Abstract: Plasma catalysis is a rapidly growing field, often employing a packed-bed dielectric barrier discharge plasma reactor. Such dielectric barrier discharges are complex, especially when a packing material (e.g., a catalyst) is introduced in the discharge volume. Catalysts are known to affect the plasma discharge, though the underlying mechanisms influencing the plasma physics are not fully understood. Moreover, the effect of the catalysts on the plasma discharge and its subsequent effect on the overall performance is often overlooked. In this work, we deliberately design and synthesize catalysts to affect the plasma discharge in different ways. These Ni or Co alumina-based catalysts are used in plasma-catalytic dry reforming of methane and ammonia synthesis. Our work shows that introducing a metal to the dielectric packing can affect the plasma discharge, and that the distribution of the metal is crucial in this regard. Further, the altered discharge can greatly influence the overall performance. In an atmospheric pressure dielectric barrier discharge reactor, this apparently more uniform plasma yields a significantly better performance for ammonia synthesis compared to the more conventional filamentary discharge, while it underperforms in dry reforming of methane. This study stresses the importance of analyzing the plasma discharge in plasma catalysis experiments. We hope this work encourages a more critical view on the plasma discharge characteristics when studying various catalysts in a plasma reactor.

Abstract: This study investigates the dry reformation of methane (DRM) over Ni/Al2O3 catalysts in a dielectric barrier discharge (DBD) non-thermal plasma reactor. A novel hybrid machine learning (ML) model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data. To address the non-linear and complex nature of the plasma-catalytic DRM process, the hybrid ML model integrates three well-established algorithms: regression trees, support vector regression, and artificial neural networks. A genetic algorithm (GA) is then used to optimize the hyperparameters of each algorithm within the hybrid ML model. The ML model achieved excellent agreement with the experimental data, demonstrating its efficacy in accurately predicting and optimizing the DRM process. The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance. We found that the optimal discharge power (20 W), CO2/CH4 molar ratio (1.5), and Ni loading (7.8 wt%) resulted in the maximum energy yield at a total flow rate of
51 mL/min. Furthermore, we investigated the relative significance of each operating parameter on the performance of the plasmacatalytic DRM process. The results show that the total flow rate had the greatest influence on the conversion, with a significance exceeding 35% for each output, while the Ni loading had the least impact on the overall reaction performance. This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets, enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.

Abstract: Handedness is an essential attribute of chiral nanocrystals, having a major influence on their properties. During chemical growth, the handedness of nanocrystals is usually tuned by selecting the corresponding enantiomer of chiral molecules involved in asymmetric growth, often known as chiral inducers. We report that, even using the same chiral inducer enantiomer, the handedness of chiral gold nanocrystals can be reversed by using Au nanorod seeds with either single crystalline or pentatwinned structure. This effect holds for chiral growth induced both by amino acids and by chiral micelles. Although it was challenging to discern the morphological handedness for<italic>L</italic>‐cystine‐directed particles, even using electron tomography, both cases showed circular dichroism bands of opposite sign, with nearly mirrored chiroptical signatures for chiral micelle‐directed growth, along with quasi‐helical wrinkles of inverted handedness. These results expand the chiral growth toolbox with an effect that might be exploited to yield a host of interesting morphologies with tunable optical properties.

Abstract: Density functional theory is widely used to gain insights into molecule−metal surface reaction networks, which is important for a better understanding of catalysis. However, it is well-known that generalized gradient approximation (GGA)
density functionals (DFs), most often used for the study of reaction networks, struggle to correctly describe both gas-phase molecules and metal surfaces. Also, GGA DFs typically underestimate reaction barriers due to an underestimation of the selfinteraction energy. Screened hybrid GGA DFs have been shown to reduce this problem but are currently intractable for wide usage. In this work, we use a more affordable meta-GGA (mGGA) DF in combination with a nonlocal correlation DF for the first time to study and gain new insights into a catalytically important surface
reaction network, namely, CO2 hydrogenation on Cu. We show that the mGGA DF used, namely, rMS-RPBEl-rVV10, outperforms typical GGA DFs by providing similar or better predictions for metals and molecules, as well as molecule−metal surface adsorption
and activation energies. Hence, it is a better choice for constructing molecule−metal surface reaction networks.

