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An Efficient Framework for Simulating Optical Responses of Dynamically Evolving Periodic Nanoarrays.
Yiting You1, Yuhang Song1, Siyuan Zhang1
1iChem, State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China.
The Journal of Physical Chemistry. A
|June 10, 2026
Summary
We developed an efficient Rank-One Decomposition Discrete Dipole Approximation with Periodic Boundary Conditions (RD-DDA-PBC) to simulate evolving nanoarrays. This method accelerates optical response predictions for dynamic nanophotonic systems.
Area of Science:
- Nanophotonics and Plasmonics
- Computational Electromagnetics
- Materials Science
Background:
- Predicting optical responses of dynamic nanoarrays is vital for sensing, photonics, and optoelectronics.
- Traditional Discrete Dipole Approximation (DDA) with Periodic Boundary Conditions (PBCs) is computationally expensive for evolving systems.
- Accelerated simulation methods are needed for dynamic nanostructure analysis.
Purpose of the Study:
- To extend the Rank-One Decomposition DDA (RD-DDA) method to periodic boundary conditions (PBCs) for simulating dynamically evolving nanoarrays.
- To establish an efficient and accurate framework for modeling the optical behavior of nanoarrays with changing lattice units.
- To enable advanced applications like spectral tracking, kinetic simulations, and inverse design.
Main Methods:
- Developed and implemented the Rank-One Decomposition Discrete Dipole Approximation with Periodic Boundary Conditions (RD-DDA-PBC).
- Coupled RD-DDA-PBC with kinetic Monte Carlo (KMC) simulations for etching kinetics.
- Integrated RD-DDA-PBC with reinforcement learning (RL) for inverse optical geometry design.
Main Results:
- Successfully tracked the spectral evolution of plasmonic nanoarrays during etching and coating.
- Captured transient spectral features of intermediate configurations efficiently.
- Investigated nanoarray etching kinetics under localized electric field enhancement.
- Demonstrated autonomous generation of nanoarray structures with desired spectral features via RL.
Conclusions:
- The RD-DDA-PBC framework provides an efficient method for updating DDA calculations during lattice evolution.
- This framework enables accurate forward spectral tracking and KMC simulations for dynamic nanoarrays.
- The integration with RL offers a powerful approach for inverse design of periodic nanoarrays.
