Simulating a simple laser structure with 5 layers. The layers are defined by their material properties and thicknesses. The simulation will solve the charge transport equations across the layers, taking into account the stimulated recombination in the active region of the laser structure.
module Ex202_Laser_simple
using ChargeTransport
using ExtendableGrids
using GridVisualize
using PyPlot
###########################################################################
numberOfColoumns = Dict(
"ref1" => [2, 4],
"ref2" => [4, 8],
"ref3" => [8, 16],
"ref4" => [16, 32],
"ref5" => [32, 64]
)
numberOfRows = Dict(
"ref1" => [4, 8, 2, 8, 4],
"ref2" => [8, 16, 4, 16, 8],
"ref3" => [16, 32, 8, 32, 16],
"ref4" => [32, 64, 16, 64, 32],
"ref5" => [64, 128, 32, 128, 64]
)
###################################################################
""" Initializing X and Y coords for the tesca grid"""
function tesca_grid(; refinement = 1, showplot = false, airbox = false)
ncol = numberOfColoumns["ref$(refinement)"]
nrow = numberOfRows["ref$(refinement)"]
widths_columns = [1.0 10.0] * μm
heights_rows = [1.0 0.5 0.05 0.5 1.0] * μm
coord_x1 = collect(range(0.0, widths_columns[1], length = ncol[1] + 1))
coord_x2 = collect(range(widths_columns[1], sum(widths_columns[1:2]), length = ncol[2] + 1))
X = glue(coord_x1, coord_x2)
X = glue(reverse(-X), X)
coord_y1 = collect(range(0.0, heights_rows[1], length = nrow[1] + 1))
coord_y2 = collect(range(heights_rows[1], sum(heights_rows[1:2]), length = nrow[2] + 1))
coord_y3 = collect(range(sum(heights_rows[1:2]), sum(heights_rows[1:3]), length = nrow[3] + 1))
coord_y4 = collect(range(sum(heights_rows[1:3]), sum(heights_rows[1:4]), length = nrow[4] + 1))
coord_y5 = collect(range(sum(heights_rows[1:4]), sum(heights_rows[1:5]), length = nrow[5] + 1))
Y = glue(glue(glue(glue(coord_y1, coord_y2), coord_y3), coord_y4), coord_y5)
grid = simplexgrid(X, Y)
cellmask!(grid, [X[1], 0.0], [sum(widths_columns), heights_rows[1]], 1)
cellmask!(grid, [X[1], heights_rows[1]], [sum(widths_columns), sum(heights_rows[1:2])], 2)
cellmask!(grid, [X[1], sum(heights_rows[1:2])], [sum(widths_columns), sum(heights_rows[1:3])], 3)
cellmask!(grid, [X[1], sum(heights_rows[1:3])], [sum(widths_columns), sum(heights_rows[1:4])], 4)
cellmask!(grid, [X[1], sum(heights_rows[1:4])], [sum(widths_columns), sum(heights_rows[1:5])], 5)AIR
cellmask!(grid, [widths_columns[1], sum(heights_rows[1:4])], [sum(widths_columns), sum(heights_rows[1:5])], 6)
cellmask!(grid, [X[1], sum(heights_rows[1:4])], [-widths_columns[1], sum(heights_rows[1:5])], 6)
bregionDonor1 = 1 # bottom boundary
bregionAcceptor2 = 2 # top boundary
bregionNoFlux = 3
bregionAirBox = 4
bfacemask!(grid, [-widths_columns[1], sum(heights_rows)], [widths_columns[1], sum(heights_rows)], bregionAcceptor2)
bfacemask!(grid, [X[1], 0.0], [X[end], 0.0], bregionDonor1)
bfacemask!(grid, [X[1], 0.0], [X[1], sum(heights_rows[1:4])], bregionNoFlux)
bfacemask!(grid, [X[1], sum(heights_rows[1:4])], [-widths_columns[1], sum(heights_rows[1:4])], bregionNoFlux)
bfacemask!(grid, [-widths_columns[1], sum(heights_rows[1:4])], [-widths_columns[1], sum(heights_rows)], bregionNoFlux)
bfacemask!(grid, [X[end], 0.0], [X[end], sum(heights_rows[1:4])], bregionNoFlux)
bfacemask!(grid, [widths_columns[1], sum(heights_rows[1:4])], [X[end], sum(heights_rows[1:4])], bregionNoFlux)
bfacemask!(grid, [widths_columns[1], sum(heights_rows[1:4])], [widths_columns[1], sum(heights_rows)], bregionNoFlux)
bfacemask!(grid, [X[1], sum(heights_rows[1:4])], [X[1], Y[end]], bregionAirBox)
bfacemask!(grid, [X[1], Y[end]], [-widths_columns[1], Y[end]], bregionAirBox)
bfacemask!(grid, [widths_columns[1], Y[end]], [X[end], Y[end]], bregionAirBox)
bfacemask!(grid, [X[end], sum(heights_rows[1:4])], [X[end], Y[end]], bregionAirBox)
if airbox == false
grid = subgrid(grid, [1, 2, 3, 4, 5])
end
if showplot == true
GridVisualize.gridplot(
grid, Plotter = PyPlot, linewidth = 1, fontsize = 35, size = (1200, 900),
legend = :best, show = true, aspect = 4, colorbar = false, title = "Device Geometry, values in [m]", xlabel = "x-coordinates", ylabel = "y-coordinates"
)
end
return grid
end
function main(;
refinement = 1, plotting = false, Plotter = PyPlot, verbose = "", test = false,
unknown_storage = :sparse, numberOfEigenvalues = 1,
parameter_set = Params_Laser_simple
) # choose the parameter setparameter
p = parameter_set()
################################################################################
if test == false
println("Set up grid.")
