def get_sample(): """ Returns a sample with cylinders in a homogeneous medium ("Vacuum"). The cylinders are a 95:5 mixture of two different size distributions. """ # defining materials m_vacuum = ba.HomogeneousMaterial("Vacuum", 0.0, 0.0) m_particle = ba.HomogeneousMaterial("Particle", 6e-4, 2e-8) # collection of particles #1 radius1 = 5.0 * nm height1 = radius1 sigma1 = radius1 * 0.2 cylinder_ff1 = ba.FormFactorCylinder(radius1, height1) cylinder1 = ba.Particle(m_particle, cylinder_ff1) gauss_distr1 = ba.DistributionGaussian(radius1, sigma1) nparticles = 150 sigma_factor = 3.0 # limits will assure, that generated Radius'es are >=0 limits = ba.RealLimits.nonnegative() par_distr1 = ba.ParameterDistribution("/Particle/Cylinder/Radius", gauss_distr1, nparticles, sigma_factor, limits) part_coll1 = ba.ParticleDistribution(cylinder1, par_distr1) # collection of particles #2 radius2 = 10.0 * nm height2 = radius2 sigma2 = radius2 * 0.02 cylinder_ff2 = ba.FormFactorCylinder(radius2, height2) cylinder2 = ba.Particle(m_particle, cylinder_ff2) gauss_distr2 = ba.DistributionGaussian(radius2, sigma2) par_distr2 = ba.ParameterDistribution("/Particle/Cylinder/Radius", gauss_distr2, nparticles, sigma_factor, limits) part_coll2 = ba.ParticleDistribution(cylinder2, par_distr2) # assembling the sample particle_layout = ba.ParticleLayout() particle_layout.addParticle(part_coll1, 0.95) particle_layout.addParticle(part_coll2, 0.05) vacuum_layer = ba.Layer(m_vacuum) vacuum_layer.addLayout(particle_layout) multi_layer = ba.MultiLayer() multi_layer.addLayer(vacuum_layer) return multi_layer
def getSample(): # Defining Materials material_2 = ba.HomogeneousMaterial("Si", 7.6e-06, 1.7e-07) material_1 = ba.HomogeneousMaterial("Air", 0.0, 0.0) # Defining Layers layer_1 = ba.Layer(material_1) layer_2 = ba.Layer(material_2) # Defining Form Factors formFactor_1 = ba.FormFactorCylinder(5.0 * nm, 5.0 * nm) # Defining Particles particle_1 = ba.Particle(material_2, formFactor_1) # Defining particles with parameter following a distribution distr_1 = ba.DistributionGaussian(5.0, 1.0) par_distr_1 = ba.ParameterDistribution("/Particle/Cylinder/Radius", distr_1, 10, 2.0) par_distr_1.linkParameter("/Particle/Cylinder/Height") particleDistribution_1 = ba.ParticleDistribution(particle_1, par_distr_1) # Defining Particle Layouts and adding Particles layout_1 = ba.ParticleLayout() layout_1.addParticle(particleDistribution_1, 1.0) layout_1.setTotalParticleSurfaceDensity(1) # Adding layouts to layers layer_1.addLayout(layout_1) # Defining Multilayers multiLayer_1 = ba.MultiLayer() multiLayer_1.addLayer(layer_1) multiLayer_1.addLayer(layer_2) return multiLayer_1
def create_layout(self, particle_material): layout = ba.ParticleLayout() radius = 5.02 nparticles = 100 sigma = 0.3 gauss_distr = ba.DistributionGaussian(radius, sigma) # scale_param = math.sqrt(math.log((sigma / radius) ** 2 + 1.0)) # gauss_distr = ba.DistributionLogNormal(radius, scale_param) particle = ba.Particle(particle_material, ba.FormFactorFullSphere(radius)) sigma_factor = 2.0 par_distr = ba.ParameterDistribution("/Particle/FullSphere/Radius", gauss_distr, nparticles, sigma_factor) part_coll = ba.ParticleDistribution(particle, par_distr) layout.addParticle(part_coll, 1.0, ba.kvector_t(0, 0, -self.m_average_layer_thickness)) for i in range(0, 100): radius = npr.normal(5.0, 0.3) if radius < 4.0 or radius > 6.0: pass particle = ba.Particle(particle_material, ba.FormFactorFullSphere(radius)) zbot = -self.m_average_layer_thickness pos = random_gate(zbot, zbot + 50) layout.addParticle(particle, 0.05, ba.kvector_t(0, 0, pos)) layout.setTotalParticleSurfaceDensity(0.002) return layout
def create_diffuse_layout(particle_material, average_layer_thickness): """ Createss layout with mesocrystal collection. """ m_radius = 5.02 m_nparticles = 100 m_sigma = 0.5 m_diffuse_surface_density = 1e-2 layout = ba.ParticleLayout() distr = ba.DistributionGaussian(m_radius, m_sigma) # scale_param = math.sqrt(math.log((m_sigma / m_radius) ** 2 + 1.0)) # distr = ba.DistributionLogNormal(m_radius, scale_param) particle = ba.Particle(particle_material, ba.FormFactorFullSphere(m_radius)) sigma_factor = 3.0 par_distr = ba.ParameterDistribution("/Particle/FullSphere/Radius", distr, m_nparticles, sigma_factor) part_coll = ba.ParticleDistribution(particle, par_distr) layout.addParticle(part_coll, 1.0, ba.kvector_t(0, 0, -average_layer_thickness + 10)) layout.setTotalParticleSurfaceDensity(m_diffuse_surface_density) return layout
def get_simulation(): """ Returns a GISAXS simulation with beam (+ divergence) and detector defined. """ simulation = ba.GISASSimulation() simulation.setDetectorParameters(100, 0.0 * deg, 2.0 * deg, 100, 0.0 * deg, 2.0 * deg) simulation.setBeamParameters(1.0 * angstrom, 0.2 * deg, 0.0 * deg) wavelength_distr = ba.DistributionLogNormal(1.0 * angstrom, 0.1) alpha_distr = ba.DistributionGaussian(0.2 * deg, 0.1 * deg) phi_distr = ba.DistributionGaussian(0.0 * deg, 0.1 * deg) simulation.addParameterDistribution("*/Beam/Wavelength", wavelength_distr, 5) simulation.addParameterDistribution("*/Beam/InclinationAngle", alpha_distr, 5) simulation.addParameterDistribution("*/Beam/AzimuthalAngle", phi_distr, 5) return simulation
def get_simulation(): """ Returns a specular simulation with beam and detector defined. """ # First argument of ba.DistributionGaussian is # the mean value for distribution. # It should be zero in the case of incident angle distribution, # otherwise an exception is thrown. alpha_distr = ba.DistributionGaussian(0.0, d_ang) wavelength_distr = ba.DistributionGaussian(wavelength, d_wl) simulation = ba.SpecularSimulation() simulation.setBeamParameters(wavelength, n_bins, alpha_i_min, alpha_i_max) simulation.addParameterDistribution("*/Beam/InclinationAngle", alpha_distr, n_points, n_sig) simulation.addParameterDistribution("*/Beam/Wavelength", wavelength_distr, n_points, n_sig) return simulation
def add_beam_divergence(simulation, wavelength): """ Adds beam divergence to the simulation """ # beam divergence parameters d_wl = 0.01 * wavelength # spread width for wavelength d_ang = 0.01 * ba.deg # spread width for incident angle n_sig = 3 # number of standard deviations to take into account n_points = 25 # number of points to take in parameter distribution # creating beam parameter distributions alpha_distr = ba.DistributionGaussian(0.0, d_ang) wavelength_distr = ba.DistributionGaussian(wavelength, d_wl) # adding distributions to the simulation simulation.addParameterDistribution("*/Beam/InclinationAngle", alpha_distr, n_points, n_sig) simulation.addParameterDistribution("*/Beam/Wavelength", wavelength_distr, n_points, n_sig)
def getSimulation(): simulation = ba.GISASSimulation() simulation.setDetectorParameters(200, -2.0 * deg, 2.0 * deg, 200, 0.0 * deg, 2.0 * deg) simulation.setBeamParameters(0.154 * nm, 0.2 * deg, 0.0 * deg) simulation.setBeamIntensity(1.0e+08) distribution_1 = ba.DistributionGaussian(0.00349065850399, 0.00174532925199) simulation.addParameterDistribution("*/Beam/InclinationAngle", distribution_1, 10, 2.0) return simulation
