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001017173 005__ 20231108201912.0
001017173 037__ $$aFZJ-2023-03986
001017173 1001_ $$0P:(DE-Juel1)130797$$aLettinga, M.P.$$b0$$eCorresponding author$$ufzj
001017173 1112_ $$aInternational Conference on Rheology$$cAthens$$d2023-07-30 - 2023-08-04$$wGreece
001017173 245__ $$aInducing irreversible strain hardening and alignment during collagen gelation
001017173 260__ $$c2023
001017173 3367_ $$033$$2EndNote$$aConference Paper
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001017173 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1699450761_14451$$xAfter Call
001017173 520__ $$aCollagen is one of the main building blocks of the mammalian extracellular matrix, due to its ability to form tough structures with a wide variety of non-linear mechanical properties allowing it to support multiple tissue types. The mechanical properties of collagen gels have been extensively studied under static conditions, however, in nature gelation will mostly take place in the presence of flow. Here we show how the modulus and the alignment of the fibrillar collagen hydrogel can be tuned by applying a stress-ramp at a well-defined moment during gelation, following up on our earlier study [1]. Where the first stress block induces most of the final strain, sequential increases in stress cause the modulus to rapidly increase (see figure). This effect is more pronounced when gelation takes place at 37 oC, where due to relatively rapid kinetics a dense network of thin filaments is formed, than at 27 oC, where slower kinetics result in the formation of an open network with thick bundles. Contrary to the modulus, the increase in alignment is more pronounced for the samples formed at lower temperatures. Thus, we not only produce tough gels with alignment, but also provide insight into in vivo collagen structure formation.
001017173 536__ $$0G:(DE-HGF)POF4-5243$$a5243 - Information Processing in Distributed Systems (POF4-524)$$cPOF4-524$$fPOF IV$$x0
001017173 7001_ $$0P:(DE-HGF)0$$aDedroog, Lens$$b1
001017173 7001_ $$0P:(DE-HGF)0$$aBartic, Carmen$$b2
001017173 7001_ $$0P:(DE-HGF)0$$aDeschaume, Olivier$$b3
001017173 7001_ $$0P:(DE-HGF)0$$aVananroy, Anja$$b4
001017173 7001_ $$0P:(DE-HGF)0$$aThielemans, Wim$$b5
001017173 7001_ $$0P:(DE-HGF)0$$aCoene, Yovan de$$b6
001017173 909CO $$ooai:juser.fz-juelich.de:1017173$$pVDB
001017173 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)130797$$aForschungszentrum Jülich$$b0$$kFZJ
001017173 9131_ $$0G:(DE-HGF)POF4-524$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5243$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vMolecular and Cellular Information Processing$$x0
001017173 9141_ $$y2023
001017173 920__ $$lyes
001017173 9201_ $$0I:(DE-Juel1)IBI-4-20200312$$kIBI-4$$lBiomakromolekulare Systeme und Prozesse$$x0
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001017173 980__ $$aVDB
001017173 980__ $$aI:(DE-Juel1)IBI-4-20200312
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