DURIP: Two-photon polymerization-based microfabrication and 3D printing system for diffractive optical processors
Abstract
This proposal aims to purchase a two-photon polymerization-based microfabrication and 3D printing system to supplement and significantly improve the speed of progress in our existing ONR project (N000142212016, PI: Ozcan), titled #Imaging and Classification of Objects Through Random Diffusers and Occlusions at the Speed of Light#. Diffractive Optical Networks have been introduced by the PI#s lab as a machine learning framework that unifies deep learning-based training of matter with the physical models governing the lightpropagation and diffraction to enable optical inference through a set of diffractive layers. A diffractive optical network design, once physically fabricated using e.g., 3D-printing, lithography, can then perform, at the speed of light, the specific task that it is trained for, using only optical diffraction and passive optical layers, creating an efficient and fast way of implementing optical inference. Our ONR-funded research program aims to design and create newtypes of all-optical diffractive processors that can imageand classify objects hidden behind random and potentially time-varying diffusing media and opaque occlusions. These all-optical diffractive processors and the resulting passive networks can operate at different parts of the electromagnetic spectrum by scaling thediffractive features proportional to the wavelength of light and therefore can be used with various light sources and detectors that are of interest to ONR. These proposed platforms will be able to infer the class/type of unknown objects almost instantaneously and without the need for any digital computer or external power (except for the illumination light), making them ideal for various naval applications such as extremely high-speed and low-power surveillance and automated monitoring of potential threats in field-settings or on naval ships.Our initial demonstrations of these diffractive optical networks employed longer wavelengths (~1 mm), using a low-resolution, inexpensive 3D printer system to fabricate the resulting diffractive layers. To bring these diffractive imaging and classification systems to shorter wavelengths, such as the visible, IR and higher frequency THz waves, we need to scale down the feature size at each of the fabricated diffractive layers proportional to the wavelength, with a lateral feature size of half a wavelength. Therefore, the purchase of this rapid microfabrication and prototyping equipment will help us create much higher resolution andmonolithically fabricated 3D diffractive optical processors that can operate at shorter wavelengths, covering e.g., visible and IR that we cannot currently cover due to the running costs and/or resolution/precision limitations of our 3D fabrication methods. It will also enable us to have several design iterations cost-effectively and rapidly, advancing the speed of progress in our existing ONR program.Despite its widespread use in research labs worldwide, this unique and powerful microfabrication 3D printer by Nanoscribe does not exist at UCLA. Therefore, purchasing this equipment will also provide an important research infrastructure at UCLA to traina large group of undergraduate and graduate students, involving >40 research trainees in a given year from >10 different departments on campus. Finally, it will significantly strengthen graduate and undergraduate courses at UCLA on Photonics/Optics (taught by thePI), where the students, in groups, will have some hands-on experience and demonstrations on 3D printed optical components. The same instrument will also be used as part of our outreach activities while hosting e.g., high-school students in the form of science demonstrations.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 09, 2024
- Source ID
- N000142412521
Entities
People
- Aydoğan Özcan
Organizations
- Office of Naval Research
- United States Navy
- University of California, Los Angeles