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001017174 005__ 20231108201912.0
001017174 037__ $$aFZJ-2023-03987
001017174 1001_ $$0P:(DE-Juel1)130797$$aLettinga, M.P.$$b0$$ufzj
001017174 1112_ $$aSymposium DRG 2023$$cBerlin$$d2023-09-20 - 2023-09-22$$wGermany
001017174 245__ $$aInducing irreversible strain hardening and alignment during collagen gelation
001017174 260__ $$c2023
001017174 3367_ $$033$$2EndNote$$aConference Paper
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001017174 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1699450747_18030$$xAfter Call
001017174 520__ $$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.
001017174 536__ $$0G:(DE-HGF)POF4-5243$$a5243 - Information Processing in Distributed Systems (POF4-524)$$cPOF4-524$$fPOF IV$$x0
001017174 7001_ $$0P:(DE-HGF)0$$aDroog, Lens de$$b1
001017174 7001_ $$0P:(DE-HGF)0$$aBartic, Carmen$$b2
001017174 7001_ $$0P:(DE-HGF)0$$aThielemeans, Wim$$b3
001017174 7001_ $$0P:(DE-HGF)0$$aVananroy, Anja$$b4
001017174 7001_ $$0P:(DE-HGF)0$$aDeschaume, Olivier$$b5
001017174 7001_ $$0P:(DE-HGF)0$$aKoos, Erin$$b6
001017174 909CO $$ooai:juser.fz-juelich.de:1017174$$pVDB
001017174 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)130797$$aForschungszentrum Jülich$$b0$$kFZJ
001017174 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$$x0
001017174 9141_ $$y2023
001017174 920__ $$lyes
001017174 9201_ $$0I:(DE-Juel1)IBI-4-20200312$$kIBI-4$$lBiomakromolekulare Systeme und Prozesse$$x0
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001017174 980__ $$aI:(DE-Juel1)IBI-4-20200312
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