloidal phase requires robust surface ligands that prevent particles from aggregation in adverse chemical environments and allow carrier flow from reagents to nanoparticles. This work describes the use of a water-soluble conjugated polymer comprising a thiophene moiety as a surface ligand for gold nanoparticles to create a hybrid system that, under the action of visible light, drives the conversion of the biorelevant NAD+ to its highly energetic reduced form NADH. A combination of advanced microscopy techniques and numerical simulations revealed that the robust metal-polymer heterojunction, rich in sulfonate functional groups, directs the interaction of electron-donor molecules with the plasmonic photocatalyst. The tight binding of polymer to the gold surface precludes the need for conventional transition-metal surface cocatalysts, which were previously shown to be essential for photocatalytic NAD(+) reduction but are known to hinder the optical properties of plasmonic nanocrystals. Moreover, computational studies indicated that the coating polymer fosters a closer interaction between the sacrificial electron-donor triethanolamine and the nanoparticles, thus enhancing the reactivity.

Abstract: CO2 conversion by plasma technology is gaining increasing interest. We present a carbon (charcoal) bed placed after a Gliding Arc Plasmatron (GAP) reactor, to enhance the CO2 conversion, promote O/O2 removal and in­ crease the CO fraction in the exhaust mixture. By means of an innovative (silo) system, the carbon is constantly supplied, to avoid carbon depletion upon reaction with O/O2. Using this carbon bed, the CO2 conversion is enhanced by almost a factor of two (from 7.6 to 12.6%), while the CO concentration even increases by a factor of three (from 7.2 to 21.9%), and O2 is completely removed from the exhaust mixture. Moreover, the energy ef­ ficiency of the conversion process drastically increases from 27.9 to 45.4%, and the energy cost significantly drops from 41.9 to 25.4 kJ.L− 1. We also present the temperature as a function of distance from the reactor outlet, as well as the CO2, CO and O2 concentrations and the temperature in the carbon bed as a function of time, which is important for understanding the underlying mechanisms. Indeed, these time-resolved measurements reveal that the initial enhancements in CO2 conversion and in CO concentration are not maintained in our current setup. Therefore, we present a model to study the gasification of carbon with different feed gases (i.e., O2, CO and CO2 separately), from which we can conclude that the oxygen coverage at the surface plays a key role in determining the product composition and the rate of carbon consumption. Indeed, our model insights indicate that the drop in CO2 conversion and in CO concentration after a few minutes is attributed to deactivation of the carbon bed, due to rapid formation of oxygen complexes at the surface.

Abstract: A multiscale modeling and simulation approach, including first-principles calculations, ab initio molecular dynamics simulations, and a tight binding approach, is employed to study band flattening of the electronic band structure of oxidized monolayer graphene. The width offlat bands can be tuned by strain, the external electric field, and the density of functional groups and their distribution. A transition to a conducting state is found for monolayer graphene with impurities when it is subjected to an electric field of similar to 1.0 V/angstrom. Several parallel impurity-induced flat bands appear in the low-energy spectrum of monolayer graphene when the number of epoxy groups is changed. The width of the flat band decreases with an increase in tensile strain but is independent of the electric field strength. Here an alternative and easy route for obtaining band flattening in thermodynamically stable functionalized monolayer graphene is introduced. Our work discloses a new avenue for research on band flattening in monolayer graphene.

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: 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: Stable emissive carbon nanodots were generated in zeolite crystals using near infrared photon irradiation gradually converting the occluded organic template, originally used to synthesize the zeolite crystals, into discrete luminescent species consisting of nano-sized carbogenic fluorophores, as ascertained using Raman microscopy, and steady-state and time-resolved spectroscopic techniques. Photoactivation in a confocal laser fluorescence microscope allows 3D resolved writing of luminescent carbon nanodot patterns inside zeolites providing a cost-effective and non-toxic alternative to previously reported metal-based nanoclusters confined in zeolites, and opens up opportunities in bio-labelling and sensing applications.

