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“Direct observation of realistic-temperature fuel combustion mechanisms in atomistic simulations”. Bal KM, Neyts EC, Chemical science 7, 5280 (2016). http://doi.org/10.1039/C6SC00498A
Abstract: Atomistic simulations can in principle provide an unbiased description of all mechanisms, intermediates, and products of complex chemical processes. However, due to the severe time scale limitation of conventional simulation techniques, unrealistically high simulation temperatures are usually applied, which are a poor approximation of most practically relevant low-temperature applications. In this work, we demonstrate the direct observation at the atomic scale of the pyrolysis and oxidation of n-dodecane at temperatures as low as 700 K through the use of a novel simulation technique, collective variable-driven hyperdynamics (CVHD). A simulated timescale of up to 39 seconds is reached. Product compositions and dominant mechanisms are found to be strongly temperature-dependent, and are consistent with experiments and kinetic models. These simulations provide a first atomic-level look at the full dynamics of the complicated fuel combustion process at industrially relevant temperatures and time scales, unattainable by conventional molecular dynamics simulations.
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 8.668
Times cited: 22
DOI: 10.1039/C6SC00498A
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“Merging Metadynamics into Hyperdynamics: Accelerated Molecular Simulations Reaching Time Scales from Microseconds to Seconds”. Bal KM, Neyts EC, Journal of chemical theory and computation 11, 4545 (2015). http://doi.org/10.1021/acs.jctc.5b00597
Abstract: The hyperdynamics method is a powerful tool to simulate slow processes at the atomic level. However, the construction of an optimal hyperdynamics potential is a task that is far from trivial. Here, we propose a generally applicable implementation of the hyperdynamics algorithm, borrowing two concepts from metadynamics. First, the use of a collective variable (CV) to represent the accelerated dynamics gives the method a very large flexibility and simplicity. Second, a metadynamics procedure can be used to construct a suitable history-dependent bias potential on-the-fly, effectively turning the algorithm into a self-learning accelerated molecular dynamics method. This collective variable-driven hyperdynamics (CVHD) method has a modular design: both the local system properties on which the bias is based, as well as the characteristics of the biasing method itself, can be chosen to match the needs of the considered system. As a result, system-specific details are abstracted from the biasing algorithm itself, making it extremely versatile and transparent. The method is tested on three model systems: diffusion on the Cu(001) surface and nickel-catalyzed methane decomposition, as examples of reactive processes with a bond-length-based CV, and the folding of a long polymer-like chain, using a set of dihedral angles as a CV. Boost factors up to 109, corresponding to a time scale of seconds, could be obtained while still accurately reproducing correct dynamics.
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 5.245
Times cited: 41
DOI: 10.1021/acs.jctc.5b00597
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“Overcoming Old Scaling Relations and Establishing New Correlations in Catalytic Surface Chemistry: Combined Effect of Charging and Doping”. Bal KM, Neyts EC, The journal of physical chemistry: C : nanomaterials and interfaces 123, 6141 (2019). http://doi.org/10.1021/acs.jpcc.9b01216
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.
Keywords: A1 Journal article; Engineering sciences. Technology; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 4.536
Times cited: 5
DOI: 10.1021/acs.jpcc.9b01216
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“Extending and validating bubble nucleation rate predictions in a Lennard-Jones fluid with enhanced sampling methods and transition state theory”. Bal KM, Neyts EC, Journal Of Chemical Physics 157, 184113 (2022). http://doi.org/10.1063/5.0120136
Abstract: We calculate bubble nucleation rates in a Lennard-Jones fluid through explicit molecular dynamics simulations. Our approach-based on a recent free energy method (dubbed reweighted Jarzynski sampling), transition state theory, and a simple recrossing correction-allows us to probe a fairly wide range of rates in several superheated and cavitation regimes in a consistent manner. Rate predictions from this approach bridge disparate independent literature studies on the same model system. As such, we find that rate predictions based on classical nucleation theory, direct brute force molecular dynamics simulations, and seeding are consistent with our approach and one another. Published rates derived from forward flux sampling simulations are, however, found to be outliers. This study serves two purposes: First, we validate the reliability of common modeling techniques and extrapolation approaches on a paradigmatic problem in materials science and chemical physics. Second, we further test our highly generic recipe for rate calculations, and establish its applicability to nucleation processes.
