An efficient sampling algorithm for variational Monte Carlo

We propose a new algorithm for sampling the N-body density mid R:Psi(R)mid R:(2)R(3N)mid R:Psimid R:(2) in the variational Monte Carlo framework. This algorithm is based upon a modified Ricci-Ciccotti discretization of the Langevin dynamics in the phase space (R,P) improved by a Metropolis-Hastings accept/reject step. We show through some representative numerical examples (lithium, fluorine, and copper atoms and phenol molecule) that this algorithm is superior to the standard sampling algorithm based on the biased random walk (importance sampling).     

Steered transition path sampling

We introduce a path sampling method for obtaining statistical properties of an arbitrary stochastic dynamics. The method works by decomposing a trajectory in time, estimating the probability of satisfying a progress constraint, modifying the dynamics based on that probability, and then reweighting to calculate averages. Because the progress constraint can be formulated in terms of occurrences of events within time intervals, the method is particularly well suited for controlling the sampling of currents of dynamic events. We demonstrate the method for calculating transition probabilities in barrier crossing problems and survival probabilities in strongly diffusive systems with absorbing states, which are difficult to treat by shooting. We discuss the relation of the algorithm to other methods.     

Efficient transition path sampling for systems with multiple reaction pathways

A new algorithm is developed for sampling transition paths and computing reaction rates. To illustrate the use of this method, we study a two-dimensional system that has two reaction pathways: one pathway is straight with a relatively high barrier and the other is roundabout with a lower barrier. The transition rate and the ratio between the numbers of the straight and roundabout transition paths are computed for a wide range of temperatures. Our study shows that the harmonic approximation for fluctuations about the steepest-descent paths is not valid even at relatively low temperatures and, furthermore, that factors related to entropy have to be determined by the global geometry of the potential-energy surface (rather than just the local curvatures alone) for complex reaction systems. It is reasonable to expect that this algorithm is also applicable to higher dimensional systems.     

Improved transition path sampling methods for simulation of rare events

The free energy surfaces of a wide variety of systems encountered in physics, chemistry, and biology are characterized by the existence of deep minima separated by numerous barriers. One of the central aims of recent research in computational chemistry and physics has been to determine how transitions occur between deep local minima on rugged free energy landscapes, and transition path sampling (TPS) Monte-Carlo methods have emerged as an effective means for numerical investigation of such transitions. Many of the shortcomings of TPS-like approaches generally stem from their high computational demands. Two new algorithms are presented in this work that improve the efficiency of TPS simulations. The first algorithm uses biased shooting moves to render the sampling of reactive trajectories more efficient. The second algorithm is shown to substantially improve the accuracy of the transition state ensemble by introducing a subset of local transition path simulations in the transition state. The system considered in this work consists of a two-dimensional rough energy surface that is representative of numerous systems encountered in applications. When taken together, these algorithms provide gains in efficiency of over two orders of magnitude when compared to traditional TPS simulations.     

Mechanism of ligand exchange studied using transition path sampling

The mechanism of intermolecular ligand exchange has been studied using transition path sampling (TPS) based molecular dynamics (MD) simulations. Specifically, the exchange of solvent molecules bound to unsaturated Cr(CO)5 in methanol solution has been investigated. The results of the TPS simulations have shown that there are multiple steps in the reaction mechanism. The first involves partial dissociation of the coordinated solvent from the Cr metal center followed by association with a new methanol molecule between the normally void first and second solvent layers. After diffusive motion of the exchanging ligands, the last step involves the originally bound methanol molecule moving into the bath continuum followed by solvation of the Cr metal fragment by the exchanging ligand. It has been found that the reaction center (defined as the organometallic fragment and two exchanging ligands only) and the solvent bath have favorable interactions. This is likely due to the adiabatic nature of the ligand exchange transition. The ability to understand the microscopic molecular dynamics of a chemical process based on a free energy analysis is also discussed.     

