Designing an Open-Source Multi-vat Digital Light Processing Printer
Raza ur Rehman Syed, Gene Tyler Felix, Akhilesh K. Gaharwar
Mitchell Institute Texas A&M University
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Additive manufacturing has undergone rapid evolution in modalities that can recreate native human tissue architectures with high resolution. Among emerging approaches, digital light processing (DLP)-based printing enables the fabrication of intricate biomimetic architectures through the photopolymerization of polymer-based hydrogels. The recent emergence of multi-material printing further enhances this capability, enabling the complex spatial arrangement of heterogeneous cells and diverse bioink compositions. However, the widespread adoption of DLP printing remains constrained by the high cost, proprietary hardware, and limited customizability of commercially available systems. Here, we present an open-source multi-vat DLP printing platform developed through the integration and modification of two low-cost commercially available 3D printers. A dedicated Python-based graphical user interface was developed, providing user-defined control over critical printing parameters, including exposure time, layer height, printing sequence, and material switching. Comprehensive hardware documentation and a complete bill of materials (BOM) are provided to ensure reproducibility and accessibility across research laboratories. In addition to multi-material printing, the system enables spatial modulation of mechanical properties within a single bioink formulation through programmable light exposure and supports enhanced z-axis resolution through user-defined layer thickness control. The platform was validated through the fabrication of geometrically complex, multi-material, and mechanically heterogeneous constructs. Collectively, this work establishes an accessible and customizable DLP printing platform that enables advanced biofabrication and facilitates the engineering of compositionally and mechanically heterogeneous tissue-mimetic construct.
逐年被引趋势
暂无年度引用数据
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
工程3D Printing in Biomedical Research
Additive Manufacturing and 3D Printing Technologies · Advanced Materials and Mechanics