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: WO3 isa 5d compound that undergoes severalstructuraltransitions in its bulk form. Its versatility is well-documented,with a wide range of applications, such as flexopiezoelectricity,electrochromism, gating-induced phase transitions, and its abilityto improve the performance of Li-based batteries. The synthesis ofWO(3) thin films holds promise in stabilizing electronicphases for practical applications. However, despite its potential,the electronic structure of this material remains experimentally unexplored.Furthermore, its thermal instability limits its use in certain technologicaldevices. Here, we employ tensile strain to stabilize WO3 thin films, which we call the pseudotetragonal phase, and investigateits electronic structure using a combination of photoelectron spectroscopyand density functional theory calculations. This study reveals theFermiology of the system, notably identifying significant energy splittingsbetween different orbital manifolds arising from atomic distortions.These splittings, along with the system's thermal stability,offer a potential avenue for controlling inter- and intraband scatteringfor electronic applications.

Abstract: DNA nanotechnology has a great potential in biosensor design including nanostructuring of the biosensor surface through DNA origami, target recognition by means of aptamers, and DNA-based signal amplification strategies. In this paper, we use DNA nanotechnology to describe for the first time the concept of real-time solid-phase monitoring of DNAzyme cleavage activity for the detection of specific single-stranded DNA (ssDNA) with a fiber optic surface plasmon resonance (FO-SPR) biosensor. Hereto, we first developed a robust ligation strategy for the functionalization of the FO-SPR biosensing surface with ssDNA-tethered gold nanoparticles, serving as the substrate for the DNAzyme. Next, we established a relation between the SPR signal change, due to the cleavage activity of the 10–23 DNAzyme, and the concentration of the DNAzyme, showing faster cleavage kinetics for higher DNAzyme concentrations. Finally, we implemented this generic concept for biosensing of ssDNA target in solution. Hereto, we designed a DNAzyme–inhibitor complex, consisting of an internal loop structure complementary to the ssDNA target, that releases active DNAzyme molecules in a controlled way as a function of the target concentration. We demonstrated reproducible target detection with a theoretical limit of detection of 1.4 nM, proving that the presented ligation strategy is key to a universal DNAzyme-based FO-SPR biosensing concept with promising applications in the medical and agrofood sector.

Abstract: The filtration process within a membrane bioreactor (MBR) is mostly controlled in a classic way through typical set-points such as aeration flow rate, filtration duration, backwash frequency or relaxation duration. The values of these filtration set-points result from experience and remain often unchanged during the installations operational lifetime. Filtration is dictated considerably by membrane fouling phenomena. The fouling potential of the mixed liquor however can significantly fluctuate, even daily, from changing influent characteristics. Fixed set-point values thus may represent sub-optimal filtration conditions. Consequently, a supervising advanced control system, being able to continuously adapt the set-points values would be beneficial regarding the MBR filtration process optimization. Such optimization could reduce the corresponding MBR energy consumption, e.g. linked to the filtration related membrane aeration. An Advanced Control System (ACS) based on Fuzzy Set Logic (FSL) is introduced here, enabling to supervise an existing classic membrane filtration control system. Such ACS is able to daily (or even more frequent) optimize the set-points of the underlying classic control system, from the input of various sensor and process parameter values. The theoretical background and practical implementation of the FSL based ACS concept is explained.

Abstract: This work presents the results of a novel application for the fast on-site screening of cocaine and its main cutting agents in suspicious and confiscated samples. The methodology behind the novel application consists of portable electrochemical detection coupled with a peak-recognition algorithm for automated result output generation, validated both in laboratory and field settings. Currently used field tests, predominantly colorimetric tests, are lacking accuracy, often giving false positive or negative results. This presses the need for alternative approaches to field testing. By combining portable electrochemical approaches with peak-recognition algorithms, an accuracy of 98.4% concerning the detection of cocaine was achieved on a set of 374 powder samples. In addition, the approach was tested on multiple 'smuggled', colored cocaine powders and cocaine mixtures in solid and liquid states, typically in matrices such as charcoal, syrup and clothing. Despite these attempts to hide cocaine, our approach succeeded in detecting cocaine during on-site screening scenarios. This feature presents an advantage over colorimetric and optical detection techniques, which can fail with colored sample matrices. This enhanced accuracy on smuggled samples will lead to increased efficiency in confiscation procedures in the field, thus significantly reducing societal economic and safety concerns and highlighting the potential for electrochemical approaches in on-the-spot identification of drugs of abuse.

