Random copolymer adsorption
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Transcript of Random copolymer adsorption
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Random copolymer adsorption
E. Orlandini, Dipartimento di Fisica and Sezione CNR-INFM, Universit`a di Padova
C.E. Soteros, Department of Mathematics and Statistics, University of Saskatchewan
S.G. Whittington, Department of Chemistry, University of Toronto
Juan AlvarezDepartment of Mathematics and Statistics, University of
Saskatchewan
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• Dilute solution (polymer-polymer interactions can be ignored).
• System in equilibrium.
• Polymer's conformations: self-avoiding walks, Motzkin paths, Dyck paths.
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• Degree of polymerization: n
• Two types of monomers: A and B.– Monomer sequence (colouring) is random.– i is colour of monomer i (i =1 → A)– i.i.d. Bernoulli random variables, P(i=1) = p
• Energy of conformation for fixed colour : – E(|) = -nA,S.– = - 1/kT
– nA,S : number of A monomers at the surface.
• Conformations with same energy are equally likely, so
– cn(nA,S|): number of walks with nA,S vertices coloured A at the surface.
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• Intensive free energy at fixed :
• Quenched average free energy :
• Limiting quenched average free energy (exists):
– Indicates if polymer prefers desorbed or adsorbed phase.
– As → ∞ , asymptotic to a line with slope• Q: What is the value of q ?• Q: What is for > q?
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• Annealed average free energy:
• Limiting annealed average free energy:
• So,
• As → ∞ , is asymptotic to a line with slope
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The Morita Approximation (Constrained Annealing)
• Consider the constrained annealed average free energy
with the Lagrangian
• Minimization of with respect to C constrains
• Mazo (1963), Morita (1964), and Kuhn (1996) showed that can be obtained as the solution to
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• Setting some ’s to zero and minimizing to obtain yields an upper bound on .
– In particular, we obtain
and so
– e.g., • annealed
• 1st order Morita:
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• Minimization to obtain is quite complex.
• Upper bound it by
– Consider the grand canonical partition function
– with radius of convergence .
– We obtain
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• G in terms of a homopolymer generating function B
– B keeps track of the number of segments of the path that have the same sequence of surface touches.
– Obtained via factorization, • e.g., dn: number of n-step Dyck paths.
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• G in terms of a homopolymer generating function B
– B keeps track of the number of segments of the path that have the same sequence of surface touches.
• The radii of convergence are related by• where
– – z1: branch cut from the desorbed phase (square root)– the other zi's are the nr poles from the adsorbed phase.
–
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Direct Renewal approach• Consider only colouring constraints on sequences of non-
overlapping vertices.
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Direct Renewal approach• Consider only colouring constraints on sequences of non-overlapping
vertices.
• As an example, consider the case = 2 for Motzkin paths. Then–
–
– i = 1 if vertex i is at surface.– Term in square brackets depends only on sequence
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• Then
where–
– is the number of Motzkin paths of length n with nj segments with the sequence as the sequence of bits in j base 2 .
– with the sequence s1s0 given by the bits in i base 2 .
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Transfer Matrix approach• Consider the following colouring constraints:
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Transfer Matrix approach• Consider the following colouring constraints:
• As an example, consider = 2 for Motzkin paths. Then–
–
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• Need to find a sequence of 2×2 real matrices
such that
• Using the properties of the trace of a real matrix
where denotes the eigenvalue with largest modulus.
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• only depends on through seq.
• Index the 8 possible matrices by the binary string in base 10.
• Then,
• and
• with
• The matrix is symmetric if .
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Lower bounds
• We can obtain a lower bound using the fact that
so that
• Another lower bound can be obtained from
so that
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Monte Carlo
• Quenched average free energy:
• Limiting quenched average free energy:
• Fir fixed n, average over a random set of colors
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Q: What is for q ?
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Heat capacity
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Scaling
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Thanks.
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Direct Renewal approach• Consider only colouring constraints on sequences of non-overlapping
vertices.
• As an example, consider the case = 2 for Motzkin paths. Then–
–
– – i = 1 if vertex i is at surface.– Term in square brackets depends only on sequence
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Transfer Matrix approach• Consider the following colouring constraints:
• As an example, consider = 2 for Motzkin paths. Then–
–
–
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• Need to find a sequence of 2×2 real matrices
such that
• Using the properties of the trace of a real matrix
where denotes the eigenvalue with largest modulus.
• Let where