Micromachining Error Tolerance Analysis in EEG Sensing Nanostructure Arrays: Control of Fano Resonance for Enhanced Performance
Year: 2025
Type: article
Abstract: The silicon-based electroencephalography (EEG) sensing technology encounters performance limitations due to spectral distortions caused by micromachining, which significantly degrade its effectiveness in Brain-Computer Interface (BCI) systems. To enhance the performance of EEG sensors, this study systematically investigates the tolerance of micromachining errors in silicon-based nanostructured arrays, specifically focusing on photonic crystal nanobeam cavities (PCNCs) used in optical EEG sensing systems. We propose a comprehensive error control methodology that integrates finite-difference time-domain (FDTD) simulations with multivariate linear regression (MLR) analysis to quantitatively assess the impact of lithographic and alignment errors on Fano resonance spectral characteristics. Our analysis establishes critical tolerance boundaries: horizontal displacement errors must be maintained within –4.56 nm to +26.31 nm, and angular deviations should be constrained between –0.068° and +0.083°. By establishing precise tolerance boundaries, our approach effectively mitigates spectral distortion while enhancing production yield, thereby ensuring manufacturing consistency. Notably, this study aligns with the fundamental objective of precision allocation in conventional silicon nanocomponents: achieving target performance metrics with cost efficiency.
Source: IEEE photonics journal
Authors: Huicheng He, Zhanzhe Huang, Huazhen Shi, Ziying Wang, Hongxia Zhang, Dagong Jia
Institutions: Tianjin University, Hebei University of Technology
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,075
Awards: G1519892830, G5740016753
OpenAlex ID: W4411203465