def get_simulation(): """ Returns a depth-probe simulation. """ alpha_distr = ba.DistributionGaussian(0.0, d_ang) footprint = ba.FootprintFactorSquare(beam_sample_ratio) simulation = ba.DepthProbeSimulation() simulation.setBeamParameters(wl, n_ai_bins, ai_min, ai_max, footprint) simulation.setZSpan(n_z_bins, z_min, z_max) simulation.addParameterDistribution("*/Beam/InclinationAngle", alpha_distr, n_points, n_sig) return simulation
def get_simulation(): """ Returns a depth-probe simulation. """ footprint = ba.FootprintFactorSquare(beam_sample_ratio) simulation = ba.DepthProbeSimulation() simulation.setBeamParameters(wl, n_ai_bins, ai_min, ai_max, footprint) simulation.setZSpan(n_z_bins, z_min, z_max) fwhm2sigma = 2 * np.sqrt(2 * np.log(2)) # add angular beam divergence alpha_distr = ba.DistributionGaussian(0.0, d_ang / fwhm2sigma) simulation.addParameterDistribution("*/Beam/InclinationAngle", alpha_distr, n_points, n_sig) # add wavelength divergence wl_distr = ba.DistributionGaussian(wl, d_wl / fwhm2sigma) simulation.addParameterDistribution("*/Beam/Wavelength", wl_distr, n_points_wl, n_sig_wl) return simulation
def create_simulation(arg_dict, bin_start, bin_end): """ Creates and returns specular simulation """ simulation = ba.SpecularSimulation() alpha_distr = ba.DistributionGaussian(0.0, arg_dict["divergence"]) footprint = ba.FootprintFactorGaussian(arg_dict["footprint_factor"]) simulation.setBeamParameters(1.54 * ba.angstrom, get_real_data_axis(bin_start, bin_end), footprint) simulation.setBeamIntensity(arg_dict["intensity"]) simulation.addParameterDistribution("*/Beam/InclinationAngle", alpha_distr, 30, 3) return simulation
def get_simulation(): """ Create and return GISAXS simulation with beam and detector defined """ simulation = ba.GISASSimulation() simulation.setDetectorParameters(200, -1.0 * deg, 1.0 * deg, 200, 0.0 * deg, 1.0 * deg) simulation.setBeamParameters(1.0 * angstrom, 0.2 * deg, 0.0 * deg) # add rotational distribution for lattice xi_distr = ba.DistributionGaussian(60.0 * deg, 30.0 * deg / 2.355) simulation.addParameterDistribution("*/Xi", xi_distr, 10, 4) return simulation
def get_simulation(ai=0.56, u0=45.3, v0=29.9): """ Returns a GISAXS simulation with beam and detector defined wavelength 12.8 angstrom incident angle 0.0 degrees (transmission) """ simulation = ba.GISASSimulation() simulation.setBeamParameters(12.8 * ba.angstrom, ai * ba.deg, 0.0 * ba.deg) simulation.setDetector(get_kws3_detector(u0, v0)) simulation.setDetectorResolutionFunction( ba.ResolutionFunction2DGaussian(5.0, 5.0)) simulation.setBeamIntensity(1000) distr_1 = ba.DistributionGaussian(1.28 * ba.nm, 0.1) simulation.addParameterDistribution("*/Beam/Wavelength", distr_1, 50, 2.0, ba.RealLimits.positive()) simulation.getOptions().setIncludeSpecular(True) return simulation
def create_diffuse_layout(self): layout = ba.ParticleLayout() radius = 5.0 nparticles = 100 sigma = 0.3 * radius gauss_distr = ba.DistributionGaussian(radius, sigma) particle = ba.Particle(self.m_adapted_particle_material, ba.FormFactorFullSphere(radius)) sigma_factor = 2.0 par_distr = ba.ParameterDistribution("/Particle/FullSphere/Radius", gauss_distr, nparticles, sigma_factor) part_coll = ba.ParticleDistribution(particle, par_distr) layout.addParticle( part_coll, 1.0, ba.kvector_t( 0, 0, -self.m_average_layer_thickness + self.m_meso_elevation)) layout.setTotalParticleSurfaceDensity(0.005) return layout
