Abstract: By means of chemical kinetics modeling, it is possible to elucidate the main dissociation mechanisms of CO2 in a gliding arc plasmatron (GAP). We obtain good agreement between the calculated and experimental conversions and energy efficiencies, indicating that the model can indeed be used to study the underlying mechanisms. The calculations predict that vibration-induced dissociation is the main dissociation mechanism of CO2, but it occurs mainly from the lowest vibrational levels because of fast thermalization of the vibrational distribution. Based on these findings, we propose ideas for improving the performance of the GAP, but testing of these ideas in the simulations reveals that they do not always lead to significant enhancement, because of other side effects, thus illustrating the complexity of the process. Nevertheless, the model allows more insight into the underlying mechanisms to be obtained and limitations to be identified.

Abstract: We study the oxygen thermal stability of two binary
systems. The larger particles are magnetic amorphous Co (7.2 nm) or
Fe3O4 (7.5 nm) nanocrystals, whereas the smaller ones (3.7 nm) are
Au nanocrystals. The nanocrystal ordering as well as the choice of the
magnetic nanoparticles very much influence the stability of the binary
system. A perfect crystalline structure is obtained with the Fe3O4/Au
binary supracrystals. For the Co/Au binary system, oxidation of Co
results in the chemical transformation from Co to CoO, where the size
of the amorphous Co nanoparticles increases from 7.2 to 9.8 nm in
diameter. During the volume expansion of the Co nanoparticles, Au
nanoparticles within the binary assemblies coalesce and are at the
origin of the instability of the binary nanoparticle supracrystals. On the
other hand, for the Fe3O4/Au binary system, the oxidation of Fe3O4 to
γ-Fe2O3 does not lead to a size change of the nanoparticles, which
maintains the stability of the binary nanoparticle supracrystals. A similar behavior is observed for an AlB2-type Co−Ag binary
system: The crystalline structure is maintained, whereas in disordered assemblies, coalescence of Ag nanocrystals is observed.

Abstract: The resistance of a TiO2 anatase (001) surface to coke formation was studied in the context of dry reforming of methane using density functional theory (DFT) calculations. As carbon atoms act as precursors for coke formation, the resistance to coke formation can be measured by the carbon coverage of the surface. This is related to the stability of different CHx (x = 0−3) species and their rate of hydrogenation and dehydrogenation on the TiO2 surface. Therefore, we studied the reaction mechanisms and their corresponding rates as a function of the temperature for the dehydrogenation of the species on the surface. We found that the stabilities of C and CH are significantly lower than those of CH3 and CH2. The hydrogenation rates of the different species are significantly higher than the dehydrogenation rates in a temperature range of 300−1000 K. Furthermore, we found that dehydrogenation of CH3, CH2, and CH will only occur at appreciable rates starting from 600, 900, and 900 K, respectively. On the basis of these results, it is clear that the anatase (001) surface has a high coke resistance, and it is thus not likely that the surface will become poisoned by coke during dry reforming of methane. As the rate limiting step in dry reforming is the dissociative adsorption of CH4, we studied an alternative approach to thermal catalysis. We found that the temperature threshold for dry reforming is at least 700 K. This threshold temperature may be lowered by the use of plasma-catalysis, where the appreciable rates of adsorption of plasma-generated CHx radicals result in bypassing the rate limiting step of the reaction.

Abstract: Optimization of catalytic materials for a given application is greatly constrained by linear scaling relations. Recently, however, it has been demonstrated that it is possible to reversibly modulate the chemisorption of molecules on nanomaterials by charging (i.e., injection or removal of electrons) and hence reversibly and selectively modify catalytic activity beyond structure−activity correlations. The fundamental physical relation between the properties of the material, the charging process, and the chemisorption energy, however, remains unclear, and a systematic exploration and optimization of charge-switchable sorbent materials is not yet possible. Using hybrid DFT calculations of CO2 chemisorption on hexagonal boron nitride nanosheets with several types of defects and dopants, we here reveal the existence of fundamental correlations between the electron affinity of a material and charge-induced chemisorption, show how defect engineering can be used to modulate the strength and efficiency of the adsorption process, and demonstrate that excess electrons stabilize many topological defects. We then show how these insights could be exploited in the development of new electrocatalytic materials and the synthesis of doped nanomaterials. Moreover, we demonstrate that calculated chemical properties of charged materials are highly sensitive to the employed computational methodology because of the self-interaction error, which underlines the theoretical challenge posed by such systems.

