Engineered photonic materials for the unconventional control of light represent an exciting frontier in photonics and materials science. These artificially structured optical media, including but not limited to photonic crystals, plasmonic components, and optical metamaterials, have led to transformative changes in the field. While most photonic structure design has relied on a conventional trial-and-error approach via iterative numerical modelling, there has recently been a growing trend toward exploring artificial intelligence and machine learning. While still in its infancy, this emerging area of research has included advances in artificial-intelligence-enabled design of engineered photonic materials that may revolutionize the way we discover, design, and use photonic materials and devices in the future.
This feature issue will cover the latest advances in artificial intelligence and photonic design. Contributions focused on how deep learning and optimization schemes can be exploited for the design of photonic materials, and conversely, on how optics can be used for the implementation of machine learning, as well as other emerging topics at the interface of artificial intelligence and photonics, are welcome.
Topics to be covered include but are not limited to:
All papers need to present original, previously unpublished work, and will be subject to the normal criteria and peer-review process of the Journal. The standard OMEx publication charges will apply to all published articles.
Manuscripts must be prepared according to the usual guidelines for submission to Optical Materials Express and must be submitted online through OSA's electronic submission system. When submitting, authors should specify that the manuscript is for the "Artificial Intelligence Meets Engineered Photonic Materials" feature issue (choose from the drop-down menu).