An Anderson impurity model for efficient sampling of adiabatic potential energy surfaces of transition metal complexes

We present a model intended for rapid sampling of ground and excited state potential energy surfaces for first-row transition metal active sites. The method is computationally inexpensive and is suited for dynamics simulations where (1) adiabatic states are required "on-the-fly" and (2) the primary source of the electronic coupling between the diabatic states is the perturbative spin-orbit interaction among the 3d electrons. The model Hamiltonian we develop is a variant of the Anderson impurity model and achieves efficiency through a physically motivated basis set reduction based on the large value of the d-d Coulomb interaction U(d) and a Lanczos matrix diagonalization routine to solve for eigenvalues. The model parameters are constrained by fits to the partial density of states obtained from ab initio density functional theory calculations. For a particular application of our model we focus on electron transfer occurring between cobalt ions solvated by ammonium, incorporating configuration interaction between multiplet states for both metal ions. We demonstrate the capability of the method to efficiently calculate adiabatic potential energy surfaces and the electronic coupling factor we have calculated compares well to previous calculations and experiment. (     

Activation energy for a model ferrous-ferric half reaction from transition path sampling

Activation parameters for the model oxidation half reaction of the classical aqueous ferrous ion are compared for different molecular simulation techniques. In particular, activation free energies are obtained from umbrella integration and Marcus theory based thermodynamic integration, which rely on the diabatic gap as the reaction coordinate. The latter method also assumes linear response, and both methods obtain the activation entropy and the activation energy from the temperature dependence of the activation free energy. In contrast, transition path sampling does not require knowledge of the reaction coordinate and directly yields the activation energy [C. Dellago and P. G. Bolhuis, Mol. Simul. 30, 795 (2004)]. Benchmark activation energies from transition path sampling agree within statistical uncertainty with activation energies obtained from standard techniques requiring knowledge of the reaction coordinate. In addition, it is found that the activation energy for this model system is significantly smaller than the activation free energy for the Marcus model, approximately half the value, implying an equally large entropy contribution.     

An efficient algorithm for chemical fingerprinting

In this paper, we present and analyze a constructive polynomial-time algorithm that helps in solving the problem of comparing FT-ICR data to theoretical compounds. A brute-force approach to solving the problem is exponential in its worst-case. Our algorithm serves as the backbone of a more general interactive software tool for chemical fingerprinting which is to be developed in a subsequent paper. A preliminary algorithm analysis shows that our approach is efficient for most commercial applications involving the general problem of determining combinations of elements that satisfy a set of prescribed constraints.     

Unprejudiced identification of reaction mechanisms from biased transition path sampling

A method for unprejudiced investigation of reaction mechanisms from molecular-dynamics simulations is presented. It combines the transition path sampling approach with a biasing strategy, which (a) allows optimization of transition paths crossing an energy minimum of the transition state surface. The bias is then used to (b) find reaction pathways, which follow different mechanistic routes. In the first step the manifold of similar trajectories that correspond to the same mechanism is reduced to a single characteristic dynamical path. Our method then allows a systematic search for further reaction mechanisms and the related energy barriers. It is illustrated at the example of a single particle in a two-dimensional potential and of the rather complex process of the pressure-induced insertion of a helium atom into a C60 buckyball molecule.     

An efficient fluctuating charge model for transition metal complexes

A fluctuating charge model for transition metal complexes, based on the Hirshfeld partitioning scheme, spectroscopic energy data from the NIST Atomic Spectroscopy Database and the electronegativity equalization approach, has been developed and parameterized for organic ligands and their high‐ and low‐spin Fe^II and Fe^III, low‐spin Co^III and Cu^II complexes, using atom types defined in the Momec force field. Based on large training sets comprising a variety of transition metal complexes, a general parameter set has been developed and independently validated which allows the efficient computation of geometry‐dependent charge distributions in the field of transition metal coordination compounds. © 2013 Wiley Periodicals, Inc.     

An algorithm for the location of transition states

An algorithm for locating transition states designed for use in the ab initio program package GAUSSIAN 82 is presented. It is capable of locating transition states even if started in the wrong region of the energy surface, and, by incorporating the ideas on hessian mode following due to Cerjan and Miller, can locate transition states for alternative rearrangement/dissociation reactions from the same initial starting point. It can also be used to locate minima.     