Abstract: Nonequilibrium plasmas offer a pathway for energy-efficient CO2 conversion through vibrationally induced dissociation. However, the efficiency of this pathway is limited by a rise in gas temperature, which increases vibrational−translational (VT) relaxation and quenches the vibrational levels. Therefore, we investigate here the effect of plasma pulsing on the VT nonequilibrium and on the CO2 conversion by means of a zerodimensional chemical kinetics model, with self-consistent gas temperature calculation. Specifically, we show that higher energy efficiencies can be reached by correctly tuning the plasma pulse and interpulse times. The ideal plasma pulse time corresponds to the time needed to reach the highest vibrational temperature. In addition, the highest energy efficiencies are obtained with long interpulse times, that is, ≥0.1 s, in which the gas temperature can entirely drop to room temperature. Furthermore, additional cooling of the reactor walls can give higher energy efficiencies at shorter interpulse times of 1 ms. Finally, our model shows that plasma pulsing can significantly improve the energy efficiency at low reduced electric fields (50 and 100 Td, typical for microwave and gliding arc plasmas) and intermediate ionization degrees (5 × 10−7 and 10−6).

Abstract: Plasma is gaining interest for CH4 conversion into higher hydrocarbons and H2. However, the performance in terms of conversion and selectivity toward different hydrocarbons is different for different plasma types, and the underlying mechanisms are not yet fully understood. Therefore, we study here these mechanisms in different plasma sources, by means of a chemical kinetics model. The model is first validated by comparing the calculated conversions and hydrocarbon/H2 selectivities with experimental results in these different plasma types and over a wide range of specific energy input (SEI) values. Our model predicts that vibrational−translational nonequilibrium is negligible in all CH4 plasmas investigated, and instead, thermal conversion is important. Higher gas temperatures also lead to a more selective production of unsaturated hydrocarbons (mainly C2H2) due to neutral dissociation of CH4 and subsequent dehydrogenation processes, while three-body recombination reactions into saturated hydrocarbons (mainly C2H6, but also higher hydrocarbons) are dominant in low temperature plasmas.

Abstract: Bimetallic plasmonic nanoparticles enable tuning of the optical response and chemical stability by variation of the composition. The present numerical simulation study compares Ag–Au alloy, Ag@Au core–shell, and Au@Ag core–shell bimetallic plasmonic nanoparticles of both spherical and anisotropic (nanotriangle and nanorods) shapes. By studying both spherical and anisotropic (with LSPR in the near-infrared region) shapes, cases with and without interband transitions of Au can be decoupled. Explicit comparisons are facilitated by numerical models supported by careful validation and examination of optical constants of Au–Ag alloys reported in the literature. Although both Au–Ag core–shell and alloy nanoparticles exhibit an intermediary optical response between that of pure Ag and Au nanoparticles, there are noticeable differences in the spectral characteristics. Also, the effect of the bimetallic constitution in anisotropic nanoparticles is starkly different from that in spherical nanoparticles due to the absence of Au interband transitions in the former case. In general, the improved chemical stability of Ag nanoparticles by incorporation of Au comes with a cost of reduction in plasmonic enhancement, also applicable to anisotropic nanoparticles with a weaker effect. A photothermal heat transfer study confirms that increased absorption by the incorporation of Au in spherical Ag nanoparticles also results in an increased steady-state temperature. On the other hand, anisotropic nanoparticles are inherently better absorbers and hence better photothermal sources, and their photothermal properties are apparently not strongly affected by the incorporation of one metal in the other. This study of the optical/spectral and photothermal characteristics of bimetallic Au–Ag alloy versus core–shell nanoparticles provides detailed physical insight for development of new taylor-made plasmonic nanostructures.

