“Identification of a unique pyridinic FeN4Cx electrocatalyst for N₂, reduction : tailoring the coordination and carbon topologies”. Nematollahi P, Neyts EC, Journal Of Physical Chemistry C 126, 14460 (2022). http://doi.org/10.1021/ACS.JPCC.2C03577
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
Keywords: A1 Journal article; Engineering sciences. Technology; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 3.7
DOI: 10.1021/ACS.JPCC.2C03577
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“Additivity of Atomic Strain Fields as a Tool to Strain-Engineering Phase-Stabilized CsPbI3Perovskites”. Teunissen JL, Braeckevelt T, Skvortsova I, Guo J, Pradhan B, Debroye E, Roeffaers MBJ, Hofkens J, Van Aert S, Bals S, Rogge SMJ, Van Speybroeck V, The Journal of Physical Chemistry C 127, 23400 (2023). http://doi.org/10.1021/acs.jpcc.3c05770
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.
Keywords: A1 Journal Article; Electron Microscopy for Materials Science (EMAT) ;
Impact Factor: 3.7
DOI: 10.1021/acs.jpcc.3c05770
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“Conformation-Dependent Monolayer and Bilayer Structures of an Alkylated TTF Derivative Revealed using STM and Molecular Modeling”. Delfino CL, Hao Y, Martin C, Minoia A, Gopi E, Mali KS, Van der Auweraer M, Geerts YH, Van Aert S, Lazzaroni R, De Feyter S, The Journal of Physical Chemistry C 127, 23023 (2023). http://doi.org/10.1021/acs.jpcc.3c04913
Abstract: In this study, the multi-layer self-assembled molecular network formation of an alkylated tetrathiafulvalene compound is studied at the liquid-solid interface between 1-phenyloctane and graphite. A combined theoretical/experimental approach associating force-field and quantum-chemical calculations with scanning tunnelling microscopy is used to determine the two-dimensional self-assembly beyond the monolayer, but also to further the understanding of the molecular adsorption conformation and its impact on the molecular packing within the assemblies at the monolayer and bilayer level.
Keywords: A1 Journal Article; Electron Microscopy for Materials Science (EMAT) ;
Impact Factor: 3.7
DOI: 10.1021/acs.jpcc.3c04913
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“Improving Molecule–Metal Surface Reaction Networks Using the Meta-Generalized Gradient Approximation: CO2Hydrogenation”. Cai Y, Michiels R, De Luca F, Neyts E, Tu X, Bogaerts A, Gerrits N, The Journal of Physical Chemistry C 128, 8611 (2024). http://doi.org/10.1021/acs.jpcc.4c01110
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.
Keywords: A1 Journal Article; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 3.7
DOI: 10.1021/acs.jpcc.4c01110
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“Plasma Catalysis Modeling: How Ideal Is Atomic Hydrogen for Eley–Rideal?”.Michiels R, Gerrits N, Neyts E, Bogaerts A, The Journal of Physical Chemistry C 128, 11196 (2024). http://doi.org/10.1021/acs.jpcc.4c02193
Abstract: Plasma catalysis is an emerging technology, but a lot of questions about the underlying surface mechanisms remain unanswered. One of these questions is how important Eley−Rideal (ER) reactions are, next to Langmuir−Hinshelwood reactions. Most plasma catalysis kinetic models predict ER reactions to be important and sometimes even vital for the surface chemistry. In this work, we take a critical look at how ER reactions involving H radicals are incorporated in kinetic models describing CO2 hydrogenation and NH3 synthesis. To this end, we construct potential energy surface (PES) intersections, similar to elbow plots constructed for dissociative chemisorption. The results of the PES intersections are in agreement with ab initio molecular dynamics (AIMD) findings in literature while being computationally much cheaper. We find that, for the reactions studied here, adsorption is more probable than a reaction via the hot atom (HA) mechanism, which in turn is more probable than a reaction via the ER mechanism. We also conclude that kinetic models of plasma-catalytic systems tend to overestimate the importance if ER reactions. Furthermore, as opposed to what is often assumed in kinetic models, the choice of catalyst will influence the ER reaction probability. Overall, the description of ER reactions is too much “ideal” in models. Based on our indings, we make a number of recommendations on how to incorporate ER reactions in kinetic models to avoid overestimation of their importance.
Keywords: A1 Journal Article; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 3.7
DOI: 10.1021/acs.jpcc.4c02193
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