A first principles simulation of rigid water

Allesch, Markus; Schwegler, Eric; Gygi, François; Galli, Giulia

doi:10.1063/1.1647529

Cited by 83 publications

(88 citation statements)

References 46 publications

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“…Note, however, that in the context of simulations that still only provide an approximate description of the exact QM dynamics of the system (Born-Oppenheimer approximation, neglect of nuclear quantum effects, 121,303-307 QM/MM treatment, and approximate QM method), the inclusion of solvent flexibility is not guaranteed to give an improvement in accuracy. 296,[308][309][310] In addition, this inclusion represents an additional increase in the computational costs by a factor of about 4-10, caused by the requirement of a corresponding time step reduction.…”

Section: Discussionmentioning

confidence: 99%

Absolute proton hydration free energy, surface potential of water, and redox potential of the hydrogen electrode from first principles: QM/MM MD free-energy simulations of sodium and potassium hydration

Hofer

Hünenberger

2018

The Journal of Chemical Physics

104

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The absolute intrinsic hydration free energy G • H + ,wat of the proton, the surface electric potential jump χ • wat upon entering bulk water, and the absolute redox potential V • H + ,wat of the reference hydrogen electrode are cornerstone quantities for formulating single-ion thermodynamics on absolute scales. They can be easily calculated from each other but remain fundamentally elusive, i.e., they cannot be determined experimentally without invoking some extra-thermodynamic assumption (ETA). The Born model provides a natural framework to formulate such an assumption (Born ETA), as it automatically factors out the contribution of crossing the water surface from the hydration free energy. However, this model describes the short-range solvation inaccurately and relies on the choice of arbitrary ion-size parameters. In the present study, both shortcomings are alleviated by performing first-principle calculations of the hydration free energies of the sodium (Na + ) and potassium (K + ) ions. The calculations rely on thermodynamic integration based on quantum-mechanical molecular-mechanical (QM/MM) molecular dynamics (MD) simulations involving the ion and 2000 water molecules. The ion and its first hydration shell are described using a correlated ab initio method, namely resolution-of-identity second-order Møller-Plesset perturbation (RIMP2). The next hydration shells are described using the extended simple point charge water model (SPC/E). The hydration free energy is first calculated at the MM level and subsequently increased by a quantization term accounting for the transformation to a QM/MM description. It is also corrected for finite-size, approximate-electrostatics, and potentialsummation errors, as well as standard-state definition. These computationally intensive simulations provide accurate first-principle estimates for G • H + ,wat , χ • wat , and V • H + ,wat , reported with statistical errors based on a confidence interval of 99%. The values obtained from the independent Na + and K + simulations are in excellent agreement. In particular, the difference between the two hydration free energies, which is not an elusive quantity, is 73.9 ± 5.4 kJ mol 1 (K + minus Na + ), to be compared with the experimental value of 71.7 ± 2.8 kJ mol 1 . The calculated values of G • H + ,wat , χ • wat , and V • H + ,wat ( 1096.7 ± 6.1 kJ mol 1 , 0.10 ± 0.10 V, and 4.32 ± 0.06 V, respectively, averaging over the two ions) are also in remarkable agreement with the values recommended by Reif and Hünenberger based on a thorough analysis of the experimental literature ( 1100 ± 5 kJ mol 1 , 0.13 ± 0.10 V, and 4.28 ± 0.13 V, respectively). The QM/MM MD simulations are also shown to provide an accurate description of the hydration structure, dynamics, and energetics. Published by AIP Publishing.

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Section: Discussionmentioning

confidence: 99%

Absolute proton hydration free energy, surface potential of water, and redox potential of the hydrogen electrode from first principles: QM/MM MD free-energy simulations of sodium and potassium hydration

Hofer

Hünenberger

2018

The Journal of Chemical Physics

104

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“…The expectations on computational models are indeed very high: for example, the specificity of biomolecular interactions depends greatly on microscopic, solvent-mediated effects [26][27][28]. Although many microscopic properties of the neat liquid, and of solute-solvent interactions, are difficult to assess experimentally, advances in quantum calculations [29][30][31][32][33][34][35] of water structure as well as experimental data on the properties of water in the liquid phase [36] and around biomolecules [26] will provide a basis for increasingly detailed explicit water models for robust treatment of water in many environments.…”

Section: Introductionmentioning

confidence: 99%

Solvent reaction field potential inside an uncharged globular protein: A bridge between implicit and explicit solvent models?

Cerutti

Baker

McCammon

2007

The Journal of Chemical Physics

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The solvent reaction field potential of an uncharged protein immersed in Simple Point Charge/ Extended (SPC/E) explicit solvent was computed over a series of molecular dynamics trajectories, intotal 1560 ns of simulation time. A finite, positive potential of 13 to 24 k b Te c −1 (where T = 300K), dependent on the geometry of the solvent-accessible surface, was observed inside the biomolecule. The primary contribution to this potential arose from a layer of positive charge density 1.0 Å from the solute surface, on average 0.008 e c /Å 3 , which we found to be the product of a highly ordered first solvation shell. Significant second solvation shell effects, including additional layers of charge density and a slight decrease in the short-range solvent-solvent interaction strength, were also observed. The impact of these findings on implicit solvent models was assessed by running similar explicit-solvent simulations on the fully charged protein system. When the energy due to the solvent reaction field in the uncharged system is accounted for, correlation between per-atom electrostatic energies for the explicit solvent model and a simple implicit (Poisson) calculation is 0.97, and correlation between per-atom energies for the explicit solvent model and a previously published, optimized Poisson model is 0.99.

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“…As mentioned it is a real problem for application of graphene into nano-electronics, since for nano-electronics applications of graphene a mass gap in itŠs energy spectrum is needed just like a conventional semiconductor. We also see that, considering the appropriate wave functions in region of electrostatic barrier reveals that transmission is independent of whether the refractive index is negative or positive [15][16][17]. There is exactly a mistake on this point in the well-known paper "The electronic properties of graphene" [18].…”

Section: Introductionmentioning

confidence: 98%

Electronic Tunneling in Graphene

Jahani¹

2013

New Progress on Graphene Research

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A first principles simulation of rigid water

Cited by 83 publications

References 46 publications

Absolute proton hydration free energy, surface potential of water, and redox potential of the hydrogen electrode from first principles: QM/MM MD free-energy simulations of sodium and potassium hydration

Absolute proton hydration free energy, surface potential of water, and redox potential of the hydrogen electrode from first principles: QM/MM MD free-energy simulations of sodium and potassium hydration

Solvent reaction field potential inside an uncharged globular protein: A bridge between implicit and explicit solvent models?

Electronic Tunneling in Graphene

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