A hybrid additive manufacturing platform to create bulk and surface composition gradients on scaffolds for tissue regeneration

DOI

Scaffolds with gradients of physico-chemical properties and controlled 3D architectures are crucial for engineering complex tissues. These can be produced using multi-material additive manufacturing (AM) techniques. However, they typically only achieve discrete gradients using separate printheads to vary compositions. Achieving continuous composition gradients, to better mimic tissues, requires material dosing and mixing controls. No such AM solution exists for most biomaterials. Existing AM techniques also cannot selectively modify scaffold surfaces to locally stimulate cell adhesion. A hybrid AM solution to cover these needs is reported here. A novel dosing- and mixing-enabled, dual-material printhead and an atmospheric pressure plasma jet to selectively activate/coat scaffold filaments during manufacturing were combined on one platform. Continuous composition gradients in both 2D hydrogels and 3D thermoplastic scaffolds were fabricated. An improvement in mechanical properties of continuous gradients compared to discrete gradients in the 3D scaffolds, and the ability to selectively enhance cell adhesion were demonstrated.

Identifier
DOI https://doi.org/10.34894/A4NGLO
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/A4NGLO
Provenance
Creator Sinha, Ravi ORCID logo; Cámara Torres, Maria ORCID logo; Scopece, Paolo ORCID logo; Verga Falzacappa, Emanuele ORCID logo; Patelli, Alessandro ORCID logo; Moroni, Lorenzo ORCID logo; Mota, Carlos ORCID logo
Publisher DataverseNL
Contributor Sinha, Ravi; Moroni, Lorenzo; Mota, Carlos; Hebels, Dennie
Publication Year 2020
Rights CC0 Waiver; info:eu-repo/semantics/openAccess; https://creativecommons.org/publicdomain/zero/1.0/
OpenAccess true
Contact Sinha, Ravi (Maastricht University); Moroni, Lorenzo (Maastricht University); Mota, Carlos (Maastricht University); Hebels, Dennie (Maastricht University)
Representation
Resource Type Dataset
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Version 1.0
Discipline Life Sciences; Medicine