FMSG: Cyber: 3D Printing of Holographic Optical Processors

FMSG：网络：全息光学处理器的 3D 打印

• 批准号: 2328362
• 负责人: Huachao Mao
• 金额: $ 49.78万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2328362&HistoricalAwards=false
• 关键词: FMSG; Cyber; 3D; Printing; Holographic

Optical processors are computing devices that use light, rather than electricity, for sensing and processing images. Layers of gratings mimic the structure of neural networks, guide the paths of light through these layers via diffraction, and achieve low-latency and low-power computation. This technology provides a promising alternative to the existing computer vision methods, which are subject to delays caused by massive computations (billions of parameters) at high frame rates. This Future Manufacturing Seed Grant (FMSG) project will investigate the additive manufacturing of holographic optical processors and enable computer vision with minimal or no computational time. If successful, this project will generate new knowledge about high-resolution manufacturing, and lead to more affordable next-generation computing devices. The increased computation capability will potentially transform multiple fields, from artificial intelligence to quantum computing, cybersecurity to next-generation communications. This project will stimulate the interest in STEM education at the interface of future manufacturing and artificial intelligence, and contribute to workforce development in both areas.This project aims to establish a holographically-assisted Vat Photopolymerization (H-VPP) process, by combining high-throughput microscale VPP with the nanoscale holographic recording process. H-VPP fabricates billions of volumetric diffractive gratings, in place of interference-patterned refractive indices, allowing for high-resolution optical structures with a large number of layers to form complex optical pathways. Several fundamental research questions to be addressed include: (1) elucidating how transparent photocurable resins can be used for printing holographic devices, (2) investigating how nanoscale refractive index modulation can be achieved by adding extra laser beams to interfere with the projected mask-images, and (3) inversely designing the mask image patterns using the back-propagation algorithm in deep learning. This research will gain new knowledge about the relationship among the holographic process, optical structure, and processor performance. Though this project focuses on VPP, the resulting science will advance the understanding of other polymer-based high-resolution manufacturing processes. This Future Manufacturing award was supported by Division of Civil, Mechanical and Manufacturing Innovation.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.

光学处理器是使用光而不是电来感知和处理图像的计算设备。光栅层模仿神经网络的结构，通过衍射引导光路穿过这些层，并实现低延迟和低功耗计算。该技术为现有计算机视觉方法提供了一种有希望的替代方案，现有计算机视觉方法容易因高帧速率下的大量计算（数十亿个参数）而导致延迟。该未来制造种子资助 (FMSG) 项目将研究全息光学处理器的增材制造，并以最少的计算时间或无需计算时间实现计算机视觉。如果成功，该项目将产生有关高分辨率制造的新知识，并带来更实惠的下一代计算设备。计算能力的增强将有可能改变多个领域，从人工智能到量子计算，从网络安全到下一代通信。该项目将激发人们对未来制造和人工智能界面的 STEM 教育的兴趣，并为这两个领域的劳动力发展做出贡献。该项目旨在建立全息辅助还原光聚合 (H-VPP) 工艺，通过结合高具有纳米级全息记录过程的微米级 VPP 吞吐量。 H-VPP 制造了数十亿个体积衍射光栅，代替干涉图案折射率，从而允许具有大量层的高分辨率光学结构形成复杂的光学路径。需要解决的几个基本研究问题包括：（1）阐明如何使用透明光固化树脂来打印全息设备，（2）研究如何通过添加额外的激光束来干扰投影掩模图像来实现纳米级折射率调制，以及（3）使用深度学习中的反向传播算法逆向设计掩模图像图案。这项研究将获得有关全息工艺、光学结构和处理器性能之间关系的新知识。尽管该项目的重点是 VPP，但由此产生的科学将增进对其他基于聚合物的高分辨率制造工艺的理解。该未来制造奖得到了土木、机械和制造创新部门的支持。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。