def get_sample(): """ Return a sample with cylinders on a substrate. The cylinders have a Gaussian size distribution. """ m_ambience = ba.HomogeneousMaterial("Air", 0.0, 0.0) m_particle = ba.HomogeneousMaterial("Particle", 6e-4, 2e-8) # cylindrical particle radius = 5 * nm height = radius cylinder_ff = ba.FormFactorCylinder(radius, height) cylinder = ba.Particle(m_particle, cylinder_ff) # collection of particles with size distribution nparticles = 100 sigma = 0.2 * radius gauss_distr = ba.DistributionGaussian(radius, sigma) sigma_factor = 2.0 par_distr = ba.ParameterDistribution("/Particle/Cylinder/Radius", gauss_distr, nparticles, sigma_factor) # by uncommenting the line below, the height of the cylinders # can be scaled proportionally to the radius: # par_distr.linkParameter("/Particle/Cylinder/Height") part_coll = ba.ParticleDistribution(cylinder, par_distr) # assembling the sample particle_layout = ba.ParticleLayout() particle_layout.addParticle(part_coll) air_layer = ba.Layer(m_ambience) air_layer.addLayout(particle_layout) multi_layer = ba.MultiLayer() multi_layer.addLayer(air_layer) return multi_layer
def get_sample(): """ Returns a sample """ # defining materials m_si = ba.MaterialBySLD("Si", sld_Si, sld_Si_im) m_d2o = ba.MaterialBySLD("D2O", sld_D2O, sld_D2O_im) m_core = ba.MaterialBySLD("Me3O5:D2O2", 2.0 * 1.0e-06, 0.0) m_shell = ba.MaterialBySLD("Me3O5:D2O", 3.9 * 1.0e-06, 0.0) # layer with particles # calculate average SLD Vcore = vol(core_radius, core_height) Vshell = vol(radius, height) - Vcore f_d2o = 0.7 f_core = (1.0 - f_d2o) / (1 + Vshell / Vcore) f_shell = (1.0 - f_d2o) / (1 + Vcore / Vshell) sld_mix = f_d2o * sld_D2O + f_shell * 3.9 * 1.0e-06 + f_core * 2.0 * 1.0e-06 m_mix = ba.MaterialBySLD("mix", sld_mix, 0.0) # fluctuation component ff_microgel = FormFactorMicrogel(b, xi, xiz) microgel = ba.Particle(m_core, ff_microgel) microgel_layout = ba.ParticleLayout() microgel_layout.addParticle(microgel, 1.0) # collection of particles ff = ba.FormFactorTruncatedSphere(radius=radius, height=height) ff_core = ba.FormFactorTruncatedSphere(radius=core_radius, height=core_height) transform = ba.RotationY(180.0 * deg) shell_particle = ba.Particle(m_shell, ff) core_particle = ba.Particle(m_core, ff_core) core_position = ba.kvector_t(0.0, 0.0, 0.0) particle = ba.ParticleCoreShell(shell_particle, core_particle, core_position) particle.setPosition(ba.kvector_t(0.0, 0.0, 0.0)) particle.setRotation(transform) nparticles = 2 # the larger is this number, the more slow will be the simulation. 10 is usually enough sigma = 0.2 * radius gauss_distr = ba.DistributionGaussian(radius, sigma) sigma_factor = 2.0 par_distr = ba.ParameterDistribution( "/ParticleCoreShell/Particle1/TruncatedSphere/Radius", gauss_distr, nparticles, sigma_factor, ba.RealLimits.lowerLimited(core_radius + 1.0)) par_distr.linkParameter( "/ParticleCoreShell/Particle1/TruncatedSphere/Height") par_distr.linkParameter( "/ParticleCoreShell/Particle0/TruncatedSphere/Height") par_distr.linkParameter( "/ParticleCoreShell/Particle0/TruncatedSphere/Radius") part_coll = ba.ParticleDistribution(particle, par_distr) microgel_layout.addParticle(part_coll, 1.2e-05) # interference can be neglected interference = ba.InterferenceFunctionNone() microgel_layout.setInterferenceFunction(interference) # describe layer roughness roughness = ba.LayerRoughness() roughness.setSigma(1.2 * ba.nm) roughness.setHurstParameter(0.8) roughness.setLatteralCorrLength(570.0 * ba.nm) # create layers d2o_layer = ba.Layer(m_d2o) mix_layer = ba.Layer(m_mix, 2.0 * height) mix_layer.addLayout(microgel_layout) si_layer = ba.Layer(m_si) multi_layer = ba.MultiLayer() multi_layer.addLayer(si_layer) multi_layer.addLayer(mix_layer) multi_layer.addLayerWithTopRoughness(d2o_layer, roughness) return multi_layer