Search

Path sampling allows the study of rare events like chemical reactions, nucleation and protein folding via a Monte Carlo (MC) exploration in path space. Instead of configuration points, this method samples short molecular dynamics (MD) trajectories with specific start- and end-conditions. As in configuration MC, its efficiency highly depends on the types of MC moves. Since the last two decades, the central MC move for path sampling has been the so-called shooting move in which a perturbed phase point of the old path is propagated backward and forward in time to generate a new path. Recently, we proposed the subtrajectory moves, stone-skipping (SS) and web-throwing (WT), that are demonstrably more efficient. However, the one-step crossing requirement makes them somewhat more difficult to implement in combination with external MD programs or when the order parameter determination is expensive. In this article, we present strategies to address the issue. The most generic solution is a new member of subtrajectory moves, wire fencing (WF), that is less thrifty than the SS, but more versatile. This makes it easier to link path sampling codes with external MD packages and provides a practical solution for cases where the calculation of the order parameter is expensive or not a simple function of geometry. We demonstrate the WF move in a double well Langevin model, a thin film breaking transition based on classical force fields, and a smaller ruthenium redox reaction at the ab initio level in which the order parameter explicitly depends on the electron density., 20 pages, 7 figures

Using molecular dynamics and path sampling techniques we investigated the effect of pressure and defects in the wurtzite to rock salt transition in cadmium selenide (CdSe). In the pressure range 2-10 GPa, rate constants of transition are in the order of 10

Coalescence is a critical phenomenon in separation and transport processes. An improved understanding of coalescence can enhance current models predicting emulsion stability and separation. We here report a combined experimental and simulation study to investigate the thin film prior to its rupture in a coalescence event. Optical tweezers measured the influence of ions and of surface-active agents on coalescence time and the forces acting between colliding oil droplets. Molecular simulation described the composition and constituent distribution of the thin films in systems comparable with the ones investigated via optical tweezers. We identify a potential relationship between the disruption of the electrical double layer and the formation of nanocrystals with the thin film breakage times and depletion forces.

Several simulations strategies have emerged to predict the permeability of solutes across membranes, which is important for many biological or industrial processes such as drug design. The widespread inhomogeneous solubility-diffusion (ISD) model is based on the Smoluchowski equation and describes permeation as purely diffusive. The counting method, which counts membrane transitions in a long molecular dynamics (MD) trajectory, is free of this diffusive assumption, but it lacks sufficient statistics when the permeation involves high free energy barriers. Metadynamics and variations thereof can overcome such barriers, but they generally lack the kinetics information. The milestoning framework has been used to describe permeation as a rare event, but it still relies on the Markovian assumption between the milestones. Replica Exchange Transition Interface Sampling (RETIS) has been shown to be an effective method for sampling rare events while simultaneously describing the kinetics without assumptions. This paper is the first permeation application of RETIS on an all-atom lipid bilayer consisting of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) to compute the entrance, escape and complete transition of molecular oxygen. Conventional MD was performed as a benchmark, and the MD rates from counting were converted to rate constants, giving good agreement with the RETIS values. Moreover, a correction factor was derived to convert the collective order parameter in RETIS, which was aimed to improve efficiency, to a single-particle order parameter. With this work, we showed how the exact kinetics of drug molecules permeation can be assessed with RETIS even if the permeation is truly a rare event or if the permeation is non-Markovian. RETIS will therefore be a valuable tool for future permeation studies.

It is quite challenging to learn complex mathematical algorithms used in molecular simulations, stressing the importance of using the most advantageous teaching methods. Ideally, individuals should learn at their pace and deal with tasks fitting their levels. Web‐based exercises make it possible to tailor every small step of the learning process, but this requires continuous monitoring of the learner. Differentiation based on the scores after the first round of common tasks can be demotivating for all students, as they will experience the initial set of tasks as being either too easy or too hard. We designed two tests, a self‐monitoring test and a rapid test (RT) in which the students explained equations relating to the current topic. The first test was aimed to see if the students were able to evaluate their own level of knowledge, whereas the RT was aimed to find a fast way to determine the level of the students. We compared both tests with traditional measures of knowledge and used a relatively new method, which was originally designed for the analysis of molecular simulation data, to interpret the results. Based on this analysis, we concluded that self‐evaluation, rather than an RT, is a valuable tool to automatically steer individual students through a tree of web‐based exercises to match their skill levels and interests. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Transition Path Sampling techniques are becoming common approaches in the study of rare events at the molecular scale. More efficient methods, such as transition interface sampling (TIS) and replica exchange transition interface sampling (RETIS), allow the investigation of rare events, e.g. chemical reactions and structural/morphological transitions, in a reasonable computational time. Here, we present pyretis, a Python library for performing TIS and RETIS simulations. pyretis directs molecular dynamics (MD) simulations in order to sample rare events with unbiased dynamics. pyretis is designed to be easily interfaced with any molecular simulation package and in the present release, it has been interfaced with GROMACS and CP2K, for classical and ab initio MD simulations, respectively. This is the pre-peer reviewed version of the following article: [PyRETIS: A well-done, medium-sized python library for rare events], which has been published in final form at [http://onlinelibrary.wiley.com/doi/10.1002/jcc.24900/abstract]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