Abstract: More and more countries and organisations emphasise the value of harm reduction measures in the context of illicit drug use and abuse. One of these measures is drug checking, a preventive action that can represent a quick win by tailored consultation on the risks of substance use upon analytical screening of a submitted sample. Unlike drop-in centres that operate within a fixed setting, enabling drug checking in a harm reduction context at events requires portable, easy to use analytical approaches, operated by personnel with limited knowledge of analytical chemistry. In this case study, four different approaches were compared for the characterisation of 3,4-methylenedioxymethamphetamine samples and this in the way the approaches would be applied today in an event context. The four approaches are mid-infrared (MIR), near-infrared, and Raman spectroscopy, which are today used in drug checking context in Belgium, as well as an electrochemical sensor approach initially developed in the context of law enforcement at ports. The MIR and the electrochemical approach came out best, with the latter allowing for a direct straightforward analysis of the percentage 3,4-methylenedioxymethamphetamine (as base equivalent) in the samples. However, MIR has the advantage that, in a broader drug checking context, it allows to screen for several molecules and so is able to identify unexpected active components or at least the group to which such components belong. The latter is also an important advantage in the context of the growing emergence of new psychotropic substances. MIR, NIR, Raman spectroscopy, and an electrochemical sensor (Narcoreader (R)) for MDMA analysis were compared in a realistic harm reduction context. NIR and Raman failed in simple library approaches. MIR and Narcoreader (R) were preferred. MIR came out as first choice. MIR and Narcoreader (R) have complementary (dis)advantages and could be used in a two-step approach: MIR for screening and Narcoreader (R) for dosage/risk evaluation of MDMA samples.image

Abstract: Enhanced weathering (EW) is an emerging carbon dioxide (CO2) removal technology that can contribute to climate change mitigation. This technology relies on accelerating the natural process of mineral weathering in soils by manipulating the abiotic variables that govern this process, in particular mineral grain size and exposure to acids dissolved in water. EW mainly aims at reducing atmospheric CO2 concentrations by enhancing inorganic carbon sequestration. Until now, knowledge of EW has been mainly gained through experiments that focused on the abiotic variables known for stimulating mineral weathering, thereby neglecting the potential influence of biotic components. While bacteria, fungi, and earthworms are known to increase mineral weathering rates, the use of soil organisms in the context of EW remains underexplored. This protocol describes the design and construction of an experimental setup developed to enhance mineral weathering rates through soil organisms while concurrently controlling abiotic conditions. The setup is designed to maximize weathering rates while maintaining soil organisms' activity. It consists of a large number of columns filled with rock powder and organic material, located in a climate chamber and with water applied via a downflow irrigation system. Columns are placed above a fridge containing jerrycans to collect the leachate. Representative results demonstrate that this setup is suitable to ensure the activity of soil organisms and quantify their effect on inorganic carbon sequestration. Challenges remain in minimizing leachate losses, ensuring homogeneous ventilation through the climate chamber, and avoiding flooding of the columns. With this setup, an innovative and promising approach is proposed to enhance mineral weathering rates through the activity of soil biota and disentangle the effect of biotic and abiotic factors as drivers of EW.

