Microscale concave interfaces for structural reflective coloration

In everyday life, humans and machines rely on different colors to process important information. As modern physics advanced, our understanding of color generation expanded greatly, and different coloration phenomena were able to be characterized; some of which include optical dispersion (e.g. prism-induced rainbows), spectrally selective absorption (e.g. chemical pigments and resonant photonic structures), and thin-film interference (e.g. bubble and oil membranes).

Structural colors in particular rely on optimizing their geometry to produce color, rather than utilize pigments or dyes. These structural coloration strategies have attracted considerable scientific and industrial interests because of their unique ability to manipulate the flow of light. In particular, a total internal reflection (TIR) interference introduced by microscale concave interfaces (MCI) was recently proposed, different from conventional coloration processes.

It was believed that the incorporation of this new color creation mechanism into large scale displays and sensors is exciting but challenging to achieve. This NSF project will first perform a combined fundamental and experimental research to clarify the physical mechanism of this MCI. The major focus is to explore unambiguous physical mechanism of this new MCI structure, which will be validated through fabrication and systematic experimental characterization.

Building upon these new optical interface structures, hybrid visible and infrared display technologies will be explored for light detection and ranging (LIDAR) applications. Realization of this new reflective coloration strategies is expected to yield important technological breakthroughs in information and display applications. The proposed micro-optics structure will foster the research and development with the broader impact on traffic safety, national security and sustaining the global leadership in photonics technologies.

This research will be closely integrated with educational programs at University at Buffalo (UB). The research will inform development of new courses on Green Optoelectronic Devices and Senior Design Implementation. The research and current and future technology trends will be presented to a broader audience including K-12 teachers and students, and the general public.

The investigator’s team developed a new MCI structure that can realize a unique reflective structural color, i.e., under different external optical illumination conditions, it can realize colorful retroreflection and iridescent reflection, respectively. It was believed that this type of structural coloration platform is different from conventional physical processes and can enable the exploration of new color display technologies and applications.

Although it is generally agreed that this new reflective color is introduced by TIR inside the concave interface, a complete and accurate explanation to the coloration mechanism is still missing. This NSF project will first perform a combined fundamental and experimental research to clarify the physical mechanism of this MCI using thorough theoretical modeling and experimental validation.

A combined ray-tracing and light coherent superposition modeling strategy will be developed to reveal the optical interference mechanism of the MCI structure. The color tunability by controlling the geometric and refractive index parameters will be investigated systematically using this combined modeling. Building upon the fundamental understanding of the new coloration mechanism, the investigator will develop traffic sign samples to explore smart signs for future remote sensing/imaging for autopilot systems.

In particular, the time-of-flight of the laser from the LIDAR system will be characterized systematically to reveal the potential of the MCI in future autopilot applications. Due to the TIR-induced retroreflection feature, this type of new structure is especially suitable for low light environment (e.g. night-time traffic signs, advertisement boards, darkroom decoration for entertainment, etc.) and is promising to address the robust physical-world attacks on current deep learning visual classification used in LIDAR systems.

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.