1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160
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r"""
.. warning:: This model is not functioning correctly in SasView and it
appears it has not done so for some time. Whilst the
problem is investigated, a workaround for Case 0 below
(the most common use case) is to use the binary_blend
model available on the `Model Maketplace
<https://marketplace.sasview.org/models/124/>`_ . For further
information, please email help@sasview.org . *The
SasView Developers. February 2022.*
Definition
----------
Calculates the macroscopic scattering intensity for a multi-component
homogeneous mixture of polymers using the Random Phase Approximation.
This general formalism contains 10 specific cases
Case 0: C/D binary mixture of homopolymers
Case 1: C-D diblock copolymer
Case 2: B/C/D ternary mixture of homopolymers
Case 3: C/C-D mixture of a homopolymer B and a diblock copolymer C-D
Case 4: B-C-D triblock copolymer
Case 5: A/B/C/D quaternary mixture of homopolymers
Case 6: A/B/C-D mixture of two homopolymers A/B and a diblock C-D
Case 7: A/B-C-D mixture of a homopolymer A and a triblock B-C-D
Case 8: A-B/C-D mixture of two diblock copolymers A-B and C-D
Case 9: A-B-C-D tetra-block copolymer
.. note::
These case numbers are different from those in the NIST SANS package!
The models are based on the papers by Akcasu *et al.* [1] and by
Hammouda [2] assuming the polymer follows Gaussian statistics such
that $R_g^2 = n b^2/6$ where $b$ is the statistical segment length and $n$ is
the number of statistical segment lengths. A nice tutorial on how these are
constructed and implemented can be found in chapters 28, 31 and 34, and Part H,
of Hammouda's 'SANS Toolbox' [3].
In brief, the macroscopic cross sections are derived from the general forms
for homopolymer scattering and the multiblock cross-terms while the inter,
polymer cross terms are described in the usual way by the $\chi$ parameter.
USAGE NOTES:
* Only one case can be used at any one time.
* The RPA (mean field) formalism only applies only when the multicomponent
polymer mixture is in the homogeneous mixed-phase region.
* **Component D is assumed to be the "background" component (ie, all contrasts
are calculated with respect to component D).** So the scattering contrast
for a C/D blend $\rho_{C/D} = [\rho_C - \rho_D]$\ :sup:`2`.
* Depending on which case is being used, the number of fitting parameters can
vary.
.. Note::
* In general the degrees of polymerization, the volume
fractions, the molar volumes, and the neutron scattering lengths for each
component are obtained from other methods and held fixed while The *scale*
parameter should be held equal to unity.
* The variables are normally the segment lengths ($b_a$, $b_b$,
etc.) and $\chi$ parameters ($K_{ab}$, $K_{ac}$, etc).
References
----------
#. A Z Akcasu, R Klein and B Hammouda, *Macromolecules*, 26 (1993) 4136
#. B. Hammouda, *Advances in Polymer Science* 106 (1993) 87
#. B. Hammouda, *SANS Toolbox*
https://www.ncnr.nist.gov/staff/hammouda/the_sans_toolbox.pdf.
Authorship and Verification
----------------------------
* **Author:** Boualem Hammouda - NIST IGOR/DANSE **Date:** pre 2010
* **Converted to sasmodels by:** Paul Kienzle **Date:** July 18, 2016
* **Last Modified by:** Paul Butler **Date:** March 12, 2017
* **Last Reviewed by:** Steve King **Date:** March 27, 2019
"""
from numpy import inf
name = "rpa"
title = "Random Phase Approximation"
description = """
This formalism applies to multicomponent polymer mixtures in the
homogeneous (mixed) phase region only.
Case 0: C/D binary mixture of homopolymers
Case 1: C-D diblock copolymer
Case 2: B/C/D ternary mixture of homopolymers
Case 3: B/C-D mixture of homopolymer b and diblock copolymer C-D
Case 4: B-C-D triblock copolymer
Case 5: A/B/C/D quaternary mixture of homopolymers
Case 6: A/B/C-D mixture of two homopolymers A/B and a diblock C-D
Case 7: A/B-C-D mixture of a homopolymer A and a triblock B-C-D
Case 8: A-B/C-D mixture of two diblock copolymers A-B and C-D
Case 9: A-B-C-D four-block copolymer
See details in the model function help
"""
category = "shape-independent"
CASES = [
"C+D binary mixture",
"C:D diblock copolymer",
"B+C+D ternary mixture",
"B+C:D binary mixture",
"B:C:D triblock copolymer",
"A+B+C+D quaternary mixture",
"A+B+C:D ternary mixture",
"A+B:C:D binary mixture",
"A:B+C:D binary mixture",
"A:B:C:D quadblock copolymer",
]
# ["name", "units", default, [lower, upper], "type","description"],
parameters = [
["case_num", "", 1, [CASES], "", "Component organization"],
["N[4]", "", 1000.0, [1, inf], "", "Degree of polymerization"],
["Phi[4]", "", 0.25, [0, 1], "", "volume fraction"],
["v[4]", "mL/mol", 100.0, [0, inf], "", "molar volume"],
["L[4]", "fm", 10.0, [-inf, inf], "", "scattering length"],
["b[4]", "Ang", 5.0, [0, inf], "", "segment length"],
["K12", "", -0.0004, [-inf, inf], "", "A:B interaction parameter"],
["K13", "", -0.0004, [-inf, inf], "", "A:C interaction parameter"],
["K14", "", -0.0004, [-inf, inf], "", "A:D interaction parameter"],
["K23", "", -0.0004, [-inf, inf], "", "B:C interaction parameter"],
["K24", "", -0.0004, [-inf, inf], "", "B:D interaction parameter"],
["K34", "", -0.0004, [-inf, inf], "", "C:D interaction parameter"],
]
source = ["rpa.c"]
single = False
control = "case_num"
HIDE_ALL = set("Phi4".split())
HIDE_A = set("N1 Phi1 v1 L1 b1 K12 K13 K14".split()).union(HIDE_ALL)
HIDE_AB = set("N2 Phi2 v2 L2 b2 K23 K24".split()).union(HIDE_A)
def hidden(case_num):
"""
Return a list of parameters to hide depending on the multiplicity parameter.
"""
case_num = int(case_num+0.5)
if case_num < 2:
return HIDE_AB
elif case_num < 5:
return HIDE_A
else:
return HIDE_ALL
# TODO: no random parameters generated for RPA
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