Abstract
Surgical prostheses and implants used in hard-tissue engineering should satisfy all the clinical,mechani-cal,manufacturing,and economic requirements in order to be used for load-bearing applications.Metals,and to a lesser extent,polymers are promising materials that have long been used as load-bearing bioma-terials.With the rapid development of additive manufacturing (AM) technology,metallic and polymeric implants with complex structures that were once impractical to manufacture using traditional process-ing methods can now easily be made by AM.This technology has emerged over the past four decades as a rapid and cost-effective fabrication method for geometrically complex implants with high levels of accuracy and precision.The ability to design and fabricate patient-specific,customized structural bioma-terials has made AM a subject of great interest in both research and clinical settings.Among different AM methods,laser powder bed fusion (L-PBF) is emerging as the most popular and reliable AM method for producing load-bearing biomaterials.This layer-by-layer process uses a high-energy laser beam to sinter or melt powders into a part patterned by a computer-aided design (CAD) model.The most impor-tant load-bearing applications of L-PBF-manufactured biomaterials include orthopedic,traumatological,craniofacial,maxillofacial,and dental applications.The unequalled design freedom of AM technology,and L-PBF in particular,also allows fabrication of complex and customized metallic and polymeric scaffolds by altering the topology and controlling the macro-porosity of the implant.This article gives an overview of the L-PBF method for the fabrication of load-bearing metallic and polymeric biomaterials.
基金项目
Australian Research Council (ARC) through the discovery grant(DP170102557)
an ARC Future Fellowship(FT160100252)
Bonash Medical and Adeiss centre at Western University for providing the images of craniomaxillofacial biomaterials()
KLS Martin Group for the image of biodegradable patient-specific cranial implant()
NETL
NSTL
维普
万方数据