r""" .. _core_shell_sphere: This model provides the form factor, $P(q)$, for a spherical particle with a core-shell structure. The form factor is normalized by the particle volume. For information about polarised and magnetic scattering, see the :ref:`magnetism` documentation. Definition ---------- The 1D scattering intensity is calculated in the following way (Guinier, 1955) .. math:: P(q) = \frac{\text{scale}}{V} F^2(q) + \text{background} where .. math:: F(q) = \frac{3}{V_s}\left[ V_c(\rho_c-\rho_s)\frac{\sin(qr_c)-qr_c\cos(qr_c)}{(qr_c)^3} + V_s(\rho_s-\rho_\text{solv})\frac{\sin(qr_s)-qr_s\cos(qr_s)}{(qr_s)^3} \right] where $V_s$ is the volume of the whole particle, $V_c$ is the volume of the core, $r_s$ = $radius$ + $thickness$ is the radius of the particle, $r_c$ is the radius of the core, $\rho_c$ is the scattering length density of the core, $\rho_s$ is the scattering length density of the shell, $\rho_\text{solv}$, is the scattering length density of the solvent. The 2D scattering intensity is the same as $P(q)$ above, regardless of the orientation of the $q$ vector. NB: The outer most radius (ie, = radius + thickness) is used as the effective radius for $S(Q)$ when $P(Q) \cdot S(Q)$ is applied. Validation ---------- Validation of our code was done by comparing the output of the 1D model to the output of the software provided by NIST (Kline, 2006). Figure 1 shows a comparison of the output of our model and the output of the NIST software. References ---------- .. [#] A Guinier and G Fournet, *Small-Angle Scattering of X-Rays*, John Wiley and Sons, New York, (1955) Source ------ `core_shell_sphere.py `_ `core_shell_sphere.c `_ Authorship and Verification ---------------------------- * **Author:** * **Last Modified by:** * **Last Reviewed by:** * **Source added by :** Steve King **Date:** March 25, 2019 """ import numpy as np from numpy import pi, inf name = "core_shell_sphere" title = "Form factor for a monodisperse spherical particle with particle with a core-shell structure." description = """ F(q) = [V_c (sld_core-sld_shell) 3 (sin(q*radius)-q*radius*cos(q*radius))/(q*radius)^3 + V_s (sld_shell-sld_solvent) 3 (sin(q*r_s)-q*r_s*cos(q*r_s))/(q*r_s)^3] V_s: Volume of the sphere shell V_c: Volume of the sphere core r_s: Shell radius = radius + thickness """ category = "shape:sphere" # pylint: disable=bad-whitespace, line-too-long # ["name", "units", default, [lower, upper], "type","description"], parameters = [["radius", "Ang", 60.0, [0, inf], "volume", "Sphere core radius"], ["thickness", "Ang", 10.0, [0, inf], "volume", "Sphere shell thickness"], ["sld_core", "1e-6/Ang^2", 1.0, [-inf, inf], "sld", "core scattering length density"], ["sld_shell", "1e-6/Ang^2", 2.0, [-inf, inf], "sld", "shell scattering length density"], ["sld_solvent", "1e-6/Ang^2", 3.0, [-inf, inf], "sld", "Solvent scattering length density"]] # pylint: enable=bad-whitespace, line-too-long source = ["lib/sas_3j1x_x.c", "lib/core_shell.c", "core_shell_sphere.c"] have_Fq = True radius_effective_modes = ["outer radius", "core radius"] demo = dict(scale=1, background=0, radius=60, thickness=10, sld_core=1.0, sld_shell=2.0, sld_solvent=0.0) def random(): """Return a random parameter set for the model.""" outer_radius = 10**np.random.uniform(1.3, 4.3) # Use a distribution with a preference for thin shell or thin core # Avoid core,shell radii < 1 radius = np.random.beta(0.5, 0.5)*(outer_radius-2) + 1 thickness = outer_radius - radius pars = dict( radius=radius, thickness=thickness, ) return pars tests = [ [{'radius': 20.0, 'thickness': 10.0}, 0.1, None, None, 30.0, 4.*pi/3*30**3, 1.0], # The SasView test result was 0.00169, with a background of 0.001 [{'radius': 60.0, 'thickness': 10.0, 'sld_core': 1.0, 'sld_shell': 2.0, 'sld_solvent': 3.0, 'background': 0.0}, 0.4, 0.000698838], ]