The pH of liquid water is determined by the infrequent process in which water molecules split into short-lived hydroxide and hydronium ions. This reaction is difficult to probe experimentally and challenging to simulate. One of the open questions is whether the local water structure around a slightly stretched OH bond is actually initiating the eventual breakage of this bond or whether this event is driven by a global ordering that involves many water molecules far away from the reaction center. Here, we investigated the self-ionization of water at room temperature by rare-event ab initio molecular dynamics and obtained autoionization rates and activation energies in good agreement with experiments. Based on the analysis of thousands of molecular trajectories, we identified a couple of local order parameters and show that if a bond stretch occurs when all these parameters are around their ideal range, the chance for the first dissociation step (double-proton jump) increases from 10−7 to 0.4. Understanding these initiation triggers might ultimately allow the steering of chemical reactions. © 2018. This is the authors' accepted and refereed manuscript to the article. The final authenticated version is available online at: https://doi.org/10.1073/pnas.1714070115

Replacing methane with carbon dioxide in gas hydrates has been suggested as a way of harvesting methane, while at the same time storing carbon dioxide. Experimental evidence suggests that this process is facilitated if gas mixtures are used instead of pure carbon dioxide. We studied the free energy barriers for diffusion of methane, carbon dioxide, nitrogen, and hydrogen in the sI hydrate structure using molecular simulation techniques. Cage hops between neighboring cages were considered with and without a water vacancy and with a potential inclusion of an additional gas molecule in either the initial or final cage. Our results give little evidence for enhanced methane and carbon dioxide diffusion if nitrogen is present as well. However, the inclusion of hydrogen seems to have a substantial effect as it diffuses rapidly and can easily enter occupied cages, which reduces the barriers of diffusion for the gas molecules that co-occupy a cage with hydrogen. This is the authors’ accepted and refereed manuscript to the article. This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. The following article may be found at https://doi.org/10.1063/1.5026385

The minimal-basis iterative stockholder (MBIS) and restrained electrostatic potential (RESP) methods were applied to examine the effects of edges and of nitrogen and boron dopants on the atomic partial charges of neutral and charged graphene flakes. The results provided the parameters to fit a second-order atom-condensed Kohn–Sham DFT model (ACKS2), accurately determining the partial charges, the dipole and local electric fields in large graphene flakes with negligible cost. Our approach can lead to improvements of graphene force fields in charged conditions and guide the design of media for catalytic applications. Publisher embargo applies until July 19, 2019

Although previously developed mesoscopic DNA models have successfully reproduced thermodynamic denaturation data, recent studies show that these overestimate the rate of denaturation by orders of magnitude. Using adapted Peyrard–Bishop–Dauxois (PBD) models, we have calculated the denaturation rates of several DNA hairpins and made comparison with experimental data. We show that the addition of a barrier at the onsite potential of the PBD model gives a more accurate description of the unzipping dynamics of short DNA sequences. The new models provide a refined theoretical insight on the dynamical mechanisms of unzipping which can have implications for the understanding of transcription and replication processes. Still, this class of adapted PBD models seems to have a fundamental limitation which implies that it is not possible to get agreement with available experimental results on the dynamics of long DNA sequences and at the same time maintain the good agreement regarding its thermodynamics. The reason for this is that the denaturation rate of long DNA chains is not dramatically lowered by the additional barrier—as the base-pairs that open are more likely to remain open, facilitating the opening of the full DNA molecule. Some care has to be taken, since experimental techniques suitable to the study of denaturation rates of long sequences seem not to agree with other experimental data on short DNA sequences. Further research, both theoretical and experimental, is therefore needed to resolve these inconsistencies—which will be a starting point for new minimalistic models that are able to describe both thermodynamics and dynamics at a predictive level., Spanish Ministry of Economy, Industry and Competitiveness (BES-2013-065453, FIS2012-38827) and the University of Burgos and the Anders Jahre fund (Project 40105000)