Solventless nanoparticles synthesis under low pressure

In the present study, metal nanocrystals were obtained by the very easy, economical, and nontoxic thermal decomposition method and stabilized by coating oleate without any solvent. These nanocrystals have a highly crystalline structure due to a high decomposition temperature (~563-573 K) at low pressure and very narrow distribution. The prepared Fe3O4 nanocrystals were controlled by the annealing time and vacuum pressure. A TEM image of monodispersed Fe3O4 nanocrystals showed the 2D assembly of nanocrystals, demonstrating their uniformity. The particle size is 10.6 +/- 1.2 nm. TEM images of silver nanocrystals a showed 2D assembly with 9.5 +/- 0.7 nm. An electron diffraction image and X-ray diffraction of the nanocrystals showed the highly crystalline nature of metal nanocrystals.     

An efficient self-optimized sampling method for rare events in nonequilibrium systems

Rare events such as nucleation processes are of ubiquitous importance in real systems.The most popular method for nonequilibrium systems,forward flux sampling(FFS),samples rare events by using interfaces to partition the whole transition process into sequence of steps along an order parameter connecting the initial and final states.FFS usually suffers from two main difficulties:low computational efficiency due to bad interface locations and even being not applicable when trapping into unknown intermediate metastable states.In the present work,we propose an approach to overcome these difficulties,by self-adaptively locating the interfaces on the fly in an optimized manner.Contrary to the conventional FFS which set the interfaces with equal distance of the order parameter,our approach determines the interfaces with equal transition probability which is shown to satisfy the optimization condition.This is done by firstly running long local trajectories starting from the current interface i to get the conditional probability distribution Pc(>i|i),and then determining i+1by equaling Pc(i+1|i)to a give value p0.With these optimized interfaces,FFS can be run in a much more efficient way.In addition,our approach can conveniently find the intermediate metastable states by monitoring some special long trajectories that neither end at the initial state nor reach the next interface,the number of which will increase sharply from zero if such metastable states are encountered.We apply our approach to a two-state model system and a two-dimensional lattice gas Ising model.Our approach is shown to be much more efficient than the conventional FFS method without losing accuracy,and it can also well reproduce the two-step nucleation scenario of the Ising model with easy identification of the intermediate metastable state.     

An isothermal-isobaric Langevin thermostat for simulating nanoparticles under pressure: application to Au clusters.

We present a method for simulating clusters or molecules subjected to an external pressure, which is exerted by a pressure-transmitting medium. It is based on the canonical Langevin thermostat, but extended in such a way that the Brownian forces are allowed to operate only from the region exterior to the cluster. We show that the frictional force of the Langevin thermostat is linked to the pressure of the reservoir in a unique way, and that this property manifests itself when the particle it acts upon is not pointlike but has finite dimensions. By choosing appropriately the strength of the random forces and the friction coefficient, both temperature and pressure can be controlled independently. We illustrate the capabilities of this new method by calculating the compressibility of small gold clusters under pressure.     

Generation of initial trajectories for transition path sampling of chemical reactions with ab initio molecular dynamics

Transition path sampling is an innovative method for focusing a molecular dynamics simulation on a reactive event. Although transition path sampling methods can generate an ensemble of reactive trajectories, an initial reactive trajectory must be generated by some other means. In this paper, the authors have evaluated three methods for generating initial reactive trajectories for transition path sampling with ab initio molecular dynamics. The authors have tested each of these methods on a set of chemical reactions involving the breaking and making of covalent bonds: the 1,2-hydrogen elimination in the borane-ammonia adduct, a tautomerization, and the Claisen rearrangement. The first method is to initiate trajectories from the potential energy transition state, which was effective for all reactions in the test set. Assigning atomic velocities found using normal mode analysis greatly improved the success of this method. The second method uses a high temperature molecular dynamics simulation and then iteratively reduces the total energy of the simulation until a low temperature reactive trajectory is found. This was effective in generating a low temperature trajectory from an initial trajectory run at 3000 K of the tautomerization reaction, although it failed for the other two. The third uses an orbital based bias potential to find a reactive trajectory and uses this trajectory to initiate an unbiased trajectory. The authors found that a highest occupied molecular orbital-lowest unoccupied molecular orbital bias could be used to find a reactive trajectory for the Claisen rearrangement, although it failed for the other two reactions. These techniques will help make it practical to use transition path sampling to study chemical reaction mechanisms that involve bond breaking and forming.     

