A method for dissecting the polymeric networks of gels enables the number of loops — strands that connect to themselves — within them to be counted. This allows network morphologies to be correlated with gel properties.
Products as diverse as jelly, pharmaceuticals and cosmetics often contain a common ingredient: a gel formed from an extensive network of cross-linked polymer chains. Such gels typically encase a large amount of fluid. Hydrogels, for example, contain as much as 90% water, yet can still be as strong and tough as rubber1. The strength of these materials comes from the polymers that interconnect multiple chains within the network, whereas strands that form non-connecting loops weaken the material (Fig. 1). Writing in Proceedings of the National Academy of Sciences, Zhou et al.2 report an experimental method for determining the number of loops — something that wasn't previously possible. The ability to quantify the fraction of a gel that consists of such 'wasted' loops3 should enable researchers to establish synthetic routes that minimize the formation of these topologies, and thereby optimize the strength and toughness of such materials.
Zhou et al. cleverly realized that to determine the fraction of loops in a polymer gel, they had to dissect it, and so they designed a material that could be carefully and precisely broken apart. Their hydrogel was composed of a linear polymer that contained a reactive group for forming cross-links at each end, and a branched monomer that contained three reactive end groups. The linear polymer was designed to contain a strategically placed, readily cleavable chemical bond.
The researchers made the gel by combining the components in solution, and then applied their careful dissection technique to break the readily cleavable bonds. Because these bonds were precisely placed, only four products would form from this degradation reaction if an ideal network without any loops had been made; each of those products had its own distinctive molecular mass. But if some loops had formed, different degradation products (with their own characteristic molecular masses) would be obtained. By measuring the masses of the actual degradation products and comparing them to the predicted masses for the ideal network, the authors could therefore determine the number of loops in the system. They named this technique 'network disassembly spectrometry' (NDS).
A potential limitation of NDS is that one must be able to predict the degradation products in order to apply the technique. Nevertheless, a broad range of polymers and chemistries will be amenable to this analytical approach. What's more, the technique enables new fundamental studies to be made of the dynamics of polymer-network formation. For example, by using NDS at different stages of their network's formation, Zhou et al. were able to probe the structural evolution of the gel. And by varying the reaction conditions of network assembly, they could control the fraction of loops that formed in the system, and thus gain valuable insight into the factors that contribute to the formation of these 'defects'.
One application of NDS might be as a tool for correlating the microstructure of gels with their mechanical properties. This could be useful in the development of artificial muscles that perform useful work4. For example, some gels controllably expand and contract in response to external stimuli (such as changes in pH, illumination or heat)5 or internal chemical reactions4, and so can function as actuators that drive movement within a system.
The rhythmic swelling and deswelling of gels has been harnessed to push micrometre-sized particles and cells along a surface6. Heat-responsive gels have also been used to drive micrometre-sized posts in and out of a bath of solution7: when the system was hot, the gel shrank, pulling the posts out of the bath, but when the system cooled down, the gel expanded and pushed the posts back in. This behaviour formed the basis of a homeostatic device that autonomously regulated the temperature of the system. For optimal performance, such soft actuators need to be mechanically robust — which means that they should not contain wasted loops.
On the other hand, because NDS can yield correlations between mechanical properties and the fraction of loops in a gel, it might help to provide design rules for exploiting loops, perhaps leading to the development of robust materials that nonetheless are highly flexible. In particular, there is rapidly growing interest in reconfigurable materials that can dramatically change shape in response to external cues8,9,10. Examples abound in biology, because such adaptive behaviour is vital for survival — consider, for example, the ability of octopuses and cuttlefish to change their shape, colour and texture in order to camouflage themselves in the presence of predators. Because gels can be made to shrink and swell controllably, they can be driven to change shape, and thus are ideal synthetic materials for creating systems that accomplish analogous adaptive behaviours.
Advances in this area could lead to multi-functional systems that have one structure and function in one environment, but another shape and function under different conditions. However, to undergo significant shape changes, the material must be very flexible. It might be that the introduction of just the right amount of loops within a polymer network could lead to robust, but sufficiently flexible, shape-changing materials. With findings from NDS, perhaps researchers will eventually establish effective routes for making gels that act like cuttlefish.
Gong, J. P. Soft Matter 6, 2583–2590 (2010).
Zhou, H. et al. Proc. Natl Acad. Sci. USA 109, 19119–19124 (2012).
Panyukov, S. & Rabin, Y. Phys. Rep. 269, 1–131 (1996).
Yashin, V., Kuksenok, O., Dayal, P. & Balazs, A. C. Rep. Progr. Phys. 75, 066601 (2012).
Cohen Stuart, M. A. et al. Nature Mater. 9, 101–113 (2010).
Yoshida, R. Sensors 10, 1810–1822 (2010).
He, X. et al. Nature 487, 214–218 (2012).
Guillet, P. et al. Soft Matter 5, 3409–3411 (2009).
Yashin, V. V., Kuksenok, O. & Balazs, A. C. J. Phys. Chem. B 114, 6316–6322 (2010).
Ueno, T., Bundo, K., Akagi, Y., Sakai, T. & Yoshida, R. Soft Matter 6, 6072–6074 (2010).
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Chem. Commun. (2016)
Accounts of Chemical Research (2016)
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