Multimodal Three-Dimensional Printing for Micro-Modulation of Scaffold Stiffness Through Machine Learning

TISSUE ENGINEERING PART A(2023)

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摘要
The ability to precisely control a scaffold's microstructure and geometry with light-based three-dimensional (3D) printing has been widely demonstrated. However, the modulation of scaffold's mechanical properties through prescribed printing parameters is still underexplored. This study demonstrates a novel 3D-printing workflow to create a complex, elastomeric scaffold with precision-engineered stiffness control by utilizing machine learning. Various printing parameters, including the exposure time, light intensity, printing infill, laser pump current, and printing speed were modulated to print poly (glycerol sebacate) acrylate (PGSA) scaffolds with mechanical properties ranging from 49.3 +/- 3.3 kPa to 2.8 +/- 0.3 MPa. This enables flexibility in spatial stiffness modulation in addition to high-resolution scaffold fabrication. Then, a neural network-based machine learning model was developed and validated to optimize printing parameters to yield scaffolds with user-defined stiffness modulation for two different vat photopolymerization methods: a digital light processing (DLP)-based 3D printer was utilized to rapidly fabricate stiffness-modulated scaffolds with features on the hundreds of micron scale and a two-photon polymerization (2PP) 3D printer was utilized to print fine structures on the submicron scale. A novel 3D-printing workflow was designed to utilize both DLP-based and 2PP 3D printers to create multiscale scaffolds with precision-tuned stiffness control over both gross and fine geometric features. The described workflow can be used to fabricate scaffolds for a variety of tissue engineering applications, specifically for interfacial tissue engineering for which adjacent tissues possess heterogeneous mechanical properties (e.g., muscle-tendon). Impact statement Fabricating three-dimensional (3D) printed scaffolds with complex stiffness gradients poses a fabrication challenge in light-based 3D printing. In this study, we demonstrate a novel 3D printing workflow that allows for a precise spatial stiffness control over both the macro- and microstructures of 3D printed scaffolds in addition to fine geometrical control over 3D printed scaffold's macroarchitecture. The proposed 3D printing workflow is promising for various applications, including the fabrication of interfacial scaffolds for tissue engineering.
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关键词
3D printing,two-photon polymerization,digital light processing,machine learning,stiffness
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