The SAG equation

    The SAG equation is a diffusion Fick equation of a specie c: \displaystyle \frac{\partial c}{\partial t} =\nabla^2 c with boundary condition of cristal growth on the substrat \frac{\partial c}{\partial y} = bi\; c on y=0 (bi is a kind of Biot number) and no growth \frac{\partial c}{\partial y} = 0 on y=0 on the mask and far from the wall, there is a constant arrival of species c(x,top)=1, right and left are periodic conditions (periodicity is here a symmetry).

    This system can be solved with the reaction–diffusion solver.

    #include "grid/multigrid.h"
    #include "run.h"
    #include "diffusion.h"
    #define MAXLEVEL 10
    #define MINLEVEL 5

    Concentration at time t+dt, t and flux, and some obvious variables

    scalar c[],cold[],dc[],flux[],dce[];
    double beta,bi,w,tmax,dx,errmax;

    The generic time loop needs a timestep. We will store the statistics on the diffusion solvers in mgd.

    double dt;
    mgstats mgd;

    the exact solution without mask

    double cexact(double y)
    { double ce;
        ce = (bi*y+1)/(bi*L0+1);
        return ce;

    Boundary conditions: a given concentration at the top, no reaction on the mask (no flux: \partial c(t)/\partial y=0), a complete reaction on the cristal (|x| < w) \partial c(t)/\partial y = bi\; c(t) this mixed condition is written (c[0,0]-c[bottom])/Delta = bi (c[0,0] + c[bottom])/2

    c[top]    =  dirichlet(1);
    //c[bottom] = (fabs(x)<w)? neumann(0) :  c[]*(2.-bi*Delta)/(2.+bi*Delta) ;

    problem with mixed

    c[bottom] = (fabs(x)<w)? neumann(0) : val(_s,0)*(2.-bi*Delta)/(2.+bi*Delta)   ; 
    c[right]  =  neumann(0);
    c[left]   =  neumann(0);


    The size of the domain L0.

    int main() {
        beta = 1;
        L0 = 10.;
        X0 = -L0/2;
        Y0 = 0;
        N =  256;
        dx = L0/N;
        tmax = 100;
        errmax = 5.e-4;

    the chemical Biot number and the width of the mask

        bi = 1.;
        w = 1;

    Initial conditions

    a constant amount of concentration

    event init (i = 0) {
        foreach() {
        boundary ({c,cold});

    Time integration

    We first set the timestep according to the timing of upcoming events. We choose a maximum timestep of 0.2 which ensures the stability of the reactive terms for this example.

        dt = dtnext (dt);

    We use the diffusion solver to advance the system from t to t+dt.

        scalar r[],lambda[];
        foreach() {
            r[] = 0;
            lambda[] = 0;

    solving \displaystyle \nabla^2 c^{n+1} + (\lambda -\frac{1}{\Delta t}) c^{n+1} + r +\frac{1}{\Delta t} c^{n}= 0

        mgd = diffusion (c, dt, r = r, beta = lambda);
        boundary ({cold});

    The flux along y is {\partial c}{\partial y}

        flux[] =  ( c[0,0] - c[0,-1] )/Delta;
        boundary ({flux});

    end when converged

        double err= sqrt(normf(dc).max);
        fprintf (stdout," %lf %lf\n",t,sqrt(normf(dc).max));
         if((t>1)&&(err < errmax)) {  fprintf (stdout,"stop convergence \n"); exit(1);}


    Here we create mpeg animations

    event movies (i += 3; t <= tmax) { fprintf (stderr, “%g %g”, t, sqrt(normf(dc).max)); foreach() dce[] = c[] -cexact(y); static FILE * fp = popen (“ppm2mpeg > c.mpg”, “w”); output_ppm (dce, fp, spread = 2, linear = true);

    static FILE * fp1 = popen (“ppm2mpeg > level.mpg”, “w”); scalar l = dce; foreach() l[] = level; output_ppm (l, fp1, min = MINLEVEL, max = MAXLEVEL, n = 512);


    print data saves along

    event printdata (t +=1;t<=tmax) {
        FILE *  fpx = fopen("cutx.txt", "w");
        FILE *  fpy = fopen("cuty.txt", "w");
        //   static double dx = L0/512;
        for (double x = -L0/2 ; x < L0/2; x += dx){
            double y=x+L0/2;
            fprintf (fpx, "%g %g %g \n",
                     x, interpolate (c, x, 0) , interpolate (flux, x, 0.));
            fprintf (fpy, "%g %g %g \n",
                     y, interpolate (c, 0, y) , interpolate (flux, 0, y));}

    At the end of the simulation, we create snapshot images of the field, in PNG format.

    event pictures (t +=1) {
        scalar  dce[];
        dce[] =  c[] -cexact(y);
        boundary ({dce});
        output_ppm (dce, file = "c.png", spread = 2, linear = true);

    We can now use wavelet adaptation. The function then returns the number of cells refined.

    event adapt(i++) {
    #if QUADTREE
        astats s = adapt_wavelet ({dce}, (double[]){.001},
                                  MAXLEVEL, MINLEVEL);
        fprintf (stderr, "# refined %d cells, coarsened %d cells\n",,;
    #else // Cartesian
        return 0;


    Then compile and run:

     rm sag; qcc  -g -O2 -DTRASH=1 -Wall  sag.c -o sag ; ./sag

    or better

     make sag.tst;make sag/plots    
     make sag.c.html ; open sag.c.html 


    compare a cut in x=0, exact solution and computed

     set output 'cuty.png'
     set xlabel "y"
     set key left
     p[:][:]'./cuty.txt'u 1:($2) t 'c'w l,''u 1:3 t'dc/dy' w l,bi/(bi*L0+1.) t 'bi/(bi L0+1)',(bi*x+1)/(bi*L0+1) t'(bi y+1)/(bi*L0+1)'
    cut in x=0 (script)

    cut in x=0 (script)

    compare a cut in y=0, concentration en flux dived by the reference flux bi/(bi L0+1)

     set output 'cutx.png'
     set xlabel "x"
     p'./cutx.txt'u 1:($2*(bi*L0+1)) t'concentration' w l,''u 1:($3*(bi*L0+1)/bi) t'flux' w l,1 not
    cut in y=0 (script)

    cut in y=0 (script)

    Field of c:



    • N. Dupuis, J. Décobert, P.-Y. Lagrée, N. Lagay, D. Carpentier, F. Alexandre (2008): “Demonstration of planar thick InP layers by selective MOVPE”. Journal of Crystal Growth issue 23, 15 November 2008, Pages 4795-4798

    • N. Dupuis, J. Décobert, P.-Y. Lagrée , N. Lagay, C. Cuisin, F. Poingt, C. Kazmierski, A. Ramdane, A. Ougazzaden (2008): “Mask pattern interference in AlGaInAs MOVPE Selective Area Growth : experimental and modeling analysis”. Journal of Applied Physics 103, 113113 (2008)

    Version 1: may 2014, ready for new site 09/05/19