In this work, interactions between carboxylate ions and calcium or sodium ions are investigated via density functional theory (DFT). Despite the ubiquitous presence of these interactions in natural and industrial chemical processes, few DFT studies on these systems exist in the literature. Special focus has been placed on determining the influence of the multibody interactions (with up to 4 carboxylates and one metal ion) on an effective pair-interaction potential, such as those used in molecular mechanics (MM). Specifically, DFT calculations are employed to quantify an effective pair-potential that implicitly includes multibody interactions to construct potential energy curves for carboxylate-metal ion pairs. The DFT calculated potential curves are compared to a widely used molecular mechanics force field (OPLS-AA). The calculations indicate that multibody effects do influence the energetic behavior of these ionic pairs and the extent of this influence is determined by a balance between (a) charge transfer from the carboxylate to the metal ions which stabilizes the complex and (b) repulsion between carboxylates, which destabilizes the complex. Additionally, the potential curves of the complexes with 1 and 2 carboxylates and one counterion have been examined to higher separation distance (20 Å) by the use of relaxed scan optimization and constrained density functional theory (CDFT). The results from the relaxed scan optimization indicate that near the equilibrium distance, the charge transfer between the metal ion and the deprotonated carboxylic acid group is significant and leads to non-negligible differences between the DFT and MM potential curves, especially for calcium. However, at longer separation distances the MM calculated interaction potential functions converge to those calculated with CDFT, effectively indicating the approximate domain of the separation distance coordinate where charge transfer between the ions is occurring.

The interaction between a carboxylate anion (deprotonated propanoic acid) and the divalent Mg(2+), Ca(2+), Sr(2+), Ba(2+) metal ions is studied via ab initio molecular dynamics. The main focus of the study is the selectivity of the carboxylate-metal ion interaction in aqueous solution. The interaction is modeled by explicitly accounting for the solvent molecules on a DFT level. The hydration energies of the metal ions along with their diffusion and mobility coefficients are determined and a trend correlated with their ionic radius is found. Subsequently, a series of 16 constrained molecular dynamics simulations for every ion is performed, and the interaction free energy is obtained from thermodynamic integration of the forces between the metal ion and the carboxylate ion. The results indicate that the magnesium ion interacts most strongly with the carboxylate, followed by calcium, strontium, and barium. Because the interaction free energy is not enough to explain the selectivity of the reaction observed experimentally, more detailed analysis is performed on the simulation trajectories to understand the steric changes in the reaction complex during dissociation. The solvent dynamics appear to play an important role during the dissociation of the complex and also in the observed selectivity behavior of the divalent ions.

We develop a new method combining replica exchange transition interface sampling with two distinct potential energy surfaces. The method can be used to combine different levels of theory in a simulation of a molecular process (e.g. a chemical reaction) and it can serve as a dynamical version of QM-MM, connecting classical dynamics with Ab Initio dynamics in the time domain. This new method, which we coin QuanTIS, could be applied to use accurate but expensive density functional theory based molecular dynamics for the breaking and making of chemical bonds, while the diffusion of reactants in the solvent are treated with classical force fields. We exemplify the method by applying it to two simple model systems (an ion dissociation reaction and a classical hydrogen model) and we discuss a possible extension of the method in which classical force field parameters for chemical reactions can be optimized on the fly. ACS AuthorChoice - This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes.

Many relevant processes in chemistry, physics, and biology are rare events from a computational perspective as they take place beyond the accessible time scale of molecular dynamics (MD). Examples are chemical reactions, nucleation, and conformational changes of biomolecules. Path sampling is an approach to break this time scale limit via a Monte Carlo (MC) sampling of MD trajectories. Still, many trajectories are needed for accurately predicting rate constants. To improve the speed of convergence, we propose two new MC moves, stone skipping and web throwing. In these moves, trajectories are constructed via a sequence of subpaths obeying super-detailed balance. By a reweighting procedure, almost all paths can be accepted. Whereas the generation of a single trajectory becomes more expensive, the reduced correlation results in a significant speedup. For a study on DNA denaturation the increase was found to be a factor 12. © American Chemical Society 2017. This is the authors accepted and refereed manuscript to the article. Locked until 31.8.2018 due to copyright restrictions.

A replica exchange transition interface sampling (RETIS) study combined with Born-Oppenheimer molecular dynamics (BOMD) is used to investigate the dynamics, thermodynamics and mechanism of the early stages of the silicate condensation process. In this process, two silicate monomers, of which one anion species, form a negatively charged five-coordinated silicate dimer. In a second stage, this dimer can fall apart again, forming the original monomers, or release a water molecule into the solution. We studied the association and dissociation reaction in the gas phase, and the dissociation and water removal step in the aqueous phase. The results on the aqueous phase dissociation suggest two possible mechanisms. The breakage of the bond between the intermediate oxygen and the five-coordinated silicon is sometimes accompanied with a proton transfer. After the dissociation into silicate monomers, the anionic monomer is either the previously four-coordinated silicon or the previously five-coordinated silicon depending on whether the hydrogen transfer occurs or not. Our results show that the mechanism with proton transfer is highly predominant. The water removal simulations also show two possible mechanisms distinguished by the proton transfer reaction path. The proton transfer can either occur via a direct or via a water mediated reaction step. The calculations reveal that although both mechanisms contribute to the water removal process, the direct proton transfer is slightly favorable and occurs roughly in six out of ten occasions. This is the first time ever that the RETIS approach is applied in combination with Ab Initio molecular dynamics. In this study, we revealed some crucial mechanistic steps in the process of silica oligomerization which would not be possible to detect by any other method as they tend to disrupt the spontaneous dynamics of the system. © 2017. This is the authors' accepted and refereed manuscript to the article. The final authenticated version is available online at: http://dx.doi.org/10.1039/C7CP01268C