end
grid = tesca_grid(refinement = refinement, showplot = plotting, airbox = false)
if test == false
println("*** done\n")
end
################################################################################
if test == false
println("Define System and fill in information about model")
end
################################################################################
# Initialize Data instance and fill in data
data = Data(grid, p.numberOfCarriers, numberOfEigenvalues = numberOfEigenvalues)
# Possible choices: Stationary, Transient
data.modelType = Stationary
# Possible choices: Boltzmann, FermiDiracOneHalfBednarczyk, FermiDiracOneHalfTeSCA,
# FermiDiracMinusOne, Blakemore.
# Can be a vector with different statistics (for n and p).
data.F .= FermiDiracOneHalfTeSCA
data.bulkRecombination = set_bulk_recombination(;
iphin = p.iphin, iphip = p.iphip,
bulk_recomb_Auger = true,
bulk_recomb_radiative = true,
bulk_recomb_SRH = true
)
# Possible choices: OhmicContact, SchottkyContact (outer boundary) and InterfaceNone,
# InterfaceRecombination (inner boundary).
data.boundaryType[p.bregionAcceptor2] = OhmicContact # top boundary Dirichlet condition
data.boundaryType[p.bregionDonor1] = OhmicContact # bottom boundary Dirichlet condition # rest is set to Neumann by default data.fluxApproximation .= ExcessChemicalPotential
#data.fluxApproximation .= ScharfetterGummel # if F=Boltzmann
if test == false
println("*** done\n")
end
################################################################################
if test == false
println("Define Params and fill in physical parameters")
end
################################################################################
""" Data from Params_Laser_simple.jl: temperature T, band edge energies EC, EV, effective density of states NC, NV
mobilities μn, μp, dielectricConstant εs, radiative recombination r0, life times τn, τp,
Auger recombination coefficients Auger_Cn, Auger_Cp
doping doping (or vcat(Nd,Na) = doping).
