arXiv subjects

Michele Parrinello

Publications and source records attributed to Michele Parrinello.

At least 109 records · Page 6Linked to original sources

arXiv2015

Variationally Optimized Free Energy Flooding for Rate Calculation

We propose a new method to obtain kinetic properties of infrequent events from molecular dynamics simulation. The procedure employs a recently introduced variational approach [Valsson and Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] to construct a bias potential as a function of several collective variables that is designed to flood only the associated free energy surface up to a predefined level. The resulting bias potential effectively accelerates transitions between metastable free energy minima while ensuring bias-free transition states, thus allowing accurate kinetic rates to be obtained. We test the method on a few illustrative systems for which we obtain an order of magnitude improvement in efficiency relative to previous approaches, and several orders of magnitude relative to unbiased molecular dynamics. We expect an even larger improvement in more complex systems. This and the ability of the variational approach to deal efficiently with a large number of collective variables will greatly enhance the scope of these calculations. This work is a vindication of the potential that the variational principle has if applied in innovative ways

cond-mat.stat-mech↗

arXiv2015

Molecular Dynamics Simulations of Solutions at Constant Chemical Potential

Molecular Dynamics studies of chemical processes in solution are of great value in a wide spectrum of applications, which range from nano-technology to pharmaceutical chemistry. However, these calculations are affected by severe finite-size effects, such as the solution being depleted as the chemical process proceeds, which influence the outcome of the simulations. To overcome these limitations, one must allow the system to exchange molecules with a macroscopic reservoir, thus sampling a Grand-Canonical ensemble. Despite the fact that different remedies have been proposed, this still represents a key challenge in molecular simulations. In the present work we propose the Constant Chemical Potential Molecular Dynamics (C$μ$MD) method, which introduces an external force that controls the environment of the chemical process of interest. This external force, drawing molecules from a finite reservoir, maintains the chemical potential constant in the region where the process takes place. We have applied the C$μ$MD method to the paradigmatic case of urea crystallization in aqueous solution. As a result, we have been able to study crystal growth dynamics under constant supersaturation conditions, and to extract growth rates and free-energy barriers.

physics.chem-ph↗

arXiv2014

A Variational Approach to Enhanced Sampling and Free Energy Calculations

The ability of widely used sampling methods, such as molecular dynamics or Monte Carlo, to explore complex free energy landscapes is severely hampered by the presence of kinetic bottlenecks. A large number of solutions have been proposed to alleviate this problem. Many are based on the introduction of a bias potential which is a function of a small number of collective variable. However constructing such a bias is not simple. Here we introduce a functional of the bias potential and an associated variational principle. The bias that minimizes the functional relates in a simple way to the free energy surface. This variational principle can be turned into a practical, efficient and flexible sampling method. A number of numerical examples are presented which include the determination of a three dimensional free energy surface. We argue that, beside being numerically advantageous, our variational approach provides a convenient standpoint for looking with novel eyes at the sampling problem.

cond-mat.stat-mech↗

arXiv2014

Evaluating functions of positive-definite matrices using colored noise thermostats

Many applications in computational science require computing the elements of a function of a large matrix. A commonly used approach is based on the the evaluation of the eigenvalue decomposition, a task that, in general, involves a computing time that scales with the cube of the size of the matrix. We present here a method that can be used to evaluate the elements of a function of a positive-definite matrix with a scaling that is linear for sparse matrices and quadratic in the general case. This methodology is based on the properties of the dynamics of a multidimensional harmonic potential coupled with colored noise generalized Langevin equation (GLE) thermostats. This "$f-$thermostat" (FTH) approach allows us to calculate directly elements of functions of a positive-definite matrix by carefully tailoring the properties of the stochastic dynamics. We demonstrate the scaling and the accuracy of this approach for both dense and sparse problems and compare the results with other established methodologies.

physics.comp-ph↗

arXiv2013

From Metadynamics to Dynamics

Metadynamics is a commonly used and successful enhanced sampling method. By the introduction of a history dependent bias which depends on a restricted number of collective variables(CVs) it can explore complex free energy surfaces characterized by several metastable states separated by large free energy barriers. Here we extend its scope by introducing a simple yet powerful method for calculating the rates of transition between different metastable states. The method does not rely on a previous knowledge of the transition states or reaction co-ordinates, as long as CVs are known that can distinguish between the various stable minima in free energy space. We demonstrate that our method recovers the correct escape rates out of these stable states and also preserves the correct sequence of state-to-state transitions, with minimal extra computational effort needed over ordinary metadynamics. We apply the formalism to three different problems and in each case find excellent agreement with the results of long unbiased molecular dynamics runs.

