Block copolymer melts morphologies

A review of the thermodynamics of block copolymer melts prior to the discovery of complex phases was presented by Bates and Fredrickson (1990). Ryan and Hamley (1997) have recently reviewed the morphology of block copolymers containing a glassy component, in the melt and glassy states, and a discussion of complex phases is included. Fredrickson and Bates (1996) and Colby (1996) have reviewed the dynamics of block copolymer melts, of which the former is a par-... 

We will briefly discuss the molecular dynamics results obtained for two systems—protein-like and random-block copolymer melts— described by a Yukawa-type potential with (i) attractive A-A interactions (saa < 0, bb = sab = 0) and with (ii) short-range repulsive interactions between unlike units (sab > 0, aa = bb = 0). The mixtures contain a large number of different components, i.e., different chemical sequences. Each system is in a randomly mixing state at the athermal condition (eap = 0). As the attractive (repulsive) interactions increase, i.e., the temperature decreases, the systems relax to new equilibrium morphologies. 

In block copolymer melts, the solvent-polymer interaction doesn t exist anymore and other morphologies can be observed. A large amount of work deals with the self-assembly in bulk, how to predict it, and how to understand the phase change or the geometry orientation in relation to the experimental parameters. In this section we will give a quick overview of the key points to be considered when working in this field. 

The stability of the PL morphologies was reexamined by Hajduk et al. (1997) in a number of block copolymer melts of low to moderate molecular... 

All the above theories are based on geometric considerations. By applying self-consistent field theory, Miiller and Schick [74] have predicted that the only thermodynamically stable morphologies for rod-coil systems are those with the coils on the convex side of the interface. Very recently Gurovich [75] developed a statistical theory which treats the microphase separation in LC block copolymer melts near the spino-dal and predicts orientational and reorienta-tional phase transitions driven by the configurational separation and four different phases. 

The interest in the phase behaviour of block copolymer melts stems from microphase separation of polymers that leads to nanoscale ordered morphologies. This subject has been reviewed extensively [1 ]. The identification of the structure of bicontinuous phases has only recently been confirmed, and this together with major advances in the theoretical understanding of block copolymers, means that the most up-to-date reviews should be consulted [1,3]. The dynamics of block copolymer melts, in particular rheological behaviour and studies of chain diffusion via light scattering and NMR techniques have also been the focus of several reviews [1,5,6]. 

Kawasaki K, Ohta T, Kohrogui M (1988) EquUibrium morphology of block copolymer melts. 2. Macromolecules 21 2972-2980... 

Ohta T, Kawasaki K (1986) Equilibrium morphology of block copolymer melts. Macromolecules 19 2621-2632... 

The phase behaviour of block copolymer melts is, to a first approximation, represented in a morphology diagram in terms of /[ ] Here/is the... 

Wall interfaces have also been found to alter the phase separation of nearby symmetric block copolymer chains. Fredrickson used SCF theory to demonstrate that a block copolymer melt in the vicinity of a solid wall or free surface (one with selective attraction) possessed a modified Flory-Huggins interaction parameter. Due to the connectivity of the blocks and the incompressibility of the material (an assumption of the calculation), the calculated interaction parameters have an oscillatory component with period 2njdo, normal to the wall plane, which decays exponentially from the interface. Milner and Morse also predirted this oscillatory profile normal to the surface for bulk-cylindrical morphology as well (corresponding to thickness commensurability), though they also observed that the decay length is longer closer to the mean-field critical point. 

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