Abstract: A Ti-Beta zeolite was used in gas phase photocatalytic CO2 reduction to reduce the charge recombination rate and increase the surface area compared to P25 as commercial benchmark, reaching 607 m2 g-1. By adding Pt nanoparticles, the selectivity can be tuned toward CO, reaching a value of 92% and a turnover frequency (TOF) of 96 µmol.gcat-1.h-1, nearly an order of magnitude higher in comparison with P25. By adding Pd nanoparticles the selectivity can be shifted from CO (70% for a bare Ti-Beta zeolite), toward CH4 as the prevalent species (60%). In this way, the selectivity toward CO or CH4 can be tuned by either using Pt or Pd. The TOF values obtained in this work outperform reported state-of-the-art values in similar research. The improved activity by adding the nanoparticles was attributed to an improved charge separation efficiency, together with a plasmonic contribution of the metal nanoparticles under the applied experimental conditions.

Abstract: At its core, reticular chemistry has translated the precision and expertise of organic and inorganic synthesis to the solid state. While initial excitement over metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) was undoubtedly fueled by their unprecedented porosity and surface areas, the most profound scientific innovation of the field has been the elaboration of design strategies for the synthesis of extended crystalline solids through strong directional bonds. In this contribution we highlight the different classes of reticular materials that have been developed, how these frameworks can be functionalized and how complexity can be introduced into their backbones. Finally, we show how the structural control over these materials is being extended from the molecular scale to their crystal morphology and shape on the nanoscale, all the way to their shaping on the bulk scale.

Abstract: The differentiation between missing linker defects
and missing cluster defects in MOFs is difficult, thereby limiting the
ability to correlate materials properties to a specific type of defects.
Herein, we present a novel and easy synthesis strategy for the
creation of solely “missing cluster defects” by preparing mixed-metal
(Zn, Zr)-UiO-66 followed by a gentle acid wash to remove the Zn
nodes. The resulting material has the reo UiO-66 structure, typical
for well-defined missing cluster defects. The missing clusters are
thoroughly characterized, including low-pressure Ar-sorption, iDPCSTEM
at a low dose (1.5 pA), and XANES/EXAFS analysis. We
show that the missing cluster UiO-66 has a negligible number of missing linkers. We show the performance of the missing cluster
UiO-66 in CO2 sorption and heterogeneous catalysis.

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: Industrial ammonia production without CO2 emission and with low energy consumption is one of the technological grand challenges of this age. Current Haber-Bosch ammonia mass production processes work with a thermally activated iron catalyst needing high pressure. The need for large volumes of hydrogen gas and the continuous operation mode render electrification of Haber-Bosch plants difficult to achieve. Electrochemical solutions at low pressure and temperature are faced with the problematic inertness of the nitrogen molecule on electrodes. Direct reduction of N2 to ammonia is only possible with very reactive chemicals such as lithium metal, the regeneration of which is energy intensive. Here, the attractiveness of an oxidative route for N2 activation was presented. N2 conversion to NOx in a plasma reactor followed by reduction with H2 on a heterogeneous catalyst at low pressure could be an energy-efficient option for small-scale distributed ammonia production with renewable electricity and without intrinsic CO2 footprint.

Abstract: Direct conversion of CH4 and CO2 to liquid fuels and chemicals under mild conditions is appealing for biogas conversion and utilization but challenging due to the inert nature of both gases. Herein, we report a promising plasma process for the catalyst-free single-step conversion of CH4 and CO2 into higher value oxygenates (i.e., methanol, acetic acid, ethanol, and acetone) at ambient pressure and room temperature using a water-cooled dielectric barrier discharge (DBD) reactor, with methanol being the main liquid product. The distribution of liquid products could be tailored by tuning the discharge power, reaction temperature and residence time. Lower discharge powers (10–15 W) and reaction temperatures (5–20 ◦ C) were favourable for the production of liquid products, achieving the highest methanol selectivity of 43% at 5 ◦ C and 15 W. A higher discharge power and reaction temperature, on the other hand, produced more gaseous products, particularly H2 (up to 26% selec­tivity) and CO (up to 33% selectivity). In addition, varying these process parameters (discharge power, reaction temperature and residence time) resulted in a simultaneous change in key discharge properties, such as mean electron energy (Ee), electron density (ne) and specific energy input (SEI), all of which are essential determiners of plasma chemical reactions. According to the results of artificial neural network (ANN) models, the relative importance of these process parameters and key discharge indicators on reaction performance follows the order: discharge power > reaction temperature > residence time, and SEI > ne > Ee, respectively. This work provides new insights into the contributions and tuning mechanism of multiple parameters for optimizing the reaction performance (e.g., liquid production) in the plasma gas conversion process.