Nearly 20 years ago transition path sampling (TPS) emerged as an alternative method to free energy based approaches for the study of rare events such as nucleation, protein folding, chemical reactions, and phase transitions. TPS performs effectively Monte Carlo (MC) with relatively short molecular dynamics trajectories, with the advantage of not having to alter the actual potential energy surface nor the underlying physical dynamics. Although the TPS approach also introduced a methodology to compute reaction rates, this approach was for a long time considered theoretically attractive, providing the exact same results as extensively long molecular dynamics simulations, but still expensive for most relevant applications. With the increase of computer power and improvements in the algorithmic methodology, quantitative path sampling is finding applications in more and more areas of research. In particular, the transition interface sampling (TIS) and the replica exchange TIS (RETIS) algorithms have, in turns, improved the efficiency of quantitative path sampling significantly, while maintaining the exact nature of the approach. Also, open-source software packages are making these methods, for which implementation is not straightforward, now available for a wider group of users. In addition, a blooming development takes place regarding both applications and algorithmic refinements. Therefore, it is timely to explore the wide panorama of the new developments in this field. This is the aim of this article, which focuses on the most efficient exact path sampling approach, RETIS, as well as its recent applications, extensions and variations. Published by AIP Publishing. Locked until 31.10.2018 due to copyright restrictions. This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. The following article appeared in Applied Physics Letters and may be found at https://aip.scitation.org/doi/10.1063/1.4989844

We studied the adsorption of chiral mixtures of lactic acid in several zeolites. All zeolite systems showed either no selectivity or heteroselectivity in which the minority enantiomer is adsorbed by a higher fraction than its fraction in the reservoir. Analysis of the mechanism showed that none of the previously identified origins of enantioselective adsorption of scalemic mixtures apply to lactic acid. However, on the basis of the lack of any ordered distribution in the adsorbed phase, we postulate a new mechanism that is likely to be very generic for chiral adsorption processes that proceed via chaotic packing of the adsorbate molecules. The new mechanism can explain several characteristics of the adsorption data and hints at new prospective separation methods with a high potential for pharmaceutical applications.

We introduce an approach to analyze collective variables regarding their predictive power for a reaction. The method is based on already available path sampling data produced by for instance transition interface sampling or forward flux sampling which are path sampling methods used for efficient computation of reaction rates. By a search in collective variable space a measure of predic- tiveness can be optimized and, in addition, the number of collective variables can be reduced using projection operations which keep this measure invariant. The approach allows testing hypotheses on the reaction mechanism, but could in principle also be used to construct the phase space com- mittor surfaces without the need of additional trajectory sampling. The procedure is illustrated for a one-dimensional double well potential, a theoretical model for an ion-transfer reaction in which the solvent structure can lower the barrier, and an Ab Initio molecular dynamics study of water auto-ionization. The analysis technique enhances the quantitative interpretation of path sampling data which can provide clues on how chemical reactions can be steered in desired directions. © American Chemical Society 2016. This is the authors accepted and refereed manuscript to the article.

Brunauer–Emmett–Teller (BET) theory is a popular method to interpret nitrogen adsorption isotherms for determining the specific surface area. Besides the monolayer capacity n m , the BET equation depends on one single additional parameter C that is adjusted to fit the experimental adsorption curves. BET analysis is key in surface characterization and is widely applied even when the underlying assumptions are not strictly justified. For example, disregarding its weaker physical interpretation, the BET surface area is generally accepted as an important characterization of microporous materials. However, whereas the accuracy of the adsorption techniques has tremendously increased in recent years, experimentally derived BET values do not yet meet the same standards. The reason for this is due to some intrinsic ambiguities in its fitting procedure. In this letter, we propose a procedure that is uniquely defined, given a certain pressure range, and is independent of arbitrary experimental details such as the distribution of data points. It puts an equal weight on both monolayer and multilayer formation and gives an additional reproducible measure that is related to the inherent deviation from the BET behavior.

