Collaborative Research: DMREF: Multi-material digital light processing of functional polymers

非技术描述：加法制造，通常被称为3D打印，是一种可以彻底改变从个性化产品到医疗植入物的各种应用的技术。制造塑料物品的最强大的3D打印技术之一使用树脂的图案化照明来定义打印部件的形状。虽然目前基于光的3D打印仅限于一种材料，但该项目的目标是开发新的树脂，允许在单一步骤中打印具有不同性质的多种材料，如硬度或弹性。这项研究将结合一个涵盖材料化学、计算科学、机器学习(ML)和物理表征的反馈回路，与材料基因组倡议(MGI)的原则保持一致。材料优化的主要目标将是设计具有不同机械性能的结构化表面来指导细胞生长。这种表面对于基础研究和实际应用都是必不可少的。实验、数据分析和制造方法在研究中的整合将为具有不同背景的研究生和本科生为未来的劳动力做准备。将开展公众宣传和K-12宣传，以提高科学和工程学对先进材料制造方法的认识。技术说明：该项目将开发用于加法制造的方法和材料，使多材料物体能够进行3D打印。这项研究将通过三个主要目标来完成，这三个目标使人们能够通过数字光处理(DLP)创建具有空间定义的机械属性的多材料对象的独特能力。在目标1中，将使用机器学习方法开发多材料DLP树脂，以寻找能够使图案具有极端机械对比度(模数从kpa到Gpa)的图案，以响应不同波长的光。在目标2中，将开发一种使用光开关来控制光曝光的多材料DLP工艺，该工艺将通过使用DLP工艺的数字双胞胎进行反向设计来优化。在目标3中，将使用机器学习加速的拓扑优化来定义多材料结构来指导细胞的行为。该设计工具将材料和加工路线的平台转化为基质，通过空间定义的地形和机械对比度区域指导细胞生长。这三个目标都将利用MGI驱动的实验和理论之间的反馈循环，每个领域的进步都会增强整体结果。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Non-technical Description: Additive manufacturing, commonly referred to as 3D printing, is a technology that could revolutionize a diverse array of applications, from personalized products to medical implants. One of the most powerful 3D printing techniques for making plastic objects uses patterned illumination of a resin to define the shape of a printed part. While light-based 3D printing is currently limited to a single material, this project aims to develop new resins that allow for printing multiple materials with varying properties, such as stiffness or elasticity, in a single step. The research will combine a feedback loop spanning materials chemistry, computational science, machine learning (ML), and physical characterization aligning with principles of the Materials Genome Initiative (MGI). The primary target for materials optimization will be the design of structured surfaces with varying mechanical properties for directing cell growth. Such surfaces are essential for both fundamental studies and practical applications. The integration of experiments, data analytics, and manufacturing methods in the research will prepare graduate and undergraduate students with diverse backgrounds for the future workforce. Public outreach and K-12 outreach to improve awareness in the science and engineering of advanced materials manufacturing methods will be carried out.Technical Description: The project will develop methods and materials for additive manufacturing that enable 3D printing of multi-material objects. The research will be accomplished through three main objectives that enable a unique ability to create multi-material objects with spatially defined mechanical properties by digital light processing (DLP). In Objective 1, multi-material DLP resins will be developed using machine learning methods to find chemistries that enable patterns with extreme mechanical contrast (moduli from kPa to GPa) in response to different wavelengths of light. In Objective 2, a multi-material DLP process will be developed using photoswitches to control light exposure that will be optimized by inverse design using digital twins of the DLP process. In Objective 3, machine-learning accelerated topology optimization will be used to define multi-material structures to direct cell behavior. This design tool will translate the platform of materials and processing routes into substrates that direct cell growth via spatially defined regions of topography and mechanical contrast. All three objectives will leverage an MGI-driven feedback loop between experiment and theory where advances in each area enhance the overall outcomes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.