<i>Ab initio</i> mass tensor molecular dynamics

Tsuchida, Eiji

doi:10.1063/1.3543898

Cited by 21 publications

(17 citation statements)

References 76 publications

(92 reference statements)

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“…28 In this case, the atomic masses m were rescaled to m H = 1.236 44, m Li = 0.284 44, and m B = 4.444 44 following the treatment in Ref. 28. These were chosen to minimize the mismatch between the slow motion of the lithium atoms ( 500 cm −1 ) and the fast B−H stretch motion (2400 cm −1 ) of the original system.…”

Section: Calculationsmentioning

confidence: 99%

“…Second, to make the MD calculations more efficient, we took advantage of the fact that the ensemble averages, such as radial distribution functions and free energies, do not depend on the atomic masses. 28 In this case, the atomic masses m were rescaled to m H = 1.236 44, m Li = 0.284 44, and m B = 4.444 44 following the treatment in Ref. 28.…”

Section: Calculationsmentioning

confidence: 99%

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Fast-ionic conductivity of Li+in LiBH4

et al. 2011

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High Li + conductivity in the high-temperature (hexagonal) phase of LiBH 4 is revealed through a first-principles molecular dynamics simulation of 1200 atoms using periodic boundary conditions. The high ionic conductivity originates from the generation of a Li + metastable state located at an interstitial site surrounded by three Li + ions and three BH − 4 ions in the a-b plane. A defect is created by Li + ions hopping from their original sites to this interstitial site. The defect then diffuses through a path connecting the nearby Li sites separated in the a and c directions. Coupling of these movements is observed. The double splitting of the Li occupation in the original Li site plays an important role in the creation of the metastable state and migration through the connection path. The activation energy and diffusion coefficient are estimated, and are within one order of magnitude of experimentally retrieved values.

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Section: Calculationsmentioning

confidence: 99%

Section: Calculationsmentioning

confidence: 99%

Fast-ionic conductivity of Li+in LiBH4

et al. 2011

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“…This algorithm may also be used in conjunction with other methods to accelerate the simulations even further, such as the Langevin dynamics [5][6][7][8] , linear scaling method [24][25][26] and mass scaling method 27 . …”

Section: Discussionmentioning

confidence: 99%

Stabilization ofAb InitioMolecular Dynamics Simulations at Large Time Steps

Tsuchida¹

2015

Proceedings of Computational Science Workshop 2014 (CSW2014)

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“…We remark here that the main advantage of Eq. (34) is that it takes into account the explicit dependence of the matrix S on the atomic positions R, without using any cumbersome derivative of its inverse, as unavoidable in other methods [8,23,24], that are computationally much more expensive. This iteration scheme is not a Markov chain as the positions R at the next time t + ∆ depend not only on the actual time t but also on the previous ones t − ∆.…”

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confidence: 99%

“…At variance of all previous attempts [3][4][5][6][7][8][9][10], we propose that an optimal way to get rid of different time scales is based on the use of first order Langevin dynamics:…”

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Acceleratingab initioMolecular Dynamics and Probing the Weak Dispersive Forces in Dense Liquid Hydrogen

Mazzola

Sorella

2017

Phys. Rev. Lett.

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We propose an ab-initio molecular dynamics method, capable to reduce dramatically the autocorrelation time required for the simulation of classical and quantum particles at finite temperature. The method is based on an efficient implementation of a first order Langevin dynamics modified by means of a suitable, position dependent acceleration matrix S. Here we apply this technique, within a Quantum Monte Carlo (QMC) based wavefunction approach and within the Born-Oppheneimer approximation, for determining the phase diagram of high-pressure Hydrogen with simulations much longer than the autocorrelation time. With the proposed method, we are able to equilibrate in few hundreds steps even close to the liquid-liquid phase transition (LLT). Within our approach we find that the LLT transition is consistent with recent density functionals predicting a much larger transition pressures when the long range dispersive forces are taken into account.One of the most important problems in ab-initio molecular dynamics (MD) is the coexistence of much different time scales underlying physical processes, even when computing equilibrium finite temperature properties. This has been a challenge for most ab-initio simulations in systems of biophysical interest, the most striking one being protein folding [1,2], where the microscopic time scale of molecular vibration is of the order of f s, while the macroscopic time scale of the folding exceeds the µs. Also in water system simulations, the weak Van der Waals (vdW) interactions and the related hydrogen bond imply very difficult equilibration properties at ambient conditions, so that the most accurate simulations are based on force field fitting forces. We will show here that, a computationally expensive ab-initio method for dense liquid hydrogen can be combined with a sampling technique capable to reduce drastically the autocorrelation times. This method has the potential, due to its simplicity, to be applied with success also to much more complex systems and other ab-initio techniques.At variance of all previous attempts[3-10], we propose that an optimal way to get rid of different time scales is based on the use of first order Langevin dynamics:where T is the temperature, f Ri = −∂ Ri V ( R) and V R is an energy potential of the classical coordinates R, e.g. atomic positions. For S ij = δ ij this is the conventional first order Langevin dynamics (CFOLD). Preconditioned Langevin equations, formally similar to Eq. 40, have been already introduced in several fields different from molecular dynamics, such as gauge field theories[11], statistics [12] and machine learning [13], with different definitions of the preconditioning matrix S. Instead, the main idea of this work is based on the simple solution of CFOLD for the harmonic potential V (R) = −K R, where K is the elastic matrix term. In this case one is able to show that the i) the autocorrelation time is independent of temperature τ −1 corr = K min , where K min (K max ) is the lowest (largest) non-zero eigenvalue of the elastic matrix...

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Ab initio mass tensor molecular dynamics

Cited by 21 publications

References 76 publications

Fast-ionic conductivity of Li+in LiBH4

Fast-ionic conductivity of Li+in LiBH4

Stabilization ofAb InitioMolecular Dynamics Simulations at Large Time Steps

Acceleratingab initioMolecular Dynamics and Probing the Weak Dispersive Forces in Dense Liquid Hydrogen

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