Hexagonally ordered mesoporous silica coined COK-12 was synthesized in a continuous process by combining streams of sodium silicate and citric acid/sodium citrate buffered solution of (ethylene oxide)(20)-(propylene oxide)(70)-(ethylene oxide)(20) triblock copolymer (Pluronic P123) from separate reservoirs. COK-12 precipitated spontaneously upon combining both streams at nearly neutral pH and ambient temperature. Stable intermediates of the COK-12 formation process could be prepared by limiting sodium silicate addition. Investigation of these intermediates using small-angle X-ray scattering revealed COK-12 formed via an assembly process departing from spherical uncharged core-shell P123-silica micelles. The sterical stabilization of these micelles decreased upon accumulation of silicate oligomers in their shell. Aggregation of the spherical micelles led to cylindrical micelles, which aligned and adopted the final hexagonal organization. This unprecedentedly fast formation of P6m ordered mesoporous silica was caused by two factors in the synthesis medium: the neutral pH favoring uncharged silicate oligomers and the high salt concentration promoting hydrophobic interactions with surfactant micelles leading to silica accumulation in the PEO shell. The easy continuous synthesis process is convenient for large-scale production. The platelet particle morphology with short and identical internal channels will be advantageous for many applications such as pore replication, nanotube or fiber growth, catalytic functionalization, drug delivery, film and sensor development, and in nano dyes as well as for investigation of pore diffusion phenomena.

The initial molecular steps of the acid-catalyzed silica sol-gel process departing from tetraethylorthosilicate (TEOS) were investigated by in situ Si-29 NMR and UV-Raman spectroscopy. The use of a substoichiometric H2O:TEOS molar ratio (r-value 0.2-1.2) slowed the silicate oligomerization reaction and allowed unraveling the initial steps of silica condensation. Molecular modeling confirmed Raman signal and Si-29 NMR shift assignment. A comprehensive listing of all Raman and Si-29 NMR assignments is provided, including unique Raman assignments of cyclosilicates and the linear tetramer. The combination of experiment and modeling allowed an analysis of the reaction kinetics. The derived kinetic model and the experimental observation both revealed that the H2O:TEOS molar ratio had a strong influence on the reaction kinetics but not on the reaction pathways. The multianalytical approach led to development of an oligomerization scheme. As dominant oligomerizations, chain growth, cyclodimerization, and branching were identified. Under the investigated conditions, chains did not grow longer than pentamer, and ring sizes were limited to 6-rings. Chains of 4 Si atoms and 4-rings were abundant species. Branched rings and chains were formed by attachment of dimers and trimers. Gelation proceeded from branched 4-rings and branched chains with limited hydroxyl functionalities.

In concentrated clear sol prepared from tetraethylorthosilicate, tetrapropylammonium hydroxide, and water suitable for crystallization of Silicalite-1 zeolite, the main part of the silica is present in nanoparticles. The nature of these nanoparticles and their evolution during the induction period and the stage of early crystal growth was investigated via dissolution experiments in the presence of excess TPAOH. The dissolution process was monitored in situ using static and dynamic light scattering (SLS/DLS) and synchrotron small-angle X-ray scattering (SAXS). The complete dissolution of an individual nanoparticle was observed to occur in one step. Dissolution transformed a nanoparticle into a cluster of silicate oligomers. Larger grown nanoparticles dissolved slower. Exponential dissolution rate constants scaled inversely proportional with the volume of the nanoparticle’s silica core. This experimentally observed dissolution behavior was modeled by assuming that a nanoparticle dissolved to oligomers via a...

Minority excluded: If mixtures of chiral compounds are adsorbed in Al-substituted MFI zeolite containing nonframework cations, a process occurs that ultimately might be used for enantioseparation. If one enantiomer is present in excess it will organize the nearby cations, which in turn influence all other cations through long-range interaction, such that all adsorption sites become effectively chiral. This suppresses the minority enantiomer.

Chiral amplification is a known phenomenon in crystallization. Recent atomistic simulations have shown that amplification can also occur in equilibrium processes when a mixtures of chiral molecules adsorb in metal-substituted zeolites that are not chiral by themselves. In this article we investigate how this process could be exploited for enantiopurification and separation in a pressure-swing adsorption process. For this purpose, we develop a mathematical model that reproduces the main features of the full-atom simulations and allows us to study the impact of several parameters on the enantioselectivity on a macroscopic scale. Besides numerical solutions of this model, we provide some analytic results which suggests that the enantioselective materials prohibit a phase transition as a function of temperature. Below a certain critical temperature, the enantiomeric content of the adsorbed phase becomes a discontinuous function of the enantiomeric gas content. This has the following consequences: (i) the adsorbed phase in racemic conditions becomes unstable, (ii) a sudden increase in efficiency of the purification process, and (iii) the possibility to not only purify but also fully separate chiral mixtures using a parallel batch process in which both lines use an input that is enriched with opposite enantiomer.

