Chen, W., Yang, S., Yan, Y., Gao, Y., Zhu, J., & Dong, Z. (2025). Empowering nanophotonic applications via artificial intelligence: pathways, progress, and prospects. Nanophotonics, 14(4), 429–447. https://doi.org/10.1515/nanoph-2024-0723
Abstract:
Empowering nanophotonic devices via artificial intelligence (AI) has revolutionized both scientific research methodologies and engineering practices, addressing critical challenges in the design and optimization of complex systems. Traditional methods for developing nanophotonic devices are often constrained by the high dimensionality of design spaces and computational inefficiencies. This review highlights how AI-driven techniques provide transformative solutions by enabling the efficient exploration of vast design spaces, optimizing intricate parameter systems, and predicting the performance of advanced nanophotonic materials and devices with high accuracy. By bridging the gap between computational complexity and practical implementation, AI accelerates the discovery of novel nanophotonic functionalities. Furthermore, we delve into emerging domains, such as diffractive neural networks and quantum machine learning, emphasizing their potential to exploit photonic properties for innovative strategies. The review also examines AI’s applications in advanced engineering areas, e.g., optical image recognition, showcasing its role in addressing complex challenges in device integration. By facilitating the development of highly efficient, compact optical devices, these AI-powered methodologies are paving the way for next-generation nanophotonic systems with enhanced functionalities and broader applications.
License type:
Attribution 4.0 International (CC BY 4.0)
Funding Info:
This research / project is supported by the National Research Foundation, Singapore - Competitive Research Programme
Grant Reference no. : NRF-CRP30-2023-0003
This research / project is supported by the Agency for Science, Technology and Research - Career Development Award
Grant Reference no. : C210112019
This research / project is supported by the Agency for Science, Technology and Research - Manufacturing, Trade, and Connectivity (MTC) Individual Research Grant
Grant Reference no. : M21K2c0116
This research / project is supported by the Agency for Science, Technology and Research - Manufacturing, Trade, and Connectivity (MTC) Individual Research Grant
Grant Reference no. : M22K2c0088
This research / project is supported by the National Research Foundation, Singapore - Quantum Engineering Program 2.0
Grant Reference no. : NRF2021-QEP2-03-P09