Date of Award
8-2026
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Electrical Engineering and Computer Science
First Advisor
Md Selim Habib
Second Advisor
Yakov Berchenko-Kogan
Third Advisor
Naveed Mahmud
Fourth Advisor
Brian A. Lail
Abstract
Anti-resonant hollow-core fibers (AR-HCFs) offer promising capabilities as a trans formative technology for next-generation photonics. By guiding light primarily in air rather than solid silica, they enable light to travel faster, presenting a fiber with sig nificantly reduced latency, high power handling, and broadband transmission. These advantages make them a promising product for future telecom systems. Accurate nu merical modeling of such fabricated structures is essential to capture the potential of a given design, particularly for predicting and minimizing surface scattering loss. Surface scattering in AR-HCFs is governed by the Rayleigh Criterion, which depends on nanoscale roughness and geometric irregularities at the air-glass interfaces. There fore, converting Scanning Electron Microscope (SEM) figures into precise vector-based simulation geometries is critical. However, raw SEM images often suffer from edge frag mentation, noise (e.g dust particles), and imperfections in fabrication which translate into deformations that challenge conventional edge detection methods and complicate tube identification by popular methods like the Hough Transform (H.T). The aim of this project is to design a fully automated workflow which identifies the tubes present in an AR-HCF design given a SEM, approximates the design with a geometry that minimizes the surface scattering loss while still resembling the original geometric de sign, and simulates such design in COMSOL to evaluate the potential of the AR-HCF. The framework compares various approaches to detect, group, and reconstruct edge segments into coherent structural components. Among the different approaches the paper compares, deep learning techniques are included. This automated characterization tool bridges the gap between fabrication and high-fidelity modeling, accelerating the development of next-generation AR-HCFs.
Recommended Citation
Garcia Arana, Daniel, "From Micrograph to Simulation: Automating the Structural Analysis of Anti-Resonant Hollow-Core Fibers" (2026). Theses and Dissertations. 1659.
https://repository.fit.edu/etd/1659