We devise an efficient Monte Carlo scheme to study the adsorption of a multicomponent gas in a nanoporous material. The configurational bias move is extended by a novel replica exchange procedure where the configurations of the different simulations describing one particular gas content are being swapped. For chiral mixtures, the efficiency can be further improved using the chiral inversion move. The method is demonstrated for an Ising-type model and a complicated realistic zeolite system.

Using computer simulations, we have studied the adsorption of racemic and scalemic mixtures of 4-ethyl-4-methyloctane molecules in aluminum-substituted MFI zeolites containing positively charged ions. Our results show that aluminum distribution affects the shape of the enantiopure adsorption isotherms, which is contrary to previously established results on linear alkanes. In addition, we examined the enantiospecific adsorption at maximum loading conditions. For enantiopure and racemic mixtures, the fraction of S- and R-enantiomers in the adsorbed phase is identical to that of the gas phase. However, when the external gas contains a scalemic mixture, the dominant enantiomeric fraction might either increase or decrease upon adsorption, depending on the aluminum distribution and on the type of cations. We provide a theoretical explanation for both types of adsorption characteristics. Our findings open perspectives for new approaches of enantioseparation that do not require a chiral adsorbent.

The transport of gas molecules in hydrates is presently poorly understood. In sII structured hydrates with hydrogen guests there is, for instance, a mismatch between experimental and computed values for diffusion constants. We provide an explanation for the experimentally observed diffusion rates, using DFT-based molecular dynamics simulations at 100 K. By considering the effect of cage occupancy, as well as the flexibility of the water lattice, we show that barriers for hydrogen diffusing between cages, can approach values as low as 5 kJ mol(-1), which is very close to experimental values.

Using rare event simulation techniques, we calculated DNA denaturation rate constants for a range of sequences and temperatures for the Peyrard-Bishop-Dauxois (PBD) model with two different parameter sets. We studied a larger variety of sequences compared to previous studies that only consider DNA homopolymers and DNA sequences containing an equal amount of weak AT- and strong GC-base pairs. Our results show that, contrary to previous findings, an even distribution of the strong GC-base pairs does not always result in the fastest possible denaturation. In addition, we applied an adaptation of the PBD model to study hairpin denaturation for which experimental data are available. This is the first quantitative study in which dynamical results from the mesoscopic PBD model have been compared with experiments. Our results show that present parameterized models, although giving good results regarding thermodynamic properties, overestimate denaturation rates by orders of magnitude. We believe that our dynamical approach is, therefore, an important tool for verifying DNA models and for developing next generation models that have higher predictive power than present ones. © 2015 AIP Publishing LLC.Published by AIP Publishing. This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. The following article appeared in Journal of Chemical Physics and may be found at http://dx.doi.org/10.1063/1.4922519

We introduce a path sampling method for the computation of rate constants for systems with a highly diffusive character. Based on the recently developed algorithm of transition interface sampling (TIS) this procedure increases the efficiency by sampling only parts of complete transition trajectories confined within a certain region. The algorithm assumes the loss of memory for highly diffusive progression along the reaction coordinate. We compare the new technique to the TIS method for a simple diatomic system and show that the computation time of the new method scales linearly, instead of quadraticaly, with the length of the diffusive barrier. The validity of the memory loss assumption is also discussed., 12 pages, including 8 figures, RevTeX4

We present a density-functional theory based molecular-dynamics study of the structural, dynamical, and electronic properties of liquid methanol under ambient conditions. The calculated radial distribution functions involving the oxygen and hydroxyl hydrogen show a pronounced hydrogen bonding and compare well with recent neutron diffraction data, except for an underestimate of the oxygen-oxygen correlation. We observe that, in line with infrared spectroscopic data, the hydroxyl stretching mode is significantly red-shifted in the liquid. A substantial enhancement of the dipole moment is accompanied by significant fluctuations due to thermal motion. Our results provide valuable data for improvement of empirical potentials., Comment: 14 pages, 4 figures, accepted for publication in Chemical Physics Letters

We studied the hydration of a single methanol molecule in aqueous solution by first-principle DFT-based molecular dynamics simulation. The calculations show that the local structural and short-time dynamical properties of the water molecules remain almost unchanged by the presence of the methanol, confirming the observation from recent experimental structural data for dilute solutions. We also see, in accordance with this experimental work, a distinct shell of water molecules that consists of about 15 molecules. We found no evidence for a strong tangential ordering of the water molecules in the first hydration shell., Comment: 5 pages, 3 figures, submitted to Chemical Physics Letters

We used molecular simulation techniques to analyze the enantioselective adsorption of chiral polar molecules in achiral zeolites. As a representative chiral molecule, CHClFBr was used in this study. We analyzed the adsorption of racemic and scalemic mixtures of these molecules into different zeolites topologies such as MFI and MEL, both structures with intersecting channels, and FER and TON, frames with nonintersecting channels. In contrast to previous findings on apolar molecules, we found that cations are not essential for imposing heteroselective adsorption, and homoselective adsorption was never observed. We derived the mechanism behind the selectivity, which turns out to be fundamentally different from that observed for apolar adsorbates. Our model is able to explain why apparently similar zeolite topologies can still have strong differences in their adsorption behavior.

