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Anisotropic Networks, Elastomers, and Gels

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Abbreviations

Elastomer:

Nominally equivalent to “rubber,” this defines a weakly cross-linked network of polymer chains which retain high thermal mobility of the strands between cross-links. In this case the entropic effects dominate the response of such networks. Entropic rubber elasticity arises when such a network percolates the whole macroscopic system and the cross-links constrain it such that it remembers its equilibrium shape and responds elastically to deformations. In this sense, an elastomer is contrasted to a polymer glass: The latter can refer to a network so densely cross-linked that the individual chain segments have no significant mobility or a polymer system below its structural glass transition. The shear elastic modulus of elastomers is usually in the range 10–1000 kPa, the estimate arising from the thermal energy kT per network strand, while the glass modulus is usually 0.1–10 GPa, as in most solids.

Gel:

This word is used in many different contexts, in all cases referring to a soft object that is capable of retaining its shape in ambient conditions against, e.g., gravity. The latter condition distinguishes a gel from a “sol” or a nominal liquid. The softness is a relative concept; usually it refers to the modulus at or below the “human” scale, around 1–100 kPa, but there are many examples of even softer gels. In this article, a gel is contrasted to an elastomer, referring to a cross-linked network of polymer chains which is swollen by a good solvent. In this case the effective shear modulus becomes very low; nevertheless, the system remains elastic as long as the integrity of percolating network remains intact.

Quenched constraints:

The term quenched (as opposed to annealed) refers to objects or systems that are prevented from exploring their full phase or conformational space during thermal motion. In elastomers and gels, network cross-links are the quenched objects, constraining the polymer chains connecting to them. The effect of randomly quenched constraints is profound in many physical systems, as local thermodynamic equilibrium has to be established among the mobile (annealed) elements while observing the constraints, the random local realization of which is determined by external factors, such as the preparation history.

Liquid crystal:

This refers to a group of anisotropic phases with incomplete translational order (which would represent a crystalline lattice). Classical examples are the nematic phase, a fluid with no translational order at all, but with a uniaxial orientational order of anisotropic molecules, and smectic or lamellar phases, which in addition to orientational order also have a one-dimensional density modulation (a stack of parallel layers). Liquid crystallinity is a state of spontaneous, equilibrium anisotropy (breaking of orientational symmetry), in contrast to anisotropy induced by external factors such as electric/magnetic field or mechanical deformation.

Shape memory:

Strictly, any elastic material “remembers” its equilibrium shape and returns to it after deformation. The term shape memory was introduced to distinguish materials that could be made to preserve their deformed state, until a trigger (e.g., heating above a transition temperature) induces the return to the original equilibrium shape. In shape-memory alloys, this is due to the martensitic transition; in shape-memory polymers, the deformed state can be fixed by a glass transition or partial crystallization. Liquid crystal elastomers and gels have a reversible or equilibrium shape memory in that the shape of the body is determined by the current state of order at any given temperature.

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  1. Cavendish Laboratory, University of Cambridge, Cambridge, UK

    Eugene M. Terentjev

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Correspondence to Eugene M. Terentjev .

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  1. Ramtech Ltd., Larkspur, California, USA

    Robert A. Meyers

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Terentjev, E.M. (2015). Anisotropic Networks, Elastomers, and Gels. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27737-5_20-2

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  • DOI: https://doi.org/10.1007/978-3-642-27737-5_20-2

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