Abstract: The Stöber method is one of the most important and fundamental processes for the synthesis of inorganic (nano)materials but has the drawback of using a large amount of organic solvent. Herein, ethanol was used as an example to explore if the organic solvent in a typical Stöber method can be omitted. It was found that ethanol increases the particle size of the obtained silica spheres and aids the formation of uniform silica particles rather than forming a gel. Nevertheless, the results indicated that an organic solvent in the initial synthesis mixture is not indispensable. An initially immiscible synthesis method was discovered, which can replace the organic solvent-based Stöber method to successfully synthesize silica particles with the same size ranges as the original Stöber process without addition of organic solvents. Moreover, this process can be of further value for the extension to synthesis processes of other materials based on the Stöber process.

Abstract: Plasma-catalytic dry reforming of CH4 (DRM) is promising to convert the greenhouse gasses CH4 and CO2 into value-added chemicals, thus simultaneously providing an alternative to fossil resources as feedstock for the chemical industry. However, while many experiments have been dedicated to plasma-catalytic DRM, there is no consensus yet in literature on the optimal choice of catalyst for targeted products, because the underlying mechanisms are far from understood. Indeed, plasma catalysis is very complex, as it encompasses various chemical and physical interactions between plasma and catalyst, which depend on many parameters. This complexity hampers the comparison of experimental results from different studies, which, in our opinion, is an important bottleneck in the further development of this promising research field. Hence, in this perspective paper, we describe the important physical and chemical effects that should be accounted for when designing plasma-catalytic experiments in general, highlighting the need for standardized experimental setups, as well as careful documentation of packing properties and reaction conditions, to further advance this research field. On the other hand, many parameters also create many windows of opportunity for further optimizing plasma-catalytic systems. Finally, various experiments also reveal the lack of improvement in plasma catalysis compared to plasma-only, specifically for DRM, but the underlying mechanisms are unclear. Therefore, we present our newly developed coupled plasma-surface kinetics model for DRM, to provide more insight in the underlying reasons. Our model illustrates that transition metal catalysts can adversely affect plasmacatalytic DRM, if radicals dominate the plasma-catalyst interactions. Thus, we demonstrate that a good understanding of the plasma-catalyst interactions is crucial to avoiding conditions at which these interactions negatively affect the results, and we provide some recommendations for improvement. For instance, we believe that plasma-catalytic DRM may benefit more from higher reaction temperatures, at which vibrational excitation can enhance the surface reactions.

Abstract: Plasma catalysis has emerged as a promising approach for driving thermodynamically unfavorable chemical
reactions. Nevertheless, comprehending the mechanisms involved remains a challenge, leading to uncertainty
about whether the optimal catalyst in plasma catalysis aligns with that in thermal catalysis. In this research, we
explore this question by studying monometallic catalysts (Fe, Co, Ni and Mo) and bimetallic catalysts (Fe-Co, Mo-
Co, Fe-Ni and Mo-Ni) in both thermal catalytic and plasma catalytic NH3 decomposition. Our findings reveal that
the Fe-Co bimetallic catalyst exhibits the highest activity in thermal catalysis, the Fe-Ni bimetallic catalyst
outperforms others in plasma catalysis, indicating a discrepancy between the optimal catalysts for the two
catalytic modes in NH3 decomposition. Comprehensive catalyst characterization, kinetic analysis, temperature
program surface reaction experiments and plasma diagnosis are employed to discuss the key factors influencing
NH3 decomposition performance.

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.