CAREER: Toward RIPEST Photopolymer Additive Manufacturing (PAM): A Cyber-Physical System of Novel Dual-wavelength Photoinhibition aided PAM

光聚合物增材制造（PAM）使用光来固化光敏材料，是与现有聚合物制造技术相比，制造具有更高分辨率的组件的最通用技术之一。然而，最先进的光聚合物增材制造技术仍然遭受过固化的棘手问题，这对打印部件的结构完整性是有害的。该学院早期职业发展（CAREER）资助支持研究阐明光传播和光化学反应的基础科学，以建立智能双波长光抑制辅助PAM过程。这种新工艺允许操纵PAM加工的固化和抑制曝光，从而可以增强几何保真度和功能完整性。如果成功，该项目将影响许多应用，包括生物芯片，电极，软机器人，超材料以及其他需要精密制造具有复杂形状和增强性能的零件的应用。该项目将提供教育活动，旨在培养未来的领导者追求与制造业相关的职业，并通过接触历史上代表性不足的社区来提高STEM劳动力的多样性。该CAREER项目的总体目标是实现快速，智能，精确，广泛，可持续和变革（RIPEST）PAM。主要研究目标是建立一种新的数字光处理方法-DLP 2Curb，该方法利用第二波长光诱导的光抑制来抑制固化部件，通过一种整体的网络物理方法，将物理引导的替代建模与实时传感和控制相结合。推力1通过多个物理机制、时间阶段和空间尺度阐述了DLP 2Curb过程动力学和材料行为，以通过构建数字孪生模型来揭示过度固化的原因和路缘反应路径。 推力2的目标是实现非接触，全领域的操作表征PAM在真实的时间。过程中的零件属性将通过部署现场干涉和超声波监测系统沿着物理传感器模型和数据分析方法进行测量。 Thrust 3通过模型预测和现场测量反馈的深度强化学习开发了一种实时控制方法。通过微柱和网格等案例研究，该项目将展示DLP 2Curb的潜在能力，以解锁具有精确几何形状和精致细节的复杂零件的高效精密制造。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Photopolymer additive manufacturing (PAM) uses light to cure photosensitive materials and is one of the most versatile technologies to fabricate components with higher resolution compared to existing polymer manufacturing technologies. However, the state-of-the-art photopolymer additive manufacturing technologies still suffer an intractable issue of overcuring, which is detrimental to the structural integrity of printed parts. This Faculty Early Career Development (CAREER) grant supports research to elucidate the fundamental science of light propagation and photochemistry reactions for establishing a smart dual-wavelength photoinhibition aided PAM process. This new process allows to manipulate cure and curb exposures of the PAM processing so that the geometrical fidelity and functional integrity can be enhanced. If successful, this project will impact numerous applications including biochips, electrodes, soft robots, metamaterials, and others that demand precision manufacturing of parts with complex shapes and strengthened performance. This project will provide educational activities aimed to train future leaders to pursue manufacturing-related careers and improve the diversity of the STEM workforce by reaching out to historically underrepresented communities.The overarching goal of this CAREER project is to realize Rapid, Intelligent, Precise, Extensive, Sustainable, and Transformative (RIPEST) PAM. The primary research objective is to establish a novel digital light processing method - DLP2Curb that capitalizes on photoinhibition induced by a second wavelength light to curb curing parts, via a holistic cyber-physical approach that combines physics-guided surrogate modeling with real-time sensing and control. Thrust 1 elaborates the DLP2Curb process dynamics and materials behavior through multiple physical regimes, temporal stages, and spatial scales to unravel the causes of overcuring and the curb reaction paths by constructing a digital twin. Thrust 2 aims to achieve non-contact, full-field operando characterization of PAM in real time. In-process part properties will be measured by deploying in-situ interferometric and ultrasonic monitoring systems along with physical sensor models and data analytics methods. Thrust 3 develops a real-time control method via deep reinforcement learning of model predictions and in-situ measurements feedback. With case studies such as micropillars and lattices, this project will demonstrate the potential ability of DLP2Curb to unlock efficient precision manufacturing of sophisticated parts with exact geometry and exquisite details.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.