cond-mat.stat-mech↗

arXiv2012

Metadynamics with adaptive Gaussians

Metadynamics is an established sampling method aimed at reconstructing the free-energy surface relative to a set of appropriately chosen collective variables. In standard metadynamics the free-energy surface is filled by the addition of Gaussian potentials of pre-assigned and typically diagonal covariance. Asymptotically the free-energy surface is proportional to the bias deposited. Here we consider the possibility of using Gaussians whose variance is adjusted on the fly to the local properties of the free-energy surface. We suggest two different prescriptions: one is based on the local diffusivity and the other on the local geometrical properties. We further examine the problem of extracting the free-energy surface when using adaptive Gaussians. We show that the standard relation between the bias and the free energy does not hold. In the limit of narrow Gaussians an explicit correction can be evaluated. In the general case we propose to use instead a relation between bias and free energy borrowed from umbrella sampling. This relation holds for all kinds of incrementally deposited bias. We illustrate on the case of alanine dipeptide the advantage of using adaptive Gaussians in conjunction with the new free-energy estimator both in terms of accuracy and speed of convergence.

cond-mat.stat-mech↗

arXiv2012

Colored-noise thermostats à la carte

Recently, we have shown how a colored-noise Langevin equation can be used in the context of molecular dynamics as a tool to obtain dynamical trajectories whose properties are tailored to display desired sampling features. In the present paper, after having reviewed some analytical results for the stochastic differential equations forming the basis of our approach, we describe in detail the implementation of the generalized Langevin equation thermostat and the fitting procedure used to obtain optimal parameters. We discuss in detail the simulation of nuclear quantum effects, and demonstrate that, by carefully choosing parameters, one can successfully model strongly anharmonic solids such as neon. For the reader's convenience, a library of thermostat parameters and some demonstrative code can be downloaded from an on-line repository.

physics.comp-ph↗

arXiv2012

Accelerating the convergence of path integral dynamics with a generalized Langevin equation

The quantum nature of nuclei plays an important role in the accurate modelling of light atoms such as hydrogen, but it is often neglected in simulations due to the high computational overhead involved. It has recently been shown that zero-point energy effects can be included comparatively cheaply in simulations of harmonic and quasi-harmonic systems by augmenting classical molecular dynamics with a generalized Langevin equation (GLE). Here we describe how a similar approach can be used to accelerate the convergence of path integral (PI) molecular dynamics to the exact quantum mechanical result in more strongly anharmonic systems exhibiting both zero point energy and tunnelling effects. The resulting PI-GLE method is illustrated with applications to a double-well tunnelling problem and to liquid water.

physics.comp-ph↗

arXiv2011

Microscopic origins of the anomalous melting behaviour of high-pressure sodium

Recent experiments have shown that sodium, a prototype simple metal at ambient conditions, exhibits unexpected complexity under high pressure. One of the most puzzling phenomena in the behaviour of dense sodium is the pressure-induced drop in its melting temperature, which extends from 1000 K at ~30GPa to as low as room temperature at ~120GPa. Despite significant theoretical effort to understand the anomalous melting its origins have remained unclear. In this work, we reconstruct the sodium phase diagram using an ab-initio-quality neural-network potential. We demonstrate that the reentrant behaviour results from the screening of interionic interactions by conduction electrons, which at high pressure induces a softening in the short-range repulsion. It is expected that such an effect plays an important role in governing the behaviour of a wide range of metals and alloys.

cond-mat.mtrl-sci↗

arXiv2011

Momentum distribution, vibrational dynamics and the potential of mean force in ice

By analyzing the momentum distribution obtained from path integral and phonon calculations we find that the protons in hexagonal ice experience an anisotropic quasi-harmonic effective potential with three distinct principal frequencies that reflect molecular orientation. Due to the importance of anisotropy, anharmonic features of the environment cannot be extracted from existing experimental distributions that involve the spherical average. The full directional distribution is required, and we give a theoretical prediction for this quantity that could be verified in future experiments. Within the quasi-harmonic context, anharmonicity in the ground state dynamics of the proton is substantial and has quantal origin, a finding that impacts the interpretation of several spectroscopies.

quant-ph↗

arXiv2011

Nucleation mechanism for the direct graphite-to-diamond phase transition

Graphite and diamond have comparable free energies, yet forming diamond from graphite is far from easy. In the absence of a catalyst, pressures that are significantly higher than the equilibrium coexistence pressures are required to induce the graphite-to-diamond transition. Furthermore, the formation of the metastable hexagonal polymorph of diamond instead of the more stable cubic diamond is favored at lower temperatures. The concerted mechanism suggested in previous theoretical studies cannot explain these phenomena. Using an ab initio quality neural-network potential we performed a large-scale study of the graphite-to-diamond transition assuming that it occurs via nucleation. The nucleation mechanism accounts for the observed phenomenology and reveals its microscopic origins. We demonstrated that the large lattice distortions that accompany the formation of the diamond nuclei inhibit the phase transition at low pressure and direct it towards the hexagonal diamond phase at higher pressure. The nucleation mechanism proposed in this work is an important step towards a better understanding of structural transformations in a wide range of complex systems such as amorphous carbon and carbon nanomaterials.

cond-mat.mtrl-sci↗

arXiv2010

Nuclear quantum effects in ab initio dynamics: theory and experiments for lithium imide