A molecular dynamics algorithm in principal component space is presented. It is demonstrated that sampling can be improved without changing the ensemble by assigning masses to the principal components proportional to the inverse square root of the eigenvalues. The setup of the simulation requires no prior knowledge of the system; a short initial MD simulation to extract the eigenvectors and eigenvalues suffices. Independent measures indicated a 6–7 times faster sampling compared to a regular molecular dynamics simulation.

The dynamics of the DNA denaturation is studied using the Peyrard-Bishop-Dauxois model. The denaturation rate of double stranded polymers decreases exponentially as function of length below the denaturation temperature. Above Tc, the rate shows a minimum, but then increases as function of length. We also examine the influence of sequence and solvent friction. Molecules having the same number of weak and strong base-pairs can have significantly different opening rates depending on the order of base-pairs., Comment: 6 pages, 6 figures, to be published in Europhysics Letters

Colloidal silicalite-1 zeolite was crystallized from a concentrated clear sol prepared from tetraethylorthosilicate (TEOS) and aqueous tetrapropylammonium hydroxide (TPAOH) solution at 95 degrees C. The silicate speciation was monitored by using dynamic light scattering (DLS), synchrotron small-angle X-ray scattering (SAXS), and quantitative liquid-state (29)Si NMR spectroscopy. The silicon atoms were present in dissolved oligomers, two discrete nanoparticle populations approximately 2 and 6 nm in size, and crystals. On the basis of new insight into the evolution of the different nanoparticle populations and of the silicate connectivity in the nanoparticles, a refined crystallization mechanism was derived. Upon combining the reagents, different types of nanoparticles (ca. 2 nm) are formed. A fraction of these nanoparticles with the least condensed silicate structure does not participate in the crystallization process. After completion of the crystallization, they represent the residual silicon atoms. Nanoparticles with a more condensed silicate network grow until approximately 6 nm and evolve into building blocks for nucleation and growth of the silicalite-1 crystals. The silicate network connectivity of nanoparticles suitable for nucleation and growth increasingly resembles that of the final zeolite. This new insight into the two classes of nanoparticles will be useful to tune the syntheses of silicalite-1 for maximum yield.

Due to the time scale problem, rare events are not accessible by straight forward molecular dynamics. The presence of multiple reaction channels complicates the problem even further. The feasibility of the standard free energy based methods relies strongly on the success in finding a proper reaction coordinate. This can be very difficult task in high-dimensional complex systems and even more if several distinct reaction channels exist. Moreover, even if a proper reaction coordinate can be found, ergodic sampling will be a challenge. In this article, we discuss the recent advancements of path sampling methods to tackle this problem. We argue why the path sampling methods, via the transition interface sampling technique, is less sensitive to the choice of reaction coordinate. Moreover, we review a new algorithm, parallel path swapping, that can dramatically improve the ergodic sampling of trajectories for the multiple reaction channel systems., 7 pages, 4 figures. Article submitted for the proceedings of the Conference on Computational Physics, Brussels 2007

The transition interface sampling (TIS) technique allows to overcome large free energy barriers within reasonable simulation time, which is impossible for straightforward molecular dynamics. Still, the method does not impose an artificial driving force, but it surmounts the timescale problem by an importance sampling of true dynamical pathways. Recently, it was shown that the efficiency of TIS to calculate reaction rates is less sensitive to the choice of reaction coordinate than those of the standard free energy based techniques. This could be an important advantage in complex systems for which a good reaction coordinate is usually very difficult to find. We explain the principles of this method and discuss some of the promising applications related to zeolite formation., Comment: 9 pages, accepted for publication in Phys. Chem. Chem. Phys. for the special issue of the CECAM workshop: Computational aspects of building blocks, nucleation, and synthesis of porous materials Aug. 29 2006 to Aug. 31 2006

The efficiency of path sampling simulations can be improved considerably using the approach of path swapping. For this purpose, we have devised a new algorithmic procedure based on the transition interface sampling technique. In the same spirit of parallel tempering, paths between different ensembles are swapped, but the role of temperature is here played by the interface position. We have tested the method on the denaturation transition of DNA using the Peyrard-Bishop-Dauxois model. We find that the new algorithm gives a reduction of the computational cost by a factor 20., Comment: 5 pages, 3 figures