Abstract: Plasma technology is gaining increasing interest for CO2 conversion. The gas temperature in (and after) the plasma reactor largely affects the performance. Therefore, we examine the effect of cooling/quenching, during and after the plasma, on the CO2 conversion and energy efficiency, for typical “warm” plasmas, by means of chemical kinetics modeling. For plasmas at low specific energy input (SEI ∼ 0.5 eV/molecule), it is best to quench at the plasma end, while for high-SEI plasmas (SEI ∼ 4 eV/molecule), quenching at maximum conversion is better. For low-SEI plasmas, quenching can even increase the conversion beyond the dissociation in the plasma, known as superideal quenching. To better understand the effects of quenching at different plasma conditions, we study the dissociation and recombination rates, as well as the vibrational distribution functions (VDFs) of CO2, CO, and O2. When a high vibrational−translational (VT) nonequilibrium exists at the moment of quenching, the dissociation and recombination reaction rates both increase. Depending on the conversion degree at the moment of quenching, this can lead to a net increase or decrease of CO2 conversion. In general, however, and certainly for equilibrium plasmas at high temperature, quenching after the plasma helps prevent recombination reactions and clearly enhances the final CO2 conversion. We also investigate the effect of different quenching cooling rates on the CO2 conversion and energy efficiency. Finally, we compare plasma-based conversion to purely thermal conversion. For warm plasmas with typical temperatures of 3000−4000 K, the conversion is roughly thermal.

Abstract: We developed a microkinetic model to reveal the effects of plasma-generated radicals, intermediates, and vibrationally excited species on the catalytic hydrogenation of CO2 to CH3OH on a Cu(111) surface. As a benchmark, we first present the mechanisms of thermal catalytic CH3OH formation. Our model predicts that the reverse water-gas shift reaction followed by CO hydrogenation, together with the formate path, mainly contribute to CH3OH formation in thermal catalysis. Adding plasma-generated radicals and intermediates results in a higher CH3OH turnover frequency (TOF) by six to seven orders of magnitude, showing the potential of plasma-catalytic CO2 hydrogenation into CH3OH, in accordance with the literature. In addition, CO2 vibrational excitation further increases the CH3OH TOF, but the effect is limited due to relatively low vibrational temperatures under typical plasma catalysis conditions. The predicted increase in CH3OH formation by plasma catalysis is mainly attributed to the increased importance of the formate path. In addition, the conversion of plasma-generated CO to HCO* and subsequent HCOO* or H2CO* formation contribute to CH3OH formation. Both pathways bypass the HCOO* formation from CO2, which is the main bottleneck in the process. Hence, our model points toward the important role of CO, but also O, OH, and H radicals, as they influence the reactions that consume CO2 and CO. In addition, our model reveals that the H pressure should not be smaller than ca. half of the O pressure in the plasma as this would cause O* poisoning, which would result in very small product TOFs. Thus, plasma conditions should be targeted with a high CO and H content as this is favorable for CH3OH formation, while the O content should be minimized.

Abstract: We use microkinetic modeling to examine the potential of plasma-catalytic partial oxidation (POX) of CH4 as a promising new approach to produce oxygenates. We study how different plasma species affect POX of CH4 on the Pt(111) surface, and we discuss the associated kinetic and mechanistic changes. We discuss the effect of vibrationally excited CH4 and O2, as well as plasma-generated radicals and stable intermediates. Our results show that vibrational excitation enhances the turnover frequency (TOF) of catalytic CH4 dissociation and has good potential for improving the selectivities toward CH3OH, HCOOH, and C2 hydrocarbons. Nevertheless, when also considering plasma-generated radicals, we find that these species mainly govern the surface chemistry. Additionally, we find that plasma-generated radicals and stable intermediates enhance the TOFs of COx and oxygenates, increase the selectivity toward oxygenates, and make the formation of HCOOH more significant on Pt(111). We also briefly illustrate the potential impact of Eley−Rideal reactions that involve plasma-generated radicals. Finally, we reveal how various radicals affect the catalyst surface chemistry and we link this to the formation of different products. This allows us to make suggestions on how the plasma composition should be altered to improve the formation of desired products.

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: CsPbI3 is a promising perovskite material for photovoltaic applications in its photoactive perovskite or black phase. However, the material degrades to a photovoltaically inactive or yellow phase at room temperature. Various mitigation strategies are currently being developed to increase the lifetime of the black phase, many of which rely on inducing strains in the material that hinder the black-to-yellow phase transition. Physical insight into how these strategies exactly induce strain as well as knowledge of the spatial extent over which these strains impact the material is crucial to optimize these approaches but is still lacking. Herein, we combine machine learning potential-based molecular dynamics simulations with our in silico strain engineering approach to accurately quantify strained large-scale atomic structures on a nanosecond time scale. To this end, we first model the strain fields introduced by atomic substitutions as they form the most elementary strain sources. We demonstrate that the magnitude of the induced strain fields decays exponentially with the distance from the strain source, following a decay rate that is largely independent of the specific substitution. Second, we show that the total strain field induced by multiple strain sources can be predicted to an excellent approximation by summing the strain fields of each individual source. Finally, through a case study, we illustrate how this additive character allows us to explain how complex strain fields, induced by spatially extended strain sources, can be predicted by adequately combining the strain fields caused by local strain sources. Hence, the strain additivity proposed here can be adopted to further our insight into the complex strain behavior in perovskites and to design strain from the atomic level onward to enhance their sought-after phase stability.

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 development of catalysts with high intrinsic activity towards the oxygen evolution reaction (OER) plays a critical role in sustainable energy conversion and storage. Herein, we report on the development of efficient (photo)electrocatalysts based on functionalized MnO(2)systems. Specifically,beta-MnO(2)nanostructures grown by plasma enhanced-chemical vapor deposition on fluorine-doped tin oxide (FTO) or Ni foams were decorated with Co(3)O(4)or Fe(2)O(3)nanoparticles by radio frequency sputtering. Upon functionalization, FTO-supported materials yielded a performance increase with respect to bare MnO2, with current densities at 1.65 Vvs. the reversible hydrogen electrode (RHE) up to 3.0 and 3.5 mA/cm(2)in the dark and under simulated sunlight, respectively. On the other hand, the use of highly porous and conductive Ni foam substrates enabled to maximize cooperative interfacial effects between catalyst components. The best performing Fe2O3/MnO(2)system provided a current density of 17.9 mA/cm(2)at 1.65 Vvs. RHE, an overpotential as low as 390 mV, and a Tafel slope of 69 mV/decade under dark conditions, comparing favorably with IrO(2)and RuO(2)benchmarks. Overall, the control of beta-MnO2/substrate interactions and the simultaneous surface property engineering pave the way to an efficient energy generation from abundant natural resources.

Abstract: It remains a real challenge to control the selectivity of the electrocatalytic CO2 reduction (eCO(2)R) reaction to valuable chemicals and fuels. Most of the electrocatalysts are made of non-renewable metal resources, which hampers their large-scale implementation. Here, we report the preparation of bimetallic copper-lead (CuPb) electrocatalysts from industrial metallurgical waste. The metal ions were extracted from the metallurgical waste through simple chemical treatment with ammonium chloride, and CuxPby electrocatalysts with tunable compositions were fabricated through electrodeposition at varying cathodic potentials. X-ray spectroscopy techniques showed that the pristine electrocatalysts consist of Cu-0, Cu1+ and Pb2+ domains, and no evidence for alloy formation was found. We found a volcano-shape relationship between eCO(2)R selectivity toward two electron products, such as CO, and the elemental ratio of Cu and Pb. A maximum Faradaic efficiency towards CO was found for Cu9.00Pb1.00, which was four times higher than that of pure Cu, under the same electrocatalytic conditions. In situ Raman spectroscopy revealed that the optimal amount of Pb effectively improved the reducibility of the pristine Cu1+ and Pb2+ domains to metallic Cu and Pb, which boosted the selectivity towards CO by synergistic effects. This work provides a framework of thinking to design and tune the selectivity of bimetallic electrocatalysts for CO2 reduction through valorization of metallurgical waste.