Chromatographic framework for coffee ring effect-driven separation of small molecules in surface enhanced Raman spectroscopy analysis

A surface chemistry perspective on SERS: revisiting the basics to push the field forward

Surfaces are well known to be complex entities that are extremely difficult to study, and any phenomenon that is related to them is consequently challenging to approach. Moving from the bulk to the nanoscale adds a further layer of complexity to the problem. Because SERS relies on surfaces at the nanoscale, a rigorous understanding of the chemical phenomena that concur in the observation of the SERS signal is still limited or disorganized at best. Specifically, the lack of understanding of the chemical properties of nanoparticle surfaces has direct consequences on the development of SERS-based devices, causing a widespread belief that SERS is an inherently unreliable and fundamentally irreproducible analytical technique. Herein, we discuss old and new literature from SERS and related fields to accompany the reader through a journey that explores the chemical nature and architecture of colloidal plasmonic nanoparticles as the most popular SERS-active surfaces. By examining the chemistry of the surface landscape of the most common SERS colloids and the thermodynamic equilibria that characterize it, we aim to paint a chemically realistic picture of what a SERS analyst deals with on a daily basis. Thus, our goal for this review is to provide a centralized compilation of key, state-of-the-art surface chemistry information that can guide the rational development of analytical protocols and contribute an additional path through which our community can continue to advance SERS as a reliable and robust analytical tool.

Analytical applications of droplet deposition Raman spectroscopy

The droplet deposition methods in Raman spectroscopy have received considerable attention in the field of analytical sensing focusing on effective pre-concentration of the studied analyte (coffee-ring effect or small spots). This review covers different analytical applications of drop-coating deposition Raman scattering (DCDRS) and droplet deposition surface-enhanced Raman scattering (SERS) spectroscopy. Two main advantages of droplet deposition Raman techniques are considered: the drying-induced segregation of the components from the mixtures (such as body fluids) and the sensitivity of detection of various analytically important molecules. Some recent advanced applications, including clinical cancer diagnosis, are discussed and summarized. Finally, the potential and further perspectives of the droplet deposition Raman methods for analytical studies are introduced.

Fabrication of localized surface plasmon resonance sensors with scalable polyvinyltetrazole/copper cluster hybrid ring-array for Cu(II) detection

The bottom of a hole-array photoresist template deposited with a hydrophobic atom-transfer radical polymerization (ATRP) initiator was wetted by treatment with oxygen plasma. After the removal of the photoresist template, ring patterns of the ATRP initiator were formed at the interface between the hydrophobic and wetting regions. Polyacrylonitrile (PAN) was grafted from the initiator ring array to covert to polyvinyltetrazole (PVT) rings via a cyano-to-tetrazole reaction, which could adsorb Cu(II) at various concentrations. The Cu(II) ions within the PVT rings were reduced to form a PVT-copper hybrid ring (VCHR), resulting in a blue-shift of the localized surface plasmon resonance (LSPR) peak as the Cu(II) was adsorbed by the PVT rings. The blue-shift and Cu(II) concentration were linearly correlated, with a detection limit of ∼25 pg mL^-1 and a linear range of 25-400 pg mL^-1 for Cu(II) detection. Although the PVT rings also chelated Pb(II) and Cr(III), these ions did not exhibit obvious LSPR peaks. The VCHR LSPR sensor exhibited excellent