We studied silica dimerization reactions in the gas and aqueous phase by density functional theory (DFT) and reactive force fields based on two parameterizations of ReaxFF. For each method (both ReaxFF force fields and DFT), we performed constrained geometry optimizations, which were subsequently evaluated in single point energy calculations using the other two methods. Standard fitting procedures typically compare the force field energies and geometries with those from quantum mechanical data after a geometry optimization. The initial configurations for the force field optimization are usually the minimum energy structures of the ab initio database. Hence, the ab initio method dictates which structures are being examined and force field parameters are being adjusted in order to minimize the differences with the ab initio data. As a result, this approach will not exclude the possibility that the force field predicts stable geometries or low transition states which are realistically very high in energy and, therefore, never considered by the ab initio method. Our analysis reveals the existence of such unphysical geometries even at unreactive conditions where the distance between the reactants is large. To test the effect of these discrepancies, we launched molecular dynamics simulations using DFT and ReaxFF and observed spurious reactions for both ReaxFF force fields. Our results suggest that the standard procedures for parameter fitting need to be improved by a mutual comparative method.

It has been speculated that bubble formation of several base-pairs due to thermal fluctuations is indicatory for biological active sites. Recent evidence, based on experiments and molecular dynamics (MD) simulations using the Peyrard-Bishop-Dauxois model, seems to point in this direction. However, sufficiently large bubbles appear only seldom which makes an accurate calculation difficult even for minimal models. In this letter, we introduce a new method that is orders of magnitude faster than MD. Using this method we show that the present evidence is unsubstantiated., 4 pages, 3 figures, accepted for publication in physical review letters

We review two recently developed efficient methods for calculating rate constants of processes dominated by rare events in high-dimensional complex systems. The first is transition interface sampling (TIS), based on the measurement of effective fluxes through hypersurfaces in phase space. TIS improves efficiency with respect to standard transition path sampling (TPS) rate constant techniques, because it allows a variable path length and is less sensitive to recrossings. The second method is the partial path version of TIS. Developed for diffusive processes, it exploits the loss of long time correlation. We discuss the relation between the new techniques and the standard reactive flux methods in detail. Path sampling algorithms can suffer from ergodicity problems, and we introduce several new techniques to alleviate these problems, notably path swapping, stochastic configurational bias Monte Carlo shooting moves and order-parameter free path sampling. In addition, we give algorithms to calculate other interesting properties from path ensembles besides rate constants, such as activation energies and reaction mechanisms., 36 pages, 5 figures

We introduce a method to evaluate simultaneously the reaction rate constant and the free energy profile of a process in a complex environment. The method employs the partial path transition interface sampling technique we recently developed for the calculation of rate constants in diffusive systems. We illustrate the applicability of the technique by studying a simple dimer in a repulsive fluid, and show that the free energy can be obtained at no additional computational cost.

We briefly review simulation schemes for the investigation of rare transitions and we resume the recently introduced Transition Interface Sampling, a method in which the computation of rate constants is recast into the computation of fluxes through interfaces dividing the reactant and product state., 12 pages, 1 figure, contributed paper to the proceedings of NEXT 2003, Second Sardinian International Conference on News and Expectations in Thermostatistics, 21-28 Sep 2003, Cagliari (Italy)

We derive a novel efficient scheme to measure the rate constant of transitions between stable states separated by high free energy barriers in a complex environment within the framework of transition path sampling. The method is based on directly and simultaneously measuring the fluxes through many phase space interfaces and increases the efficiency with at least a factor of two with respect to existing transition path sampling rate constant algorithms. The new algorithm is illustrated on the isomerization of a diatomic molecule immersed in a simple fluid., Comment: 14 pages, including 13 figures, RevTeX4

Incommensurate structures can be described by the Frenkel Kontorova model. Aubry has shown that, at a critical value K_c of the coupling of the harmonic chain to an incommensurate periodic potential, the system displays the analyticity breaking transition between a sliding and pinned state. The ground state equations coincide with the standard map in non-linear dynamics, with smooth or chaotic orbits below and above K_c respectively. For the standard map, Greene and MacKay have calculated the value K_c=.971635. Conversely, evaluations based on the analyticity breaking of the modulation function have been performed for high commensurate approximants. Here we show how the modulation function of the infinite system can be calculated without using approximants but by Taylor expansions of increasing order. This approach leads to a value K_c'=.97978, implying the existence of a golden invariant circle up to K_c' > K_c., 7 pages, 5 figures, file 'epl.cls' necessary for compilation provided; Revised version, accepted for publication in Europhysics Letters