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Rectangular grating

Result

Rectangular grating result

Sample

Rectangular grating sample

Python script

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#!/usr/bin/env python3
# /// script
# requires-python = ">=3.10"
# dependencies = ["bornagain>=25,<26"]
# ///
"""
Simulation of grating using very long boxes and 1D lattice.
Monte-carlo integration is used to get rid of
large-particle form factor oscillations.
"""
import bornagain as ba
ba.require_versions("bornagain>=25,<26")
from bornagain import deg, micrometer, nm


def get_sample(lattice_rotation_angle=0*deg):
    """
    A sample with a grating on a substrate.
    lattice_rotation_angle = 0 - beam parallel to grating lines
    lattice_rotation_angle = 90*deg - beam perpendicular to grating lines
    """
    # Materials
    vacuum = ba.Vacuum()
    si_color = (0.30, 0.62, 0.86)
    si_mat = ba.RefractiveMaterial("Si", si_color, 5.7816e-6, 1.0229e-7)

    box_length, box_width, box_height = 50*micrometer, 70*nm, 50*nm
    lattice_length = 150*nm

    box_ff = ba.LongBoxLorentz(box_length, box_width, box_height)
    box = ba.Particle(si_mat, box_ff)
    box.rotate(ba.RotationZ(lattice_rotation_angle))

    # Particle layout
    layout = ba.Crystal1D(box, lattice_length,
                          90*deg - lattice_rotation_angle,
                          1/box_length)
    profile = ba.Profile1DGauss(450)
    layout.setDecayFunction(profile)

    sigma, hurst, corrLength = 5*nm, 0.5, 10*nm
    autocorr = ba.SelfAffineFractalModel(sigma, hurst, corrLength)
    transient = ba.TanhTransient()
    roughness = ba.Roughness(autocorr, transient)

    # Sample
    vacuum_layer = ba.Layer(vacuum)
    vacuum_layer.deposit2D(layout)
    substrate_layer = ba.Layer(si_mat, roughness)

    sample = ba.Sample()
    sample.addLayer(vacuum_layer)
    sample.addLayer(substrate_layer)
    return sample


def get_simulation(sample):
    beam = ba.Beam(1e8, 0.134*nm, 0.4*deg)
    n = 200
    detector = ba.SphericalDetector(n, -0.5*deg, 0.5*deg, n, 0, 0.5*deg)
    simulation = ba.ScatteringSimulation(beam, sample, detector)
    simulation.options().setMonteCarloIntegration(True, 100, seed=0)
    return simulation


if __name__ == '__main__':
    sample = get_sample()
    ba.showSample3D(sample, sample_size=1500*nm, seed=0)
    simulation = get_simulation(sample)
    result = simulation.simulate()
    ba.plot_datafield(result, unit_aspect=1)
    ba.plt.show()
auto/Examples/gisas/order/RectangularGrating.py