QuasiEwald.jl

This is a julia package for Quasi Ewald method.
Author HPMolSim
Popularity
1 Star
Updated Last
6 Months Ago
Started In
May 2023

QuasiEwald.jl

Build Status

QuasiEwald.jl is a package written in Julia. It is an implementation of the algorithm Quasi Ewald Method, which used to calculate the electrostatic interaction in dielectric confined Quasi-2D charged systems for MD simulations, which has a linear complexity to the number of particles.

Getting Started

This package has to be used as an extentation of the author's previous package ExTinyMD.jl, which is a small but fast MD package written in Julia language. To use this package, you only need to type

pkg> add ExTinyMD, QuasiEwald

in your command lines.

Here is an simple example, which will calculate the interaction between two paricle confined by dielectric substrate of different dielectric permittivity.

using Plots, ExTinyMD, QuasiEwald

begin
    n_atoms = 2
    L = 180.0
    boundary = ExTinyMD.Q2dBoundary(L, L, 10.0) 

    atoms = [Atom(type = 1, mass = 1.0, charge = 1.0), Atom(type = 2, mass = 1.0, charge = -1.0)]

    sys = MDSys(
                n_atoms = n_atoms,
                atoms = atoms,
                boundary = boundary,
                interactions = [(NoInteraction(), NoNeighborFinder(n_atoms))],
                loggers = [TrajectionLogger(step = 100, output = false)],
                simulator = VerletProcess(dt = 0.001, thermostat = AndersenThermoStat(1.0, 0.05))
            )

    Force_x = Vector{Vector{Float64}}()
    coord_1 = Point(50.0, 50.0, 1.0)
    X = 0.1:0.1:40.0

    for (γ_1, γ_2) in [(0.0, 0.0), (0.95, 0.95), (-0.95, -0.95), (10.0, 10.0), (-10.0, -10.0)]
        ϵ_0 = 1.0
        n_t = 30

        accuracy = 1e-4
        α = 1.0
        r_c = 15.0
        k_c = sqrt(-4 * α * log(accuracy))

        force_x = Vector{Float64}()

        for x_2 in X
            info = SimulationInfo(n_atoms, atoms, (0.0, L, 0.0, L, 0.0, 10.0), boundary; min_r = 1.0, temp = 1.0)
            coord_2 = Point(50.0 + x_2, 50.0, 1.01)

            info.particle_info[1].position = coord_1
            info.particle_info[2].position = coord_2

            sortz = SortingFinder(info)
            cellq2d = CellListQ2D(info, r_c, boundary, 1)
            interaction_short = QuasiEwaldShortInteraction(γ_1, γ_2, ϵ_0, (L, L, 10.0), false, accuracy, α, n_atoms, r_c, n_t)
            interaction_long = QuasiEwaldLongInteraction(γ_1, γ_2, ϵ_0, (L, L, 10.0), false, accuracy, α, n_atoms, k_c, 0)
    
            force_qem = [Point(0.0, 0.0, 0.0) for i in 1:n_atoms]
            QuasiEwald_Fs!(interaction_short, cellq2d, sys, info)
            QuasiEwald_Fl!(interaction_long, sortz, sys, info)
            push!(force_x, info.particle_info[1].acceleration[1])
        end
        push!(Force_x, force_x)
    end

    plot(dpi = 300, size = (800, 600), legend = :topright, xlabel = "x", ylabel = "force_x")
    for (γ, force_x) in zip([0.0, 0.95, -0.95, 10.0, -10.0], Force_x)
        plot!(X, force_x, label = "γ = " * string(γ), ylim = [-0.06, 0.06])
    end
    savefig("force_x.png")
end

To run this script, you can simple type:

julia ./example/force/force_pair.jl

The result is shown below:

Force in x direction

Here is another example, which shows how to simulate a dielectric confined charged system via ExTinyMD.jl and QuasiEwald.jl.

using ExTinyMD, QuasiEwald

begin
    n_atoms = 436
    n_atoms = Int64(round(n_atoms))
    L_x = 100.0
    L_y = 100.0
    L_z = 50.0
    L = (L_x, L_y, L_z)
    boundary = Q2dBoundary(L_x, L_y, L_z)
    atoms = Vector{Atom{Float64}}()

    for i in 1:218
        push!(atoms, Atom(type = 1, mass = 1.0, charge = 1.0))
    end

    for i in 219:436
        push!(atoms, Atom(type = 2, mass = 1.0, charge = - 1.0))
    end

    (γ_1, γ_2) = (0.95, -0.95)

    info = SimulationInfo(n_atoms, atoms, (0.0, L_x, 0.0, L_y, 0.5, L_z - 0.5), boundary; min_r = 2.0, temp = 1.0)

    ϵ_0 = 1.0

    accuracy = 1e-4
    α = 1.0
    k_c = sqrt(- 4 * α * log(accuracy))
    r_c =* accuracy)^(-1/3) / 2
    n_t = 30
    rbe_p = 50

    intershort = QuasiEwaldShortInteraction(γ_1, γ_2, ϵ_0, L, true, accuracy, α, n_atoms, r_c, n_t)
    short_finder = CellListQ2D(info, r_c + 1.0, boundary, 100)
    interlong = QuasiEwaldLongInteraction(γ_1, γ_2, ϵ_0, L, true, accuracy, α, n_atoms, k_c, rbe_p)
    long_finder = SortingFinder(info)

    interactions = [
        (LennardJones(), CellList3D(info, 4.5, boundary, 100)),
        (SubLennardJones(0.0, L_z; cutoff = 0.5, σ = 0.5), SubNeighborFinder(1.0, info, 0.0, L_z)), 
        (intershort, short_finder),
        (interlong, long_finder)
        ]

    loggers = [TempartureLogger(100, output = true), TrajectionLogger(step = 100, output = true)]
    simulator = VerletProcess(dt = 0.001, thermostat = AndersenThermoStat(1.0, 0.05))

    sys = MDSys(
        n_atoms = n_atoms,
        atoms = atoms,
        boundary = boundary,
        interactions = interactions,
        loggers = loggers,
        simulator = simulator
    )

    simulate!(simulator, sys, info, 100000)
end

which will simulate 436 changed particle confined by substrates with $\gamma = 0.95$ for $10^6$ steps, and the trajection will be recorded.

Questions and Contributions

Please open an issue if you encounter any problems, or have any feature requests.

It is also welcomed for any suggestions about the issues marked as enhancement, please let us know if you have any idea about them.

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