UCLA

Surface plasmons (SPs) are coherent delocalized electron oscillations that exist at the metal-dielectric interface. The charge motion in the surface plasmon creates intense electromagnetic fields at certain locations of the interface, which are referred to as "hot spots". The intense electromagnetic field associated with the excitation of surface plasmons has found applications in various bio-sensing techniques.

A unique plasmonic hybrid platform, graphene-Au pyramid structure, was invented by our group. The hybrid platform provides an ultra intense surface plasmon field and has a bio-compatible surface, making it a powerful tool for bio-sensing. The work to refine the nanostructure for generation of stronger surface plasmon field has been intensively explored by my group mates. Aside from generation of stronger surface plasmon fields, this research was done to improve several surface plasmon based techniques through the hybrid platform and to explore their applications in the label free bio-sensing field. The ultimate goal of my thesis work is to develop an integrated system for biological detection and analysis with high sensitivity and specificity.

In the bio-sensing field, especially in regards to remote detection in an analyte, the biological entities (e.g. biomolecules and cells) of interest are always dispersed in the solution. This would be a concern if we were using plasmon resonance powered techniques by themselves. The first part of this research focuses on Plasmonic tweezers, a manipulation technique to attract and capture biological entities onto the plasmonics surface. Plasmonic tweezers is noninvasive manipulation technique, in which a near-field gradient force is generated by the surface plasmon field around hot spots. It can be used to precisely control the position of biological entities. However, the near-field property of plasmonic tweezer limits its functional range in capturing biological samples. To remedy this problem, electrostatic bias is used in conjunction with plasmonic tweezers. Electrostatic bias produces a long range force whose effects spread across the entire space between a pair of electrodes. It compensates for the plasmonic tweezers’ short range limitation by “condensing” molecules throughout the analyte to a layer immediately adjacent to the plasmonic surface. By using plasmonic tweezers and an electrostatic force together, the biological entities can be confined to sub-wavelength dimensions near the hot spots. For the plasmonics based bio-detection methods, the hot spots are always where the signal generates from. Therefore, this self-aligned trapping method is used to effectively increase the sensitivity and selectivity of bio-sensing techniques.

After the biological entities are attracted to the plasmonics surface, the next step is to develop specific detection techniques. The second part of this thesis is to demonstrate the capability of the surface-enhanced Raman spectroscopy (SERS) techniques based on a nanopyramid array hybrid platform. SERS is a surface-sensitive technique employing strong plasmon resonance fields to enhance the Raman signal by several orders of magnitude. This enables even the detection of single molecules. Also, compared with other nanostructures, the hybrid platform has distinct advantages. The nanopyramid array is an open structure, in which hot spots are located between neighboring pyramids. As such, large biomolecules and biological entities can easily move into these regions and their Raman signals can be enhanced. By introducing single layer graphene, the hybrid platform provides a bio-friendly surface, preventing biological entities from being affected by toxic metals such as silver. The signal of the graphene layer can also serve as a built-in gauge of local electromagnetic field intensity used to indicate the distribution of the hot spots. These properties make the hybrid platform a powerful tool for biological detection and analysis. In this thesis work, the hybrid platform is employed to generate SERS signals of biological samples, in particular, the characterization of exosomes and T-cells. However, the biological entities would naturally bring variations to the SERS signals due variations in the type and quantity of their chemical compositions. In our research, principle component analysis (PCA) is also employed to interpret the SERS data and provide a statistical investigation of the biological samples.

To achieve dynamic monitoring of biological processes, higher sensitivity and temporal resolution are preferred. In the last part of this thesis, another label free bio-sensing technique, surface-enhanced coherent anti-Stokes Raman spectroscopy (SECARS), was developed based on the hybrid platform. A multiplicative enhancement of the Raman signal over CARS and SERS is achieved using a novel SECARS setup. Compared to previous setups, it shows a broadband feature with high spectral resolution, which is preferred in biological detection. The novel setup based on the hybrid platform could be a powerful tool for not only the characterization of biological entities but also the dynamic monitoring of various biological processes.