Abstract: High-entropy materials are an emerging pathway in the development of high-activity (electro)catalysts because of the inherent tunability and coexistence of multiple potential active sites, which may lead to earth-abundant catalyst materials for energy-efficient electrochemical energy storage. In this report, we identify how the multication composition in high-entropy perovskite oxides (HEO) contributes to high catalytic activity for the oxygen evolution reaction (OER), i.e., the key kinetically limiting half-reaction in several electrochemical energy conversion technologies, including green hydrogen generation. We compare the activity of the (001) facet of LaCr0.2Mn0.2Fe0.2Co0.2Ni0.2O3-delta with the parent compounds (single B-site in the ABO3 perovskite). While the single B-site perovskites roughly follow the expected volcano-type activity trends, the HEO clearly outperforms all of its parent compounds with 17 to 680 times higher currents at a fixed overpotential. As all samples were grown as an epitaxial layer, our results indicate an intrinsic composition-function relationship, avoiding the effects of complex geometries or unknown surface composition. In-depth X-ray photoemission studies reveal a synergistic effect of simultaneous oxidation and reduction of different transition metal cations during the adsorption of reaction intermediates. The surprisingly high OER activity demonstrates that HEOs are a highly attractive, earth-abundant material class for high-activity OER electrocatalysts, possibly allowing the activity to be fine-tuned beyond the scaling limits of mono-or bimetallic oxides.

Abstract: Van der Waals quantum wells, naturally formed in two-dimensional layered materials with nanoscale thickness, possess many inherent advantages over conventional molecular beam epitaxy grown counterparts, and could bring up intriguing physics and applications. However, optical transitions originated from the series of quantized states in these emerging quantum wells are still elusive. Here, we show that multilayer black phosphorus appears to be an excellent candidate for van der Waals quantum wells with well-defined subbands and high optical quality. Using infrared absorption spectroscopy, we probe subband structures of multilayer black phosphorus with tens of atomic layers, revealing clear signatures for optical transitions with subband index as high as 10, far from what was attainable previously. Surprisingly, in addition to allowed transitions, an unexpected series of “forbidden” transitions is also evidently observed, which enables us to determine energy spacings separately for conduction and valence subbands. Furthermore, the linear tunability of subband spacings by temperature and strain is demonstrated. Our results are expected to facilitate potential applications for infrared optoelectronics based on tunable van der Waals quantum wells.

Abstract: The efficiency of light emission is a critical performance factor for monolayer transition metal dichalcogenides (1L-TMDs) for photonic applications. While various methods have been studied to compensate for lattice defects to improve the quantum yield (QY) of 1L-TMDs, exciton-exciton annihilation (EEA) is still a major nonradiative decay channel for excitons at high exciton densities. Here, we demonstrate that the combined use of a proximal Au plate and a negative electric gate bias (NEGB) for 1L-WS2 provides a dramatic enhancement of the exciton lifetime at high exciton densities with the corresponding QY enhanced by 30 times and the EEA rate constant decreased by 80 times. The suppression of EEA by NEGB is attributed to the reduction of the defect-assisted EEA process, which we also explain with our theoretical model. Our results provide a synergetic solution to cope with EEA to realize high-intensity 2D light emitters using TMDs.

Abstract: Assemblies of closely separated gold nanoparticles exhibit a strong collective plasmonic response due to coupling of the plasmon modes of the individual nanostructures. In the context of self-assembly of nanoparticles, close-packed two-dimensional (2D) clusters of spherical nanoparticles present an important composite system that promises numerous applications. The present study probes the collective plasmonic characteristics and resulting photothermal behavior of close-packed 2D Au nanoparticle clusters to delineate the effects of the cluster size, interparticle distance, and particle size. Smaller nanoparticles (20 and 40 nm in diameter) that exhibit low individual scattering and high absorption were considered for their relevance to photothermal applications. In contrast to typical literature studies, the present study compares the optical response of clusters of different sizes ranging from a single nanoparticle up to large assemblies of 61 nanoparticles. Increasing the cluster size induces significant changes to the spectral position and optophysical characteristics. Based on the model outcome, an optimal cluster size for maximum absorption per nanoparticle is also determined for enhanced photothermal effects. The effect of the particle size and interparticle distance is investigated to elucidate the nature of interaction in terms of near-field and far-field coupling. The photothermal effect resulting from absorption is compared for different cluster sizes and interparticle distances considering a homogeneous water medium. A strong dependence of the steady-state temperature of the nanoparticles on the cluster size, particle position in the cluster, incident light polarization, and interparticle distance provides new physical insight into the local temperature control of plasmonic nanostructures.