"""
paramsoptical = ParamsOptical(grid, p.numberOfCarriers, numberOfEigenvalues)
paramsoptical.laserWavelength = p.λ
paramsoptical.absorption_0[:] = p.α0
paramsoptical.gain_0[:] = p.gain0
paramsoptical.refractiveIndex_0[:] = p.nTilde
paramsoptical.refractiveIndex_d[:] = p.nTilde_d
paramsoptical.refractiveIndex_γ[:] = p.γn
paramsoptical.absorptionFreeCarriers[p.iphin, :] = p.fcnalf
paramsoptical.absorptionFreeCarriers[p.iphip, :] = p.fcpalf
paramsoptical.eigenvalues .= 1 + 1 * im # dummy value for initializing
data.params = Params(p)
data.paramsoptical = paramsoptical
ctsys = System(grid, data, unknown_storage = unknown_storage)
if test == false
show_params(ctsys)
println("*** done\n")
end
################################################################################
if test == false
println("Define control parameters for Solver")
end
################################################################################
control = SolverControl()
control.verbose = verbose
control.maxiters = 300
control.abstol = 1.0e-7
control.reltol = 1.0e-7
control.tol_round = 1.0e-7
control.max_round = 3
control.damp_initial = 0.8 # < 1
#control.damp_growth = 1.21 # >= 1
if test == false
println("*** done\n")
end
################################################################################
if test == false
println("Compute solution in thermodynamic equilibrium for Boltzmann")
end
################################################################################
# calculate equilibrium solution and set as initial guess
psi0Vector = electroNeutralSolution(ctsys)
inival = unknowns(ctsys)
inival[1, :] = inival[2, :] .= 0.0
inival[3, :] = psi0Vector
solution = equilibrium_solve!(ctsys, inival = inival, control = control, nonlinear_steps = 20.0)
inival = solution
if test == false
println("*** done\n")
end
################################################################################
if test == false
println("Bias loop")
end
################################################################################
maxBias = p.U[end] # = 1.81 = topVoltageAcceptor2 # bias goes until the given voltage at acceptor boundary
biasValues = range(0, stop = maxBias, length = 40)
IV = zeros(0)
for Δu in biasValues
if test == false
println("bias value: Δu = ", Δu, " V")
end
# set non equilibrium boundary conditions
set_contact!(ctsys, p.bregionAcceptor2, Δu = Δu)
solution = solve(ctsys; inival = inival, control = control)
inival .= solution
end # bias loop
if test == false
println("*** done\n")
end
################################################################################
ctsys.data.paramsoptical.oldSolution = solution
currentSolution = solution
inival = solutioneigenvalue and eigenvector of the Helmholtz eigenvalue problem calculated explicitly
λ1 = [-5.6192359487570194e14 + 4.6950340673509827e11im]
v1 = [
-6.44693721037541e-8 + 2.1403391419628273e-8im,
-0.00016112043789318325 + 5.3345497772375895e-5im,
-0.04065180212557369 + 0.013461955814899604im,
-1.625774595841853e-5 + 5.383258567547116e-6im,
-0.00015713796062169245 + 6.309731311560341e-5im,
-0.03964667896215338 + 0.015922689828672086im,
-2.3324630277054376e-5 - 3.9545140054933005e-5im,
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0.0005919624102358168 + 0.0007767767309721376im,
0.14909867925795559 + 0.1961272646164019im,
0.003509519704937677 + 0.00023236831835518715im,
0.8850503810764251 + 0.059473291222819455im,
0.009849688910224585 - 0.00747820637205809im,
2.485408855146658 - 1.8845167715203734im,
0.013192949613002478 - 0.03461148153029405im,
3.3355658648998205 - 8.74169283250292im,
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]
v1 = reshape(v1, length(v1), 1) # reshaping because in system it must be a 2D array
############################
ctsys.data.paramsoptical.eigenvalues = λ1
ctsys.data.paramsoptical.eigenvectors = v1
ctsys.data.paramsoptical.power = p.P[2]
previousSolution = currentSolution
solution = solve(ctsys; inival = inival, control = control)
ctsys.data.paramsoptical.oldSolution = solution
currentSolution = solution
inival = solution
ctsys.data.paramsoptical.eigenvalues = λ1
ctsys.data.paramsoptical.eigenvectors = v1
ctsys.data.paramsoptical.power = p.P[2]
previousSolution = currentSolution
solution = solve(ctsys; inival = inival, control = control)
ctsys.data.paramsoptical.oldSolution = solution
currentSolution = solution
inival = solution
if plotting
vis = GridVisualizer(; Plotter = PyPlot, fignumber = 2, resolution = (1200, 900))
scalarplot!(
vis, grid, solution[1, :], Plotter = PyPlot, legend = :best, clear = false, title = "Applied voltage Δu = $maxBias V",
xlabel = "cross section space along \$x=0\$ [m]", ylabel = "potentials [V]", fontsize = 55, linewidth = 5,
slice = :x => 0, label = "\$ \\varphi_n \$", color = "blue"
)
scalarplot!(
vis, grid, solution[2, :], Plotter = PyPlot, linewidth = 5,
slice = :x => 0, label = "\$ \\varphi_p \$", clear = false, color = "mediumvioletred"
)
scalarplot!(
vis, grid, solution[3, :], Plotter = PyPlot, linewidth = 5,
slice = :x => 0, label = "\$ \\psi \$", clear = false, color = "darkorange"
)
end
testval = sum(solution) / length(solution)
return testval
end # main
function test()
testval = 0.5122451923673309
return main(test = true) ≈ testval
end
if test == false
println("This message should show when this module is successfully recompiled.")
end
end # moduleThis page was generated using Literate.jl.