Research Projects

This study proposes an integrated approach for the selective separation and detection of targeted biomolecules from complex fluidic environments. The proposed lab-on-chip platform combines (i) a dielectrophoretic-based particle separation unit, designed to isolate unwanted blood constituents such as RBCs, WBCs, and platelets, with (ii) an absorbance-sensitive fiber optic sensing element. This combination offers a unique solution for selective biomolecule detection through plasmonic absorption. A plasmonic sandwich immunoassay can be achieved by introducing antibody-functionalized plasmonic particles through a buffer channel, guiding them to the optical sensing region. In this process, the plasmonic particles capture the analyte molecules and transfer them to the optical fiber surface for detection and quantification. The proposed project aims to develop a lab-on-chip microfluidic device for detecting target biomolecules in resource-limited settings. The first focus is on designing a dielectrophoretic (DEP) microfluidic device to isolate unwanted blood constituents (e.g., RBCs, WBCs, platelets) using non-uniform electric fields. By optimizing factors like electric field strength, frequency, and channel geometry, the system will effectively separate these components, providing a clean environment for detecting specific biomolecules with high sensitivity. This microfluidic approach reduces sample volume and allows for high-throughput, cost-effective separation. The second step involves integrating an absorbance-sensitive optical fiber sensor into the device. This sensor will detect labeled biomolecules, such as immunoglobulins, through plasmonic particles (e.g., gold nanoparticles) functionalized with antibodies. When the sample is introduced, the antibody-functionalized particles capture the analyte, shifting the plasmonic properties and producing a measurable absorbance change detected by the optical fiber. Finally, the project will optimize assay parameters (e.g., antibody concentration, incubation time), flow conditions, and microstructure dimensions to enhance detection efficiency, reduce false positives, and improve throughput. These optimizations will ensure the system operates effectively with minimal sample volume and in real-time. The overall goal is to create a rapid, integrated lab-on-chip platform that offers a faster and more efficient solution for biomolecule detection in complex samples, making it ideal for real-time diagnostics in resource-poor settings.