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 4.4
DOI: 10.1063/5.0120136
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“Modelling molecular adsorption on charged or polarized surfaces: a critical flaw in common approaches”. Bal KM, Neyts EC, Physical chemistry, chemical physics 20, 8456 (2018). http://doi.org/10.1039/C7CP08209F
Abstract: A number of recent computational material design studies based on density functional theory (DFT) calculations have put forward a new class of materials with electrically switchable chemical characteristics that can be exploited in the development of tunable gas storage and electrocatalytic applications. We find systematic flaws in almost every computational study of gas adsorption on polarized or charged surfaces, stemming from an improper and unreproducible treatment of periodicity, leading to very large errors of up to 3 eV in some cases. Two simple corrective procedures that lead to consistent results are proposed, constituting a crucial course correction to the research in the field.
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 4.123
Times cited: 8
DOI: 10.1039/C7CP08209F
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“On the time scale associated with Monte Carlo simulations”. Bal KM, Neyts EC, The journal of chemical physics 141, 204104 (2014). http://doi.org/10.1063/1.4902136
Abstract: Uniform-acceptance force-bias Monte Carlo (fbMC) methods have been shown to be a powerful technique to access longer timescales in atomistic simulations allowing, for example, phase transitions and growth. Recently, a new fbMC method, the time-stamped force-bias Monte Carlo (tfMC) method, was derived with inclusion of an estimated effective timescale; this timescale, however, does not seem able to explain some of the successes the method. In this contribution, we therefore explicitly quantify the effective timescale tfMC is able to access for a variety of systems, namely a simple single-particle, one-dimensional model system, the Lennard-Jones liquid, an adatom on the Cu(100) surface, a silicon crystal with point defects and a highly defected graphene sheet, in order to gain new insights into the mechanisms by which tfMC operates. It is found that considerable boosts, up to three orders of magnitude compared to molecular dynamics, can be achieved for solid state systems by lowering of the apparent activation barrier of occurring processes, while not requiring any system-specific input or modifications of the method. We furthermore address the pitfalls of using the method as a replacement or complement of molecular dynamics simulations, its ability to explicitly describe correct dynamics and reaction mechanisms, and the association of timescales to MC simulations in general.
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 2.965
Times cited: 26
DOI: 10.1063/1.4902136
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Bal KM, Neyts EC (2021) Quantifying the impact of vibrational nonequilibrium in plasma catalysis: insights from a molecular dynamics model of dissociative chemisorption. 394004
Abstract: The rate, selectivity and efficiency of plasma-based conversion processes is strongly affected by nonequilibrium phenomena. High concentrations of vibrationally excited molecules are such a plasma-induced effect. It is frequently assumed that vibrationally excited molecules are important in plasma catalysis because their presence lowers the apparent activation energy of dissociative chemisorption reactions and thus increases the conversion rate. A detailed atomic-level understanding of vibrationally stimulated catalytic reactions in the context of plasma catalysis is however lacking. Here, we couple a recently developed statistical model of a plasma-induced vibrational nonequilibrium to molecular dynamics simulations, enhanced sampling methods, and machine learning techniques. We quantify the impact of a vibrational nonequilibrium on the dissociative chemisorption barrier of H2 and CH4 on nickel catalysts over a wide range of vibrational temperatures. We investigate the effect of surface structure and compare the role of different vibrational modes of methane in the dissociation process. For low vibrational temperatures, very high vibrational efficacies are found, and energy in bend vibrations appears to dominate the dissociation of methane. The relative impact of vibrational nonequilibrium is much higher on terrace sites than on surface steps. We then show how our simulations can help to interpret recent experimental results, and suggest new paths to a better understanding of plasma catalysis.
Keywords: A1 Journal Article;plasma catalysis; vibrational nonequilibrium; dissociative chemisorption; free energy barriers; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 2.588
DOI: 10.1088/1361-6463/ac113a
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