An efficient ring polymer contraction scheme for imaginary time path integral simulations

A quantum simulation of an imaginary time path integral typically requires around n times more computational effort than the corresponding classical simulation, where n is the number of ring polymer beads (or imaginary time slices) used in the calculation. However, this estimate neglects the fact that the potential energies of many systems can be decomposed into a sum of rapidly varying short-range and slowly varying long-range contributions. For such systems, the computational effort of the path integral simulation can be reduced considerably by evaluating the long-range forces on a contracted ring polymer with fewer beads than are needed to evaluate the short-range forces. This idea is developed and then illustrated with an application to a flexible model of liquid water in which the intramolecular forces are evaluated with 32 beads, the oxygen-oxygen Lennard-Jones forces with seven, and the intermolecular electrostatic forces with just five. The resulting static and dynamic properties are within a few percent of those of a full 32-bead calculation, and yet they are obtained with a computational effort less than six times (rather than 32 times) that of a classical simulation. We hope that this development will encourage future studies of quantum mechanical fluctuations in liquid water and aqueous solutions and in many other systems with similar interaction potentials.     

Exploring reaction pathways with transition path and umbrella sampling: application to methyl maltoside

The transition path sampling (TPS) method is a powerful approach to study chemical reactions or transitional properties on complex potential energy landscapes. One of the main advantages of the method over potential of mean force methods is that reaction rates can be directly accessed without knowledge of the exact reaction coordinate. We have investigated the complementary nature of these two differing approaches, comparing transition path sampling with the weighted histogram analysis method to study a conformational change in a small model system. In this case study, the transition paths for a transition between two rotational conformers of a model disaccharide molecule, methyl beta-D-maltoside, were compared with a free energy surface constrained by the two commonly used glycosidic (phi,psi) torsional angles. The TPS method revealed a reaction channel that was not apparent from the potential of mean force method, and the suitability of phi and psi as reaction coordinates to describe the isomerization in vacuo was confirmed by examination of the transition path ensemble. Using both transition state theory and transition path sampling methods, the transition rate was estimated. We have estimated a characteristic time between transitions of approximately 160 ns for this rare isomerization event between the two conformations of the carbohydrate. We conclude that transition path sampling can extract subtle information about the dynamics not apparent from the potential of mean force method. However, in calculating the reaction rate, the transition path sampling method required 27.5 times the computational effort than was needed by the potential of mean force method.     

A transition path sampling study of the reaction catalyzed by the enzyme chorismate mutase

The study of the chemical steps in enzyme-catalyzed reactions represents a challenge for molecular simulation techniques. One concern is how to calculate paths for the reaction. Common techniques include the definition of a reaction coordinate in terms of a small set of (normally) geometrical variables or the determination of minimum energy paths on the potential energy surface of the reacting system. Both have disadvantages, the former because it presupposes knowledge of which variables are likely to be important for reaction and the latter because it provides a static picture and dynamical effects are ignored. In this paper, we employ the transition path sampling method developed by Chandler and co-workers, which overcomes some of these limitations. The reaction that we have chosen is the chorismate-mutase-catalyzed conversion of chorismate into prephenate, which has become something of a test case for simulation studies of enzyme mechanisms. We generated an ensemble of approximately 1000 independent transition paths for the reaction in the enzyme and another approximately 500 for the corresponding reaction in solution. A large variety of analyses of these paths was performed, but we have concentrated on characterizing the transition state ensemble, particularly the flexibility of its structures with respect to other ligands of the enzyme and the time evolution of various geometrical and energetic properties as the reaction proceeds. We have also devised an approximate technique for locating transition state structures along the paths.