Abstract: The engineering, construction, performance and running costs of a catalytic flue gas cleaning component in the low dust area of a municipal waste incinerator is discussed. For this purpose, the case study of a Flemish incineration plant is presented, covering the history, the design procedure of the catalyst, relevant process data and the financial aspects. A reliable PCDD/F-destruction by means of oxidation by the catalyst to typical values of 0.001 ng TEQ/N m3 has been demonstrated. At the same time, NOx- and CO-emissions are reduced by 90% and 20% to about 50 mg/N m3 and below 10 mg/N m3, respectively.

Abstract: The principal aim of this work is to study the effect of the processes of sintering and Pd doping of SnO2 gas sensor materials on the conversion of CO to CO2. For this purpose, the gas phase above screen printed sensor material is investigated using FTIR spectroscopy, while surface area, porosity and particle size measurements are performed on the SnO2 powders. During sintering, larger agglomerates of primary particles are formed, which results in a larger conversion degree of CO. The effect of Pd doping of the tin dioxide film on the CO conversion is more pronounced. The transformation of CO starts at a lower temperature and the conversion degree increases remarkably.

Abstract: In this manuscript, we compare different analytical methodologies to validate or disprove the binding capabilities of aptamer sequences. This was prompted by the lack of a universally accepted and robust quality control protocol for the characterization of aptamer performances coupled with the observation of independent yet inconsistent data sets in the literature. As an example, we chose three aptamers with a reported affinity in the nanomolar range for ampicillin, a β-lactam antibiotic, used as biorecognition elements in several detection strategies described in the literature. Application of a well-known colorimetric assay based on aggregation of gold nanoparticles (AuNPs) yielded conflicting results with respect to the original report. Therefore, ampicillin binding was evaluated in solution using isothermal titration calorimetry (ITC), native nano-electrospray ionization mass spectrometry (native nESI-MS), and 1H-nuclear magnetic resonance spectroscopy (1H NMR). By coupling the thermodynamic data obtained with ITC with the structural information on the binding event given by native nESI-MS and 1H NMR we could verify that none of the ampicillin aptamers show any specific binding with their intended target. The effect of AuNPs on the binding event was studied by both ITC and 1H NMR, again without providing positive evidence of ampicillin binding. To validate the performance of our analytical approach, we investigated two well-characterized aptamers for cocaine/quinine (MN4), chosen for its nanomolar range affinity, and l-argininamide (1OLD) to show the versatility of our approach. The results clearly indicate the need for a multifaceted analytical approach, to unequivocally establish the actual detection potential and performance of aptamers aimed at small organic molecules.

Abstract: Metal-organic frameworks (MOFs) are exciting materials due to their extensive applicability in a multitude of modern technological fields. Their most prominent characteristic and primary origin of their widespread success is the exceptional variety of their structures, which we termed 'reticular diversity'. Naturally, the ever-emerging applications of MOFs made it increasingly common that researchers from various areas delve into reticular chemistry to overcome their scientific challenges. This confers a crucial role to comprehensive overviews capable of providing newcomers with the knowledge of the state of the art, as well as with the key physics and chemistry considerations needed to design MOFs for a specific application. In this review, we commit to this purpose by outlining the fundamental understanding needed to carefully navigate MOFs' reticular diversity in their main fields of application, namely hostguest chemistry, chemical sensing, electronics, photophysics, and catalysis. Such knowledge and a meticulous, open-minded approach to the design of MOFs paves the way for their most innovative and successful applications, and for the global advancement of the research areas they are employed in. (C) 2020 Elsevier B.V. All rights reserved.