Abstract: The reduction of dimensionality is a very effective way to achieve appealing properties in two-dimensional materials (2DMs). First-principles calculations can greatly facilitate the prediction of 2DM properties and find possible approaches to enhance their performance. We employed first-principles calculations to gain insight into the impact of different types of point defects (vacancies and substitutional dopants) on the electronic and magnetic properties of a ZnSnN2 (ZSN) monolayer. We show that Zn, Sn, and N + Zn vacancy-defected structures are p-type conducting, while the defected ZSN with a N vacancy is n-type conducting. For substitutional dopants, we found that all doped structures are thermally and energetically stable. The most stable structure is found to be B-doping at the Zn site. The highest work function value (5.0 eV) has been obtained for Be substitution at the Sn site. Li-doping (at the Zn site) and Be-doping (at the Sn site) are p-type conducting, while B-doping (at the Zn site) is n-type conducting. We found that the considered ZSN monolayer-based structures with point defects are magnetic, except those with the N vacancy defects and Be-doped structures. The ab initio molecular dynamics simulations confirm that all substitutionally doped and defected structures are thermally stable. Thus, our results highlight the possibility of tuning the magnetism in ZnSnN2 monolayers through defect engineering.

Abstract: Direct experimental measurement of thermal expansion coefficient without substrate effects is a challenging task for two-dimensional (2D) materials, and its accurate estimation with large-scale ab initio molecular dynamics is computationally very expensive. Machine learning-based interatomic potentials trained with ab initio data have been successfully used in molecular dynamics simulations to decrease the computational cost without compromising the accuracy. In this study, we investigated using Gaussian approximation potentials to reproduce the density functional theory-level accuracy for graphene within both lattice dynamical and molecular dynamical methods, and to extend their applicability to larger length and time scales. Two such potentials are considered, GAP17 and GAP20. GAP17, which was trained with pristine graphene structures, is found to give closer results to density functional theory calculations at different scales. Further vibrational and structural analyses verify that the same conclusions can be deduced with density functional theory level in terms of the reasoning of the thermal expansion behavior, and the negative thermal expansion behavior is associated with long-range out-of-plane phonon vibrations. Thus, it is argued that the enabled larger system sizes by machine learning potentials may even enhance the accuracy compared to small-size-limited ab initio molecular dynamics.

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: Semiconductor monolayer transition metal dichalcogenides (TMDs) have brought a new paradigm by introducing optically addressable valley degree of freedom. Concomitantly, their high flexibility constitutes a unique platform that links optics to mechanics via valleytronics. With the intention to expedite the research in this direction, we investigated ten TMDs, namely MoS2, MoSe2, MoTe2, WS2, WSe2, WTe2, MoSSe, MoSeTe, WSSe, and WSeTe, which particularly includes their so-called janus types (JTMDs). First, we obtained their electronic band structures using regular and hybrid density functional theory (DFT) calculations in the presence of the spin-orbit coupling and biaxial or uniaxial strain. Our DFT results indicated that against the expectations based on their reported piezoelectric behavior, JTMDs typically interpolated between the standard band properties of the constituent TMDs without producing a novel feature. Next, by fitting to our DFT data we generated both spinless and spinful k center dot p parameter sets which are quite accurate over the K valley where the optical activity occurs. As an important application of this parametrization, we considered the circular and linear dichroism under strain. Among the studied (J)TMDs, WTe2 stood out with its largest linear dichroism under uniaxial strain because of its narrower band gap and large K valley uniaxial deformation potential. This led us to suggest WTe2 monolayer membranes for optical polarization-based strain measurements, or conversely, as strain tunable optical polarizers.