Virtual testing methodology to predict the mechanical behavior of collagen hydrogels from nanoarchitecture

dc.contributor.authorNúñez Ortega, Elías
dc.contributor.authorBlázquez Carmona, Pablo
dc.contributor.authorRuiz Mateos, Raquel
dc.contributor.authorMartín Alfonso, José Enrique
dc.contributor.authorSanz Herrera, José A.
dc.contributor.authorReina Romo, Esther
dc.date.accessioned2025-11-26T12:27:14Z
dc.date.available2025-11-26T12:27:14Z
dc.date.issued2025
dc.description.abstractCollagen-based hydrogels are three-dimensional, cross-linked structures capable of mimicking the extracellular fibered matrix of biological tissues, making them particularly well-suited for biomedical applications. These hydrogels typically exhibit highly non-linear mechanical behavior, which strongly depends on their internal nanostructural characteristics - an interconnection that remains poorly understood. The aim of this work is to combine high resolution imaging with a multiscale in silico structural model to virtually reproduce the mechanical behavior of a widely used collagen-based hydrogel, using solely its nanoarchitecture as input. The real fiber structure of the hydrogel was originally quantified at the nanometer scale using state-of-the-art microscopy, specifically, focused ion beam-scanning electron microscopy (FIB-SEM). In silico shear tests were then performed on the reconstructed collagen matrix to compute, through a multiscale approach, its homogenized mechanical response, including the energies and stresses developed by the fibers during the tests. Different samples of the hydrogel were also mechanically characterized by means of rheological tests to fit the model and show the feasibility of the methodology. The in silico simulations successfully captured the detailed mechanical interactions between fibers as well as the experimental non-linear mechanical behavior of the hydrogels. Results also highlight the relevant role of the bending energy throughout the entire range of deformation analyzed. This methodology provides a framework to elucidate the structure-mechanical behavior relationship of fiber network topologies, and can be applied to predict mechanical response of both native tissues and biomaterials based exclusively on their fibered nanostructures.
dc.description.departmentIngeniería Química, Química Física y Ciencias de los Materiales
dc.description.sponsorshipThis study was supported by the MICIU (Ministry of Science, Inno vation and Universities of the Spanish Government) and ERPF/EU (European Regional Development Fund of the European Union) via Grant PID 2023-148828OB-I00 funded by MICIU/AEI/10.13039/ 501100011033 and by the ERDF/EU. Elías Nú˜nez-Ortega was supported by grant PREP2023-001306
dc.identifier.citationNúñez-Ortega, E., Blázquez-Carmona, P., Ruiz-Mateos, R., Martín-Alfonso, J. E., Sanz-Herrera, J. A., & Reina-Romo, E. (2025). Virtual testing methodology to predict the mechanical behavior of collagen hydrogels from nanoarchitecture. Materials Today Bio, 33, 101962. https://doi.org/10.1016/j.mtbio.2025.101962
dc.identifier.doi10.1016/j.mtbio.2025.101962
dc.identifier.issn2590-0064 (electrónico)
dc.identifier.urihttps://hdl.handle.net/10272/27442
dc.language.isoeng
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.otherCollagen-based hydrogels
dc.subject.otherFIB-SEM
dc.subject.otherFiber structures
dc.subject.otherHomogenization
dc.subject.otherIn silico model
dc.subject.otherMechanobiology
dc.subject.otherRheology
dc.subject.unesco2206.03 Macromoléculas
dc.subject.unesco2205.09 Mecánica de Sólidos
dc.subject.unesco2407 Biología Celular
dc.titleVirtual testing methodology to predict the mechanical behavior of collagen hydrogels from nanoarchitecture
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isAuthorOfPublicationd82e9c1e-88a3-40c3-b768-494b5e83f54b
relation.isAuthorOfPublication.latestForDiscoveryd82e9c1e-88a3-40c3-b768-494b5e83f54b

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