Abstract: Natural deep eutectic solvents (NADES) are mixtures of naturally derived compounds with a significantly decreased melting point due to the specific interactions among the constituents. NADES have benign properties (low volatility, flammability, toxicity, cost) and tailorable physicochemical properties (by altering the type and molar ratio of constituents), hence they are often considered as a green alternative to common organic solvents. Modeling the relation between their composition and properties is crucial though, both for understanding and predicting their behavior. Several efforts were done to this end, yet this review aims at structuring the present knowledge as an outline for future research. First, we reviewed the key properties of NADES and relate them to their structure based on the available experimental data. Second, we reviewed available modeling methods applicable to NADES. At the molecular level, density functional theory and molecular dynamics allow interpreting density differences and vibrational spectra, and computation of interaction energies. Additionally, properties at the level of the bulk media can be explained and predicted by semi-empirical methods based on ab initio methods (COSMO-RS) and equation of state models (PC-SAFT). Finally, methods based on large datasets are discussed; models based on group contribution methods and machine learning. A combination of bulk media and dataset modeling allows qualitative prediction and interpretation of phase equilibria properties on the one hand, and quantitative prediction of melting point, density, viscosity, surface tension and refractive indices on the other hand. In our view, multiscale modeling, combining the molecular and macroscale methods, will strongly enhance the predictability of NADES properties and their interaction with solutes, yielding truly tailorable solvents to accommodate (bio)chemical reactions.

Abstract: The pursuit of two-dimensional (2D) borides, MBenes, has proven to be challenging, not the least because of the lack of a suitable precursor prone to the deintercalation. Here, we studied room-temperature topochemical deintercalation of lithium from the layered polymorphs of the LiNiB compound with a considerable amount of Li stored in between [NiB] layers (33 at. % Li). Deintercalation of Li leads to novel metastable borides (Li similar to 0.5NiB) with unique crystal structures. Partial removal of Li is accomplished by exposing the parent phases to air, water, or dilute HCl under ambient conditions. Scanning transmission electron microscopy and solid-state Li-7 and B-1(1) NMR spectroscopy, combined with X-ray pair distribution function (PDF) analysis and DFT calculations, were utilized to elucidate the novel structures of (Li similar to 0.5NiB) and the mechanism of Li-deintercalation. We have shown that the deintercalation of Li proceeds via a “zip-lock” mechanism, leading to the condensation of single [NiB] layers into double or triple layers bound via covalent bonds, resulting in structural fragments with Li[NiB](2) and Li[NiB](3) compositions. The crystal structure of Li similar to 0.5NiB is best described as an intergrowth of the ordered single [NiB], double [NiB](2), or triple [NiB](3) layers alternating with single Li layers; this explains its structural complexity. The formation of double or triple [NiB] layers induces a change in the magnetic behavior from temperature-independent paramagnets in the parent LiNiB compounds to the spin-glassiness in the deintercalated Li similar to 0.5NiB counterparts. LiNiB compounds showcase the potential to access a plethora of unique materials, including 2D MBenes (NiB).

Abstract: Quintuple perovskites Sm2Ba3Fe5-xCoxO15-delta = 0.5, 1.0 and 1.5) have been prepared by glycerin-nitrate tech- nique in air. The phase purity was confirmed by XRD. Partial substitution of Co for Fe decreases the oxygen content and thus the mean oxidation state of 3d-metals. It also slightly decreases the thermal expansion coefficient of oxides. Positive value of the Seebeck coefficient confirmed p-type conductivity, though the thermopower decreases as the Co content increases. The temperature dependence of electrical conductivity reveals a maximum at 550-750 degrees C.

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: 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: The electronic and optical properties of vertical heterostructures (HTSs) and lateral heterojunctions (HTJs) between (B,N)-codoped graphene (dop@Gr) and graphene (Gr), C3N, BC3 and h-BN monolayers are investigated using van der Waals density functional theory calculations. We have found that all the considered HTSs are energetically and thermally feasible at room temperature, and therefore they can be synthesized experimentally. The dop@Gr/Gr, BC3/dop@Gr and BN/dop@Gr HTSs are semiconductors with direct bandgaps of 0.1 eV, 80 meV and 1.23 eV, respectively, while the C3N/dop@Gr is a metal because of the strong interaction between dop@Gr and C3N layers. On the other hand, the dop@Gr-Gr and BN-dop@Gr HTJs are semiconductors, whereas the C3N-dop@Gr and BC3-dop@Gr HTJs are metals. The proposed HTSs can enhance the absorption of light in the whole wavelength range as compared to Gr and BN monolayers. The applied electric field or pressure strain changes the bandgaps of the HTSs and HTJs, indicating that these HTSs are highly promising for application in nanoscale multifunctional devices.