TY - UNPB
T1 - Exploiting generative design for multi-material inkjet 3D printed cell instructive, bacterial biofilm resistant composites
AU - He, Yinfeng
AU - Begines, Belen
AU - Trindade, Gustavo F.
AU - Abdi, Meisam
AU - Dubern, Jean-Frédéric
AU - Prina, Elisabetta
AU - Hook, Andrew L.
AU - Choong, Gabriel
AU - Ledesma, Javier
AU - Tuck, Christopher J.
AU - Rose, Felicity R. A. J.
AU - Hague, Richard
AU - Roberts, Clive J.
AU - de Focatiis, Davide De
AU - Ashcroft, Ian A.
AU - Williams, Paul
AU - Irvine, Derek J.
AU - Alexander, Morgan R.
AU - Wildman, Ricky D.
PY - 2020
Y1 - 2020
N2 - As our understanding of disease grows, it is becoming established that treatment needs to be personalized and targeted to the needs of the individual. In this paper we show that multi-material inkjet-based 3D printing, when backed with generative design algorithms, can bring a step change in the personalization of medical devices. We take cell-instructive materials known for their resistance to bacterial biofilm formation and reformulate for multi-material inkjet-based 3D printing. Specimens with customizable mechanical moduli are obtained without loss of their cell-instructive properties. The manufacturing is coupled to a design algorithm that takes a user-specified deformation and computes the distribution of the materials needed to meet the target under given load constraints. Optimisation led to a voxel map file defining where different materials should be placed. Manufactured products were assessed against the mechanical and cell-instructive specifications and ultimately showed how multifunctional personalization emerges from generative design driven 3D printing.
AB - As our understanding of disease grows, it is becoming established that treatment needs to be personalized and targeted to the needs of the individual. In this paper we show that multi-material inkjet-based 3D printing, when backed with generative design algorithms, can bring a step change in the personalization of medical devices. We take cell-instructive materials known for their resistance to bacterial biofilm formation and reformulate for multi-material inkjet-based 3D printing. Specimens with customizable mechanical moduli are obtained without loss of their cell-instructive properties. The manufacturing is coupled to a design algorithm that takes a user-specified deformation and computes the distribution of the materials needed to meet the target under given load constraints. Optimisation led to a voxel map file defining where different materials should be placed. Manufactured products were assessed against the mechanical and cell-instructive specifications and ultimately showed how multifunctional personalization emerges from generative design driven 3D printing.
KW - Multimaterial
KW - 3D printing
KW - Generative design
KW - Cell instructive
KW - Bacterial biofilm resistant
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85098902255&partnerID=MN8TOARS
U2 - 10.26434/chemrxiv.12596999.v1
DO - 10.26434/chemrxiv.12596999.v1
M3 - Working paper
BT - Exploiting generative design for multi-material inkjet 3D printed cell instructive, bacterial biofilm resistant composites
PB - Cambridge Open Engage
CY - Cambridge
ER -