Statistical copolymers crystallization kinetics

Besides its effects on morphology, comonomer sequence distribution also affects copolymer crystallization kinetics. In statistical copolymers, due to the broad distribution of crystaUizable sequence lengths, bimodal melting endotherms are typically observed. In block copolymers, the dynamics of crystallization have features characteristic of both homopolymer crystallization and microphase separation in amorphous block copolymers. In addition, the presence of order in the melt, even if the segregation strength is weak, hinders the development of the equihbrium spacing in the block copolymer solid-state structure. 

In what follows, we use simple mean-field theories to predict polymer phase diagrams and then use numerical simulations to study the kinetics of polymer crystallization behaviors and the morphologies of the resulting polymer crystals. More specifically, in the molecular driving forces for the crystallization of statistical copolymers, the distinction of comonomer sequences from monomer sequences can be represented by the absence (presence) of parallel attractions. We also devote considerable attention to the study of the free-energy landscape of single-chain homopolymer crystallites. For readers interested in the computational techniques that we used, we provide a detailed description in the Appendix. ... 

Copolymers are macromolecules composed of two or more chemically distinct monomer units, covalently joined to form a common polymer chain [1,2], In these materials, the sequence distribution of the monomer counits plays a critical role in determining the copolymer s crystallization behavior, and consequently influences its solid-state morphology and material properties [1,2], At one extreme, different types of monomer units may be randomly incorporated into the polymer chain, resulting in a statistical copolymer. At the other extreme, blocks of homopolymer sequences of different chemical nature and chain length may be joined together to form what is known as a block copolymer. In this chapter, we wiU review the key effects of comonomer incorporation on the solid-state morphology and crystallization kinetics in both statistical and block copolymers. 

Statistical copolymers refer to a class of copolymers in which the distribution of the monomer counits follows Markovian statistics [1,2]. In these polymeric materials, since the different chemical units are joined at random, the resulting polymer chains would be expected to encounter difficulties in packing into crystaUine structures with long-range order however, numerous experiments have shown that crystallites can form in statistical copolymers under suitable conditions [2], In this section, we will discuss the effects of counit incorporation on the solid-state structure and the crystallization kinetics in statistical copolymers. A number of thermodynamic models, which have been proposed to describe the equilibrium crystallization/melting behavior in copolymers, vill also be highlighted, and their applicability to describing experimental observations will be discussed. 

Thus far, we have discussed a number of key experimental observations regarding the effects of counit incorporation on the solid-state structure and the crystallization kinetics in statistical copolymers. In order to better quantify these experimental observations, various thermodynamic models have been proposed. Rory s model, as outlined in Section 11.2.1, correctly describes the equilibrium melting behavior of copolymers in the limit of complete comonomer exclusion however, it is often found to be inadequate at predicting experimentally accessible copolymer melting temperatures [11-14]. An alternative was proposed by Baur [91], where each polymer sequence is treated as a separate molecule with an average sequence length in the melt given by [91] ... 

In Section 11.2, we discussed the morphology and crystallization kinetics of statistical copolymers, where the comonomer units are distributed along the polymer... 

The effect of block chain architecture on crystallization kinetics was studied by comparing the OBC H84 with a statistical EO copolymer, E02.8. Both have the same total octene content of about 3.0 mol % and about the same crystallinity. Table 1. The comparison of spheruhte growth rates of H84, E02.8 and HS is shown in Figure 9. At 110 °C the growth rate of H84 is more than two orders of magnitude faster than E02.8. This indicates that statistical sequences crystallize much slower than long ethylene blocks of the OBC. The HS control which has 1.3 mol % octene was much faster than E02.8 because of its lower octene content. 

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