Owing to their small mass, hydrogen atoms exhibit strong quantum behavior even at room temperature. Including these effects in first principles calculations is challenging, because of the huge computational effort required by conventional techniques. Here we present the first ab-initio application of a recently-developed stochastic scheme, which allows to approximate nuclear quantum effects inexpensively. The proton momentum distribution of lithium imide, a material of interest for hydrogen storage, was experimentally measured by inelastic neutron scattering experiments and compared with the outcome of quantum thermostatted ab initio dynamics. We obtain favorable agreement between theory and experiments for this purely quantum mechanical property, thereby demonstrating that it is possible to improve the modelling of complex hydrogen-containing materials without additional computational effort.

cond-mat.mtrl-sci↗

arXiv2010

Static disorder and structural correlations in the low temperature phase of lithium imide

Based on ab-initio molecular dynamics simulations, we investigate the low temperature crystal structure of Li2NH which in spite of its great interest as H-storage material is still matter of debate. The dynamical simulations reveal a precise correlation in the fractional occupation of Li sites which leads average atomic positions in excellent agreement with diffraction data and solves inconsistencies of previous proposals.

cond-mat.mtrl-sci↗

arXiv2010

A self-learning algorithm for biased molecular dynamics

A new self-learning algorithm for accelerated dynamics, reconnaissance metadynamics, is proposed that is able to work with a very large number of collective coordinates. Acceleration of the dynamics is achieved by constructing a bias potential in terms of a patchwork of one-dimensional, locally valid collective coordinates. These collective coordinates are obtained from trajectory analyses so that they adapt to any new features encountered during the simulation. We show how this methodology can be used to enhance sampling in real chemical systems citing examples both from the physics of clusters and from the biological sciences.

physics.comp-ph↗

arXiv2010

Efficient stochastic thermostatting of path integral molecular dynamics

The path integral molecular dynamics (PIMD) method provides a convenient way to compute the quantum mechanical structural and thermodynamic properties of condensed phase systems at the expense of introducing an additional set of high-frequency normal modes on top of the physical vibrations of the system. Efficiently sampling such a wide range of frequencies provides a considerable thermostatting challenge. Here we introduce a simple stochastic path integral Langevin equation (PILE) thermostat which exploits an analytic knowledge of the free path integral normal mode frequencies. We also apply a recently-developed colored-noise thermostat based on a generalized Langevin equation (GLE), which automatically achieves a similar, frequency-optimized sampling. The sampling efficiencies of these thermostats are compared with that of the more conventional Nosé-Hoover chain (NHC) thermostat for a number of physically relevant properties of the liquid water and hydrogen-in-palladium systems. In nearly every case, the new PILE thermostat is found to perform just as well as the NHC thermostat while allowing for a computationally more efficient implementation. The GLE thermostat also proves to be very robust delivering a near-optimum sampling efficiency in all of the cases considered. We suspect that these simple stochastic thermostats will therefore find useful application in many future PIMD simulations.

cond-mat.stat-mech↗

arXiv2010

Displaced path integral formulation for the momentum distribution of quantum particles

The proton momentum distribution, accessible by deep inelastic neutron scattering, is a very sensitive probe of the potential of mean force experienced by the protons in hydrogen-bonded systems. In this work we introduce a novel estimator for the end to end distribution of the Feynman paths, i.e. the Fourier transform of the momentum distribution. In this formulation, free particle and environmental contributions factorize. Moreover, the environmental contribution has a natural analogy to a free energy surface in statistical mechanics, facilitating the interpretation of experiments. The new formulation is not only conceptually but also computationally advantageous. We illustrate the method with applications to an empirical water model, ab-initio ice, and one dimensional model systems.

physics.comp-ph↗

arXiv2010

Ab initio quality study of the graphite-diamond phase coexistence

An interatomic potential for the diamond and graphite phases of carbon has been created using a neural-network (NN) representation of the ab initio potential energy surface. The NN potential combines the accuracy of a first-principle description of both phases with the efficiency of empirical force fields and allows one to perform, for the first time, a molecular dynamics study, of ab initio quality, of the thermodynamics of graphite-diamond coexistence. Good agreement between the experimental and calculated coexistence curves is achieved if nuclear quantum effects are included in the simulation.

cond-mat.mtrl-sci↗

arXiv2010

Ab initio quality neural-network potential for sodium

An interatomic potential for high-pressure high-temperature (HPHT) crystalline and liquid phases of sodium is created using a neural-network (NN) representation of the ab initio potential energy surface. It is demonstrated that the NN potential provides an ab initio quality description of multiple properties of liquid sodium and bcc, fcc, cI16 crystal phases in the P-T region up to 120 GPa and 1200 K. The unique combination of computational efficiency of the NN potential and its ability to reproduce quantitatively experimental properties of sodium in the wide P-T range enables molecular dynamics simulations of physicochemical processes in HPHT sodium of unprecedented quality.

cond-mat.mtrl-sci↗