In a recent study published in the Journal of Physical Chemistry, a team of researchers demonstrated that a controlled molecular surface functionalization technique can be used for detecting a variety of textured gold surfaces.
Developing an effective analytical sensing technique with high sensitivity and specificity for a wide range of target analytes is a constant requirement for breakthroughs in diagnostics.
Significant challenges in the field of analytical spectroscopy and molecular diagnostics can be overcome by combining the highly sensitive characteristics of surface-enhanced Raman spectroscopy with highly specific analyte recognition characteristics via molecular surface functionalization.
Researchers utilized self-assembled benzyl-terminated and benzoboroxole-terminated monolayers to examine which thicknesses and root-mean-square (RMS) roughness of planar gold provide the most sensitive and specific surfaces, resulting in the molecularly surface-functionalized surface-enhanced Raman spectroscopy platforms.
Potential of Sensing via Molecular Functionalization
Molecular functionalization-based sensing can offer superior analytical selectivity for various applications, including catalysis, drug administration, sensors, and chromatographic separation.
Surface molecular imprinting, which involves in situ surface polymerization of functional monomers in the presence of a template molecule, is an example of molecular functionalization.
The polymerization leaves behind artificial receptors in nanocavities on surfaces complementary to the target template in terms of shape, size, and functional group orientation.
In functionalized recognition platforms, target affinity and selectivity are achieved using a variety of surface contacts that combine hydrogen bonds, electrostatic interactions, van der Waals forces, or covalent bonds.
Surface Enhanced Raman Spectroscopy as a Transduction Technique
Surface functionalization alone cannot fulfill the requirements for a sensor in detecting applications. A transduction approach must be used to transform the molecular interaction into a detectable signal.
Surface-enhanced Raman spectroscopy can be used as a transduction technique to increase the Raman signal of molecules adsorbed on a nano-roughened noble metal surface. Surface-enhanced Raman spectroscopy produces distinctive molecular fingerprints of vibrational spectra, enabling a quick and very sensitive technique of sensing transduction.
Evaluation of Effects of Gold Thickness and Roughness Parameters on the Surface Enhanced Raman Spectroscopy
The thickness and nano-roughness of gold must be determined to get the highest level of molecular surface functionalization and surface-enhanced Raman spectroscopy effect. De Carvalho et al thoroughly assessed the impact of a wide variety of gold thickness layers and roughness parameters on the Surface-enhanced Raman spectroscopy effect and the molecular surface functionalization. The biochemical analysis of the Raman spectral data provides a strong foundation for choosing the best substrates, which is a necessary step in developing the viability of molecular imprinting for surface-enhanced Raman spectroscopy applications.
Experimentally, the researchers used two types of self-assembled monolayers (SAM) to investigate and improve surface-enhanced Raman spectroscopy detection on functionalized gold surfaces. The SAMs in both functionalizations are terminated with acrylamide, which is generally utilized as a base to design the molecularly imprinted surfaces.
The functional group contains the differences between the SAM. One is equipped with a benzoboroxole (BNB) functional group, which forms reversible covalent bonds with the hydroxyl groups of carbohydrates to bind to them. A second lacks carbohydrate binding due to its benzyl functional group. Melezitose (Mel) is a trisaccharide that is used to illustrate the differences in the selective binding of the BNB-terminated SAM and the benzyl-terminated SAM, as well as the various planar gold thickness and roughness.
The trisaccharide melezitose was used as an example analyte while the researchers methodically investigated planar gold films of varied thicknesses and roughnesses and evaluated the impact on molecular surface functionalization.
The ideal gold layer thickness was 80 nm with an RRMS of 7.2 nm. This was demonstrated by an algorithmic analysis using PCA and SOM, two unsupervised machine learning techniques. Peaks were assigned after thoroughly analyzing the pre-and post-melezitose application BNB-terminated SAM Raman spectra.
A clear increase in pre- and post-melezitose cluster separation in PCA scores space was detected. A 30% increase in classification accuracy for the BNB-terminated SAM compared to the pre-and post-melezitose states was achieved for the pristine gold and benzyl-terminated SAM surface.
PCA clearly showed the advantage of 80 nm-thick gold films functionalized with BNB-terminated molecules for melezitose detection. With improved surface-enhanced Raman spectroscopy signal and analyte sensitivity, an ideal functionalization was found for gold substrates with an RMS of 3.5 nm and an 80 nm thickness.
A SOM analysis showed more distinct clusters for the two BNB-terminated states. With the potential of additional investigation, mechanisms have been presented to characterize the intricate nature of the signal variations seen. To provide a foundation for additional theoretical investigations of plasmonic effects, electromagnetic models based on experimentally recorded AFM topographies were carried out, with 10 nm and 80 nm thick films providing the highest improvements.
De Carvalho Gomes, P., Hardy, M., Tagger, Y., Rickard, J. J. S., Mendes, P., & Oppenheimer, P. G. (2022). Optimization of Nanosubstrates toward Molecularly Surface-Functionalized Raman Spectroscopy. The Journal of Physical Chemistry C. https://pubs.acs.org/doi/10.1021/acs.jpcc.2c03524