Abstract: Two-dimensional materials composed of transition metal carbides and nitrides (MXenes) are poised to revolutionize energy conversion and storage. In this work, we used density functional theory (DFT) to investigate the adsorption of Mg and Na adatoms on five M2CS2 monolayers (where M = Mo, Nb, Ti, V, and Zr) for battery applications. We assessed the stability of the adatom (i.e. Na and Mg)-monolayer systems by calculating adsorption and formation energies, as well as voltages as a function of surface coverage. For instance, we found that Mo2CS2 cannot support a full layer of Na nor even a single Mg atom. Na and Mg exhibit the strongest binding on Zr2CS2, followed by Ti2CS2, Nb2CS2 and V2CS2. Using the nudged elastic band method (NEB), we computed promising diffusion barriers for both dilute and nearly full ion surface coverage cases. In the dilute ion adsorption case, a single Mg and Na atom on Ti2CS2 experience similar to 0.47 eV and similar to 0.10 eV diffusion barriers between the lowest energy sites, respectively. For a nearly full surface coverage, a Na ion moving on Ti2CS2 experiences a similar to 0.33 eV energy barrier, implying a concentration-dependent diffusion barrier. Our molecular dynamics results indicate that the three (one) layers (layer) of the Mg (Na) ion on both surfaces of Ti2CS2 remain stable at T = 300 K. While, according to voltage calculations, Zr2CS2 can store Na up to three atomic layers, our MD simulations predict that the outermost layers detach from the Zr2CS2 monolayer due to the weak interaction between Na ions and the monolayer. This suggests that MD simulations are essential to confirm the stability of an ion-electrode system – an insight that is mostly absent in previous studies.

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: This current review focuses on contributions to amphetamine-type substances (ATS) analysis. This type of synthetic illicit drugs has been increasingly present worldwide reaching 5% of the market on illicit drugs in 2019. The increment of their production in many clandestine laboratories and easy distribution among society are two of the main concerns towards the battle against synthetic drugs. Therefore, the first part of this review details the classification and mechanism of action of ATS in the human body. Second, the pharmacological and toxicological effects of ATS on human health are described to motivate the need of early detection of ATS. Subsequently, the most used laboratory-based and portable methods are presented and critically discussed along the review. Finally, a careful discussion on the advantages and disadvantages of portable techniques employed on the field are addressed as potential tools for on-site ATS detection by law enforcement officers.

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.

Abstract: In the present work, the identification of two hexagonal phases of germanium oxides (namely GeO2 and GeO) through the vibrational and optical properties is reported using density functional theory calculations. While structural optimizations show that single-layer GeO2 and GeO crystallize in 1T and buckled phases, phonon band dispersions reveal the dynamical stability of each structure. First-order off-resonant Raman spectral predictions demonstrate that each free-standing single-layer possesses characteristic peaks that are representative for the identification of the germanium oxide phase. On the other hand, electronic band dispersion analysis shows the insulating and large-gap semiconducting nature of single-layer GeO2 and GeO, respectively. Moreover, optical absorption, reflectance, and transmittance spectra obtained by means of G(0)W(0)-BSE calculations reveal the existence of tightly bound excitons in each phase, displaying strong optical absorption. Furthermore, the excitonic gaps are found to be at deep UV and visible portions of the spectrum, for GeO2 and GeO crystals, with energies of 6.24 and 3.10 eV, respectively. In addition, at the prominent excitonic resonances, single-layers display high reflectivity with a zero transmittance, which is another indication of the strong light-matter interaction inside the crystal medium.

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: Immobilization of single metal atoms on a solid host opens numerous possibilities for catalyst designs. If that host is a two-dimensional sheet, sheet curvature becomes a design parameter potentially complementary to host and metal composition. Here, we use a combination of density functional theory calculations and microkinetic modeling to compare the mechanisms and kinetics of formic acid decomposition and formation, chosen for their relevance as a potential hydrogen storage medium, over single Ru atoms anchored to pyridinic nitrogen in a planar graphene flake (RuN4-G) and curved carbon nanotube (RuN4-CNT). Activation barriers are lowered and the predicted turnover frequencies are increased over RuN4-CNT relative to RuN4-CNT. The results highlight the potential of curvature control as a means to achieve high performance and robust catalysts.

Abstract: In this work, motivated by the fabrication of an AlSb monolayer, we have focused on the electronic, mechanical and optical properties of AlSb and InSb monolayers with double-layer honeycomb structures, employing the density functional theory approach. The phonon band structure and cohesive energy confirm the stability of the XSb (X = Al and In) monolayers. The mechanical properties reveal that the XSb monolayers have a brittle nature. Using the GGA + SOC (HSE + SOC) functionals, the bandgap of the AlSb monolayer is predicted to be direct, while InSb has a metallic character using both functionals. We find that XSb (X = Al, In) two-dimensional bodies can absorb ultraviolet light. The present findings suggest several applications of AlSb and InSb monolayers in novel optical and electronic usages.