Incorporation of machine learning in the design of bio-nanocomposites produced by DLP 3D printer

This is the authors' abstract. We don't add key points for this paper.

• By incorporating biocompatible nanoparticles, such as alumina, graphene, and silica in various volume fractions, the mechanical and wear characteristics of nanocomposites are improved. • The effects of varying the thickness of the printing layers are explored within the DLP 3D printing process. • The machine learning technique, along with the meta-heuristic algorithms and the TOPSIS decision-making method, is employed to optimize the process. • The mechanical and wear properties are analyzed along with the SEM images from the fracture and worn surfaces. • Hybrid nanocomposites, specifically combinations of (Alumina + Silica / PLA), and (Alumina + Graphene / PLA) nanocomposites, are created to optimize wear resistance and mechanical performance. Due to its ease of processing and compatibility with biological systems, polylactic acid (PLA) sees extensive use in biomedical applications. This research explores the mechanical characteristics and wear resistance of PLA biocomposites fabricated via Digital Light Processing (DLP). To create both single-component and hybrid nanocomposites, alumina (Al 2 O 3 ), silica (SiO 2 ), and graphene (GS), all biocompatible materials commonly found in medical devices, were added to the PLA matrix. The study evaluated how printing layer thickness, the type, and the amount of reinforcements affected the final product's properties. The collected data were analyzed utilizing machine learning methodologies to predict bio-nanocomposites' characteristics. The results indicated that the thinner printing layer exhibits higher strength and wear resistance. The tensile strength improved by ∼16% while raising the alumina content to 8 wt.%. However, silica and graphene deteriorate the tensile properties. Concerning the wear properties, even though all reinforcements increase the wear resistance, it is enabled more severely by graphene with 77% improvement, while silica (with 69%) and alumina (with 62% improvement in wear resistance) stand on the second and last level. In hybrid nanocomposites, the silica and graphene reinforcements reduce the strength, despite improving the wear rate