Grand Canonical adaptive resolution simulation for molecules with electrons: A theoretical framework based on physical consistency

Site, Luigi Delle

doi:10.1016/j.cpc.2017.09.020

Cited by 17 publications

(14 citation statements)

References 61 publications

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“…The next frontier for classical adaptive resolution methods is the extension to molecules with electrons. In this context, a computational framework that I have recently proposed, electronic AdResS (el‐QM‐AdResS), where the classical adaptive resolution technique is combined with the electronic scale, is discussed in the following sections. Finally, a discussion of the similarities, differences, and possible synergies of A‐QM/MM and el‐QM‐AdResS concludes the chapter.…”

Section: Molecules In Solution: Exchange Of Molecules Between System mentioning

confidence: 99%

“…An extension of the A‐QM/MM method that includes the internal criteria of control described in this section, has been proposed by myself and is based on the inclusion of molecules with electrons within the classical atomistic/coarse‐grained AdResS in its grand canonical version (GC‐AdResS) . The essence of the idea is reported in the next section.…”

Section: Molecules In Solution: Exchange Of Molecules Between System mentioning

confidence: 99%

“…AT indicates the atomistic region; Δ is the region where molecules change resolution according to

w (x)

Section: Molecules In Solution: Exchange Of Molecules Between System mentioning

confidence: 99%

“…In order to include electrons, the theoretical framework of el‐QM‐AdResS, proposed in ref. [], is based on two simple concepts (see also pictorial representation in Figure ): Use the classical GC‐AdResS scheme as a computational interface for the quantum region (i.e., equivalent to the MM region of a QM/MM scheme).GC‐AdResS will take care of providing and removing the (classical) nuclei (i.e., the skeleton of the molecule) in the QM region according to the macroscopic (thermodynamic) chemical potential. The electrons of the QM region are treated as a system in contact with an ideal (grand canonical) reservoir of electrons whose exchange of particles is regulated by a properly chosen (see explanation later) electronic chemical potential. The scheme follows three automatic criteria of control for assuring physical consistency of the calculation: The coupling between the QM region and the classical reservoir must be such that

false⟨ H_{Q M - A d} false⟩ ≪ false⟨ H_{Q M} false⟩

at any time, with

H_{Q M - A d}

the coupling Hamiltonian of the QM region with the GC‐AdResS interface (as an example of application of this criterion in GC‐AdResS, see refs. []). The macroscopic chemical potential must be such that

μ_{m a c r o}^{Q M} = μ_{m a c r o}^{G C - A d R e s S}

, that is, the whole system is at the same macroscopic chemical potential at any time. The electronic chemical potential in the QM region must satisfy the condition

μ_{e l}^{Q M} = μ_{e l}^{r e f}

, where

μ_{e l}^{r e f}

is the electronic chemical potential the QM region would have if the whole system was treated at quantum resolution.…”

Section: Molecules In Solution: Exchange Of Molecules Between System mentioning

confidence: 99%

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Simulation of Many‐Electron Systems That Exchange Matter with the Environment

Site

2018

Advcd Theory and Sims

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The computational treatment of many-electron systems capable of exchanging electrons and nuclei with the environment represents one of the outermost frontiers in simulation methodology. The exchanging process occurs in a large variety of natural and artificially induced phenomena which are of major relevance to several leading fields of academic research and modern technology. In this Progress Report, an overview of problems in current materials science and chemical physics is presented where the corresponding computational approaches require the concept of an electronic system with open boundaries. Quantum and quantum/classical computational techniques treat the exchange of electrons with the environment at different computational efficiency, conceptual rigorousness, and numerical accuracy. The overall emerging picture shows a rich availability of interesting ideas, some with a higher weight on the pragmatic side, others with higher weight on the conceptual side; possible combinations, in perspective, may push the field much beyond its current frontiers.

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Section: Molecules In Solution: Exchange Of Molecules Between System mentioning

confidence: 99%

Section: Molecules In Solution: Exchange Of Molecules Between System mentioning

confidence: 99%

“…AT indicates the atomistic region; Δ is the region where molecules change resolution according to

w (x)

Section: Molecules In Solution: Exchange Of Molecules Between System mentioning

confidence: 99%

false⟨ H_{Q M - A d} false⟩ ≪ false⟨ H_{Q M} false⟩

at any time, with

H_{Q M - A d}

μ_{m a c r o}^{Q M} = μ_{m a c r o}^{G C - A d R e s S}

, that is, the whole system is at the same macroscopic chemical potential at any time. The electronic chemical potential in the QM region must satisfy the condition

