Highly accurate, efficient, and fabrication tolerance-aware nanostructure prediction for high-performance optoelectronic devices.

ABSTRACT: Despite extensive efforts to predict optimal nanostructures for enhancing optical devices, a more accurate, efficient, and practical method for nanostructure optimisation is required. In particular, fabrication tolerance is a promising avenue for significantly improving manufacturing efficiency; however, research in this area is limited. In this study, we introduce a practical approach for enhancing the performance of optoelectronic devices using an artificial intelligence (AI)-based nanostructure optimisation strategy. We optimised a support vector regression (SVR) model to capture the complex and nonlinear relationships between the transmittance and nanograting structure variables with the goal of improving optoelectronic devices. Our versatile model accurately predicted the continuous t

SUBMITTER: Jeong WK 

PROVIDER: S-EPMC11615345 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature