A theoretically informed coarse-grained Monte Carlo method is proposed for studying liquid crystals. The free energy functional of the system is described in the framework of the Landau-de Gennes formalism. The alignment field and its gradients are approximated by finite differences, and the free energy is minimized through a stochastic sampling technique. The validity of the proposed method is established by comparing the results of the proposed approach to those of traditional free energy minimization techniques. Its usefulness is illustrated in the context of three systems, namely, a nematic liquid crystal confined in a slit channel, a nematic liquid crystal droplet, and a chiral liquid crystal in the bulk. It is found that for systems that exhibit multiple metastable morphologies, the proposed Monte Carlo method is generally able to identify lower free energy states that are often missed by traditional approaches. Importantly, the Monte Carlo method identifies such states from random initial configurations, thereby obviating the need for educated initial guesses that can be difficult to formulate.

A continuum theory is used to study the effects of homeotropic nano-particles on degenerate planar liquid crystal interfaces. Particle self-assembly mechanisms are obtained from careful examination of particle configurations on a planar film and on a spherical droplet. The free energy functional that describes the system is minimized according to Ginzburg-Landau and stochastic relaxations. The interplay between elastic and surface distortions and the desire to minimize defect volumes (boojums and half-Saturn rings) is shown to be responsible for the formation of intriguing ordered structures. As a general trend, the particles prefer to localize at defects to minimize the overall free energy. However, multiple metastable configurations corresponding to local minima can be easily observed due to the high energy barriers that separate distinct particle arrangements. We also show that by controlling anchoring strength and temperature one can direct liquid-crystal mediated nanoparticle self-assembly along well defined pathways.

This paper presents a model that predicts fiber–matrix separation in ribbed sections of compression molded parts. The model combines a mechanical analysis of compression molding with some experimentally measured variables. It is shown that with a higher closing speed, the viscosity of the material will increase and fiber–matrix separation can be reduced. Specific applications for this method are compression molding of sheet molding compounds and glass mat‐reinforced thermoplastics. POLYM. COMPOS., 28:451–457, 2007. © 2007 Society of Plastics Engineers

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Metal sorption on carbon plays an important role in a range of applications, including batteries, supercapacitors, and nuclear reactors. In particular, understanding sorption of radioactive isotopes, such as Cs and Sr in different graphite materials, is important for establishing nuclear reactor safety. This work uses ab initio methods to predict the binding behavior of Cs and Sr adatoms to perfect graphite, amorphous carbon, and diamond structures. The aim of these simulations is to analyze the influence of sp2 / sp3 binding and graphite defects on adatom binding strength. Results show a tendency of defects in graphite and carbon structures with sp3 bonds to form stronger bonds with the adatoms than perfect sp2 graphite. Comparison with experimental sorption data suggests that defects and sp3 bonded regions play a critical role in the sorption behavior of Cs and Sr on graphite.