μ_{e l}^{Q M} = μ_{e l}^{r e f}

, where

μ_{e l}^{r e f}

is the electronic chemical potential the QM region would have if the whole system was treated at quantum resolution.…”

Section: Molecules In Solution: Exchange Of Molecules Between System mentioning

confidence: 99%

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Simulation of Many‐Electron Systems That Exchange Matter with the Environment

Site

2018

Advcd Theory and Sims

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“…Only recently it became feasible to set up an all-atom MD simulation for a larger set of DNA molecules [51,53] characterized by a single packing geometry with only a partial characterization of the DNA countercharge and solvent ordering. This approach has been later extended by the applications of the multiscale MD technique AdResS (Adaptive Resolution Scheme) [54][55][56][57][58][59][60][61][62][63][64][65][66][67], which has been already successfully applied to various biological systems [68][69][70][71][72][73][74][75][76][77], enabling a concurrent and consistent coupling between the atomistic (AT) and the coarse-grained (CG) representations with a key feature of allowing molecules to freely move not only in real space but also in the resolution space across different regions and change their resolution on the fly according to their position in the computational domain.…”

Section: Simulating Dna Arraysmentioning

confidence: 99%

Molecular Dynamics Simulation of High Density DNA Arrays

2018

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Densely packed DNA arrays exhibit hexagonal and orthorhombic local packings, as well as a weakly first order transition between them. While we have some understanding of the interactions between DNA molecules in aqueous ionic solutions, the structural details of its ordered phases and the mechanism governing the respective phase transitions between them remains less well understood. Since at high DNA densities, i.e., small interaxial spacings, one can neither neglect the atomic details of the interacting macromolecular surfaces nor the atomic details of the intervening ionic solution, the atomistic resolution is a sine qua non to properly describe and analyze the interactions between DNA molecules. In fact, in order to properly understand the details of the observed osmotic equation of state, one needs to implement multiple levels of organization, spanning the range from the molecular order of DNA itself, the possible ordering of counterions, and then all the way to the induced molecular ordering of the aqueous solvent, all coupled together by electrostatic, steric, thermal and direct hydrogen-bonding interactions. Multiscale simulations therefore appear as singularly suited to connect the microscopic details of this system with its macroscopic thermodynamic behavior. We review the details of the simulation of dense atomistically resolved DNA arrays with different packing symmetries and the ensuing osmotic equation of state obtained by enclosing a DNA array in a monovalent salt and multivalent (spermidine) counterions within a solvent permeable membrane, mimicking the behavior of DNA arrays subjected to external osmotic stress. By varying the DNA density, the local packing symmetry, and the counterion type, we are able to analyze the osmotic equation of state together with the full structural characterization of the DNA subphase, the counterion distribution and the solvent structural order in terms of its different order parameters and consequently identify the most important contribution to the DNA-DNA interactions at high DNA densities.

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Particle–Continuum Coupling and its Scaling Regimes: Theory and Applications

Site

Praprotnik

Bell

et al. 2020

Advcd Theory and Sims

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This work is motivated by the goal of designing simulation software for technical devices that, at their functional core, rely on atomistic-scale processes embedded in a larger-scale fluid environment. The core of the problem is the conceptual and technical approach for coupling particle and continuum representations of a fluid. The state of the art for key aspects including physical modeling, mathematical formalization, computational implementation, and applications, is discussed and organized in a consistent picture across the relevant physical regimes.Key building blocks of the related developments that we will summarize and appraise in some detail below are i) finite volume FHD solvers following Bell, Donev, Garcia, Nonaka and colleagues [4] (see Section 2), ii) the "adaptive resolution simulation" (AdResS) approach that enables molecular dynamics simulations on limited size domains [5][6][7] (see Section 3), and iii) the recent mathematical formalization of open molecular systems by two of the authors [8] (see Section 4). In Section 5, we discuss scaling regimes and the rationale behind possible MD-FHD coupling strategies, finally, Section 6 is dedicated to the description of some representative examples, while Section 7 outlines future perspectives and summarizes our conclusions.

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Grand Canonical adaptive resolution simulation for molecules with electrons: A theoretical framework based on physical consistency

Cited by 17 publications

References 61 publications

Simulation of Many‐Electron Systems That Exchange Matter with the Environment

Simulation of Many‐Electron Systems That Exchange Matter with the Environment

Molecular Dynamics Simulation of High Density DNA Arrays

Particle–Continuum Coupling and its Scaling Regimes: Theory and Applications

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