Abstract: We introduce a simple enhanced sampling approach for the calculation of free energy differences and barriers along a one-dimensional reaction coordinate. First, a small number of short nonequilibrium simulations are carried out along the reaction coordinate, and the Jarzynski equality is used to learn an approximate free energy surface from the nonequilibrium work distribution. This free energy estimate is represented in a compact form as an artificial neural network and used as an external bias potential to accelerate rare events in a subsequent molecular dynamics simulation. The final free energy estimate is then obtained by reweighting the equilibrium probability distribution of the reaction coordinate sampled under the influence of the external bias. We apply our reweighted Jarzynski sampling recipe to four processes of varying scales and complexities.spanning chemical reaction in the gas phase, pair association in solution, and droplet nucleation in supersaturated vapor. In all cases, we find reweighted Jarzynski sampling to be a very efficient strategy, resulting in rapid convergence of the free energy to high precision.

Abstract: The evaluation of nucleation rates from molecular dynamics trajectories is hampered by the slow nucleation time scale and impact of finite size effects. Here, we show that accurate nucleation rates can be obtained in a very general fashion relying only on the free energy barrier, transition state theory, and a simple dynamical correction for diffusive recrossing. In this setup, the time scale problem is overcome by using enhanced sampling methods, in casu metadynamics, whereas the impact of finite size effects can be naturally circumvented by reconstructing the free energy surface from an appropriate ensemble. Approximations from classical nucleation theory are avoided. We demonstrate the accuracy of the approach by calculating macroscopic rates of droplet nucleation from argon vapor, spanning 16 orders of magnitude and in excellent agreement with literature results, all from simulations of very small (512 atom) systems.

Abstract: While spectroscopic data on small hydrocarbons in interstellar media in combination with crossed molecular beam (CMB) experiments have provided a wealth of information on astrochemically relevant species, much of the underlying mechanistic pathways of their formation remain elusive. Therefore, in this work, the chemical reaction mechanisms of C(³P_J) + C₆H₆and C⁺(²P) + C₆H₆systems using the quantum mechanical molecular dynamics (QMMD) technique at the PBE0-D3(BJ) level of theory is investigated, mimicking a CMB experiment. Both the dynamics of the reactions as well as the electronic structure for the purpose of the reaction network are evaluated. The method is validated for the first reaction by comparison to the available experimental data. The reaction scheme for the C(³P_J) + C₆H₆system covers the literature data,<italic>e.g.</italic>the major products are the 1,2-didehydrocycloheptatrienyl radical (C₇H₅) and benzocyclopropenyl radical (C₆H₅–CH), and it reveals the existence of less common pathways for the first time. The chemistry of the C⁺(²P_J) + C₆H₆system is found to be much richer, and we have found that this is because of more exothermic reactions in this system in comparison to those in the C(³P_J) + C₆H₆system. Moreover, using the QMMD simulation, a number of reaction paths have been revealed that produce three distinct classes of reaction products with different ring sizes. All in all, at all the collision energies and orientations, the major product is the heptagon molecular ion for the ionic system. It is also revealed that the collision orientation has a dominant effect on the reaction products in both systems, while the collision energy mostly affects the charged system. These simulations both prove the applicability of this approach to simulate crossed molecular beams, and provide fundamental information on reactions relevant for the interstellar medium.

Abstract: Atomistic simulation methods for the quantification of free energies are in wide use. These methods operate by sampling the probability density of a system along a small set of suitable collective variables (CVs), which is, in turn, expressed in the form of a free energy surface (FES). This definition of the FES can capture the relative stability of metastable states but not that of the transition state because the barrier height is not invariant to the choice of CVs. Free energy barriers therefore cannot be consistently computed from the FES. Here, we present a simple approach to calculate the gauge correction necessary to eliminate this inconsistency. Using our procedure, the standard FES as well as its gauge-corrected counterpart can be obtained by reweighing the same simulated trajectory at little additional cost. We apply the method to a number of systems—a particle solvated in a Lennard-Jones fluid, a Diels–Alder reaction, and crystallization of liquid sodium—to demonstrate its ability to produce consistent free energy barriers that correctly capture the kinetics of chemical or physical transformations, and discuss the additional demands it puts on the chosen CVs. Because the FES can be converged at relatively short (sub-ns) time scales, a free energy-based description of reaction kinetics is a particularly attractive option to study chemical processes at more expensive quantum mechanical levels of theory.

Abstract: The limitation in time and length scale is a major issue of molecular dynamics (MD) simulation. Although several methods have been developed to extend the MD time scale, their performance usually deteriorates with increasing system size. Therefore, an acceleration method which is applicable to large systems is required to bridge the gap between the MD simulations and target phenomena. In this study, an accelerated MD method for large system is developed based on the collective variable-driven hyperdynamics (CVHD) method [K.M. Bal and E.C. Neyts, 2015]. The key idea is to run CVHD in parallel with rate control and accelerate multiple possible events simultaneously. Using this novel method, carbon diffusion in bcc-iron bicrystal with grain boundary is examined as an application for practical materials. Carbon atoms reaching at the grain boundary are trapped whereas carbon atoms in the bulk region diffuse randomly, and both dynamic regimes can be simultaneously accelerated with the parallel CVHD technique.

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: In order to optimize the plasma-synthesis and modification process of carbon nanomaterials for applications such as nanoelectronics and energy storage, a deeper understanding of fundamental hydrogengraphite/graphene interactions is required. Atomistic simulations by Molecular Dynamics have proven to be indispensable to illuminate these phenomena. However, severe time-scale limitations restrict them to very fast processes such as reflection, while slow thermal processes such as surface diffusion and molecular desorption are commonly inaccessible. In this work, we could however reach these thermal processes for the first time at time-scales and surface temperatures (1000 K) similar to high-flux plasma exposure experiments during the simulation of multilayer graphene etching by 5 eV H ions. This was achieved by applying the Collective Variable-Driven Hyperdynamics biasing technique, which extended the inter-impact time over a range of six orders of magnitude, down to a more realistic ion-flux of 1023m
2s
1. The results show that this not only causes a strong shift from predominant ion-to thermally induced interactions, but also significantly affects the hydrogen uptake and surface evolution. This study thus elucidates H ion-graphite/graphene interaction mechanisms and stresses the importance of including long time-scales in atomistic simulations at high surface temperatures to understand the dynamics of the ion-surface system.

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.

Abstract: The catalytic oxidative dehydrogenation of hydrocarbons is an industrially important process, in which selectivity is a key issue. We here investigate the conversion of methanol to formaldehyde on a vanadia surface employing long timescale simulations, reaching a time scale of seconds. In particular, we compare the thermal process to the case where an additional external electric field is applied, as would be the case in a direct plasma-catalysis setup. We find that the electric field influences the retention time of the molecules at the catalyst surface. These simulations provide an atomic scale insight in the thermal catalytic oxidative dehydrogenation process, and in how an external electric field may affect this process.

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.

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.

Abstract: Uniform acceptance force biased Monte Carlo (UFMC) simulations have previously been shown to be a powerful tool to simulate atomic scale processes, enabling one to follow the dynamical path during the simulation. In this contribution, we present a simple proof to demonstrate that this uniform acceptance still complies with the condition of detailed balance, on the condition that the characteristic parameter lambda = 1/2 and that the maximum allowed step size is chosen to be sufficiently small. Furthermore, the relation to Metropolis Monte Carlo (MMC) is also established, and it is shown that UFMC reduces to MMC by choosing the characteristic parameter lambda = 0 [Rao, M. et al. Mol. Phys. 1979, 37, 1773]. Finally, a simple example compares the UFMC and MMC methods.