Abstract

This thesis examines the development of non-enzymatic glucose sensors by engineering advanced electrode materials based on metal-organic frameworks (MOFs). Conventional enzymatic glucose sensors, although widely used, suffer from inherent limitations, including poor long-term stability, narrow operating conditions, and sensitivity to environmental factors, due to their reliance on biological enzymes. Non-enzymatic sensors offer a more robust alternative by enabling direct electrochemical oxidation of glucose on engineered electrode surfaces. MOFs represent a highly tunable class of hybrid materials with structural and chemical features that are ideal for sensor applications, including a high surface area, tailored porosity, and excellent thermal and chemical stability. This work focuses explicitly on copper-based MOFs (Cu-MOFs), which have demonstrated promising electrochemical activity and redox behavior suitable for glucose detection. A key objective of this study is to optimize the material composition by systematically investigating the effect of the metal-to-linker ratio on the structural, morphological, and electrochemical properties of the resulting MOFs. The synthesized materials were characterized using various techniques, including XRD, SEM, BET, and electrochemical methods, to evaluate their performance as electrode materials. Results show that fine-tuning the metal-to-ligand ratio has a significant influence on the sensor’s sensitivity, selectivity, and stability. Optimized Cu-MOF electrodes exhibited enhanced electron transfer kinetics and higher catalytic activity toward glucose oxidation. This research highlights the critical role of material design and compositional engineering in the development of high-performance, enzyme-free electrochemical glucose sensors.

School

School of Sciences and Engineering

Department

Mechanical Engineering Department

Degree Name

MS in Mechanical Engineering

Graduation Date

Winter 1-31-2026

Submission Date

9-18-2025

First Advisor

Mohamed Serry

Second Advisor

Ehab Elsawy

Committee Member 1

Adel Elshabasy

Committee Member 2

Mohamed Elmorsi

Extent

62 p.

Document Type

Master's Thesis

Institutional Review Board (IRB) Approval

Not necessary for this item

Disclosure of AI Use

Thesis text drafting; Thesis editing and/or reviewing

Available for download on Friday, September 18, 2026

Share

COinS