Polymer crystallization in the presence of "sticky" additives.

The effect of "sticky" additives (viz., those that have attractive interactions with the polymer) on polymer crystallization, has been investigated by dynamic Monte Carlo (DMC) simulations. Additive-polymer attractive interactions result in a slowing down of the polymer chain diffusivity in the melt state. Our results show that with increasing additive stickiness, polymer crystallinity decreases monotonically, and thinner crystallites form, viz., crystallization is inhibited by the presence of sticky additives. Unusually, the observed "specific heat" peak at the phase transition shows nonmonotonic behavior with additive stickiness, and exhibits a maximum for intermediate values of additive stickiness. While the origins of this unexpected behavior are not clear, we show that it correlates with a large interchange between crystalline and amorphous states of the monomers, in the vicinity of the additives. At this intermediate additive stickiness, we also find that crystallization follows a qualitatively different route--crystallinity shows a non-Avrami-like evolution, unlike the case at low or high additive stickiness.

Elasticity and photoelasticity relationships for polyethylene terephthalate fiber networks by molecular simulation.

We present a framework for the development of elasticity and photoelasticity relationships for polyethylene terephthalate fiber networks, incorporating aspects of the primary molecular structure. Semicrystalline polymeric fiber networks are modeled as sequentially arranged crystalline and amorphous regions. Rotational isomeric states-Monte Carlo simulations of amorphous chains of up to 360 bonds (degree of polymerization, DP=60), confined between and bridging infinite impenetrable crystalline walls, have been characterized by Omega, the probability density of the intercrystal separation h, and Deltabeta, the polarizability anisotropy. ln Omega and Deltabeta have been modeled as functions of h, yielding the chain deformation relationships. The development has been extended to the fiber network to yield the photoelasticity relationships. We execute our framework by fitting to experimental stress-elongation data and employing the single fitted parameter to directly predict the birefringence-elongation behavior, without any further fitting. Incorporating the effect of strain-induced crystallization into the framework makes it physically more meaningful and yields accurate predictions of the birefringence-elongation behavior.

Pathway to copolymer collapse in dilute solution: uniform versus random distribution of comonomers.

Monte Carlo simulations show that copolymers with uniformly (or periodically) distributed sticky comonomers collapse "cooperatively," abruptly forming a compact intermediate comprising a monomer shell surrounding a core of the aggregated comonomers. In comparison, random copolymers collapse through a relatively less-compact intermediate comprising a comonomer core surrounded by a fluffy monomer shell that densifies over a wide temperature range. This difference between the collapse pathways for random and uniform copolymers persists to higher chain lengths, where uniform copolymers tend to form multiple comonomer cores. In this paper, we describe the formation of such an intermediate state, and the subsequent collapse, by recognizing that these arise from the expected balance between comonomer aggregation enthalpy and loop formation entropy dictated by the chain microstructure.

Protein structure prediction aided by geometrical and probabilistic constraints.

Database-assisted ab initio protein structure prediction methods have exhibited considerable promise in the recent past, with several implementations being successful in community-wide experiments (CASP). We have employed combinatorial optimization techniques toward solving the protein structure prediction problem. A Monte Carlo minimization algorithm has been employed on a constrained search space to identify minimum energy configurations. The search space is constrained by using radius of gyration cutoffs, the loop backbone dihedral probability distributions, and various secondary structure packing conformations. Simulations have been carried out on several sequences and 1000 conformations have been initially generated. Of these, 50 best candidates have then been selected as probable conformations. The search for the optimum has been simplified by incorporating various geometrical constraints on secondary structural elements using distance restraint potential functions. The advantages of the reported methodology are its simplicity, and modifiability to include other geometric and probabilistic restraints.