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: The recent advantages of the fabrication of artificial nanochannels enabled new research on the molecular transport, permeance, and selectivity of various gases and molecules. However, the physisorption/chemisorption of the unwanted molecules (usually hydrocarbons) inside nanochannels results in the alteration of the functionality of the nanochannels. We investigated contamination due to hydrocarbon molecules, nanochannels made of graphene, hexagonal boron nitride, BC2N, and molybdenum disulfide using molecular dynamics simulations. We found that for a certain size of nanochannel (i.e., h = 0.7 nm), as a result of the anomalous hydrophilic nature of nanochannels made of graphene, the hydrocarbons are fully adsorbed in the nanochannel, giving rise to full uptake. An increasing temperature plays an important role in unclogging, while pressure does not have a significant role. The results of our pioneering work contribute to a better understanding and highlight the important factors in alleviating the contamination and unclogging of nanochannels, which are in good agreement with the results of recent experiments.

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: Molecular dynamics simulations are essential for a better understanding of dissociative chemisorption on metal surfaces, which is often the rate-controlling step in heterogeneous and plasma catalysis. The workhorse quasi-classical trajectory approach ubiquitous in molecular dynamics is able to accurately predict reactivity only for high translational and low vibrational energies. In contrast, catalytically relevant conditions generally involve low translational and elevated vibrational energies. Existing quantum dynamics approaches are intractable or approximate as a result of the large number of degrees of freedom present in molecule−metal surface reactions. Here, we extend a ring polymer molecular dynamics approach to fully include, for the first time, the degrees of freedom of a moving metal surface. With this approach, experimental sticking probabilities for the dissociative chemisorption of methane on Pt(111) are reproduced for a large range of translational and vibrational energies by including nuclear quantum effects and employing full-dimensional simulations.

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: Although the heterogeneity of pyrolyzed Fe???N???C materials is known and has been reported previously, the atomic structure of the active sites and their detailed reaction mechanisms are still unknown. Here, we identified two pyridinic Fe???N4-like centers with different local C coordinates, i.e., FeN4C8 and FeN4C10, and studied their electrocatalytic activity for the nitrogen reduction reaction (NRR) based on density functional theory (DFT) calculations. We also discovered the influence of the adsorption of NH2 as a functional ligand on catalyst performance on the NRR. We confirmed that the NRR selectivity of the studied catalysts is essentially governed either by the local C coordination or by the dynamic structure associated with the FeII/FeIII. Our investigations indicate that the proposed traditional pyridinic FeN4C10 has higher catalytic activity and selectivity for the NRR than the robust FeN4C8 catalyst, while it may have outstanding activity for promoting other (electro)catalytic reactions. <comment>Superscript/Subscript Available</comment

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: Electrenes, an atomically thin form of layered electrides, are very recent members of the 2D materials family. In this work, we employed first principle calculations to determine stable, exfoliatable, and application-promising 2D electrene materials among possible M2X compounds, where M is a group II-A metal and X is a nonmetal element (C, N, P, As, and Sb). The promise of stable electrene compounds for battery applications is assessed via their exfoliation energy, adsorption properties, and migration energy barriers toward relevant Li, Na, K, and Ca atoms. Our calculations revealed five new stable electrene candidates in addition to previously known Ca2N and Sr2N. Among these seven dynamically stable electrenes, Ba2As, Ba2P, Ba2Sb, Ca2N, Sr2N, and Sr2P are found to be very promising for either K or Na ion batteries due to their extremely low migration energy barriers (5-16 meV), which roughly demonstrates 105 times higher mobility than graphene and two to four times higher mobility than other promising 2D materials such as MXene (Mo2C).

Abstract: The quantum electrostatic heterostructure (QEH) model allows for efficient computation of the dielectric screening properties of layered van der Waals (vdW)-bonded heterostructures in terms of the dielectric functions of the individual two-dimensional (2D) layers. Here, we extend the QEH model by including (1) contributions to the dielectric function from infrared active phonons in the 2D layers, (2) screening from homogeneous bulk substrates, and (3) intraband screening from free carriers in doped 2D semiconductor layers. We demonstrate the potential of the extended QEH model by calculating the dispersion of coupled phonons in multilayer stacks of hexagonal boron-nitride (hBN), the strong hybridization of plasmons and optical phonons in graphene/hBN heterostructures, the effect of substrate screening on the exciton series of monolayer MoS2, and the properties of hyperbolic plasmons in a doped phosphorene sheet. The new QEH code is distributed as a Python package with a simple command line interface and a comprehensive library of dielectric building blocks for the most common 2D materials, providing an efficient open platform for dielectric modeling of realistic vdW heterostructures.

Abstract: We evaluate the importance of quantum effects on the sticking of H2 on Al(110) for conditions that are close to those of molecular beam experiments that have been done on this system. Calculations with the quasi-classical trajectory (QCT) method and with quantum dynamics (QD) are performed using a model in which only motion in the six molecular degrees of freedom is allowed. The potential energy surface used has a minimum barrier height close to the value recently obtained with the quantum Monte Carlo method. Monte Carlo averaging over the initial rovibrational states allowed the QD calculations to be done with an order of magnitude smaller computational expense. The sticking probability curve computed with QD is shifted to lower energies relative to the QCT curve by 0.21 to 0.05 kcal/mol, with the highest shift obtained for the lowest incidence energy. Quantum effects are therefore expected to play a small role in calculations that would evaluate the accuracy of electronic structure methods for determining the minimum barrier height to dissociative chemisorption for H2 + Al(110) on the basis of the standard procedure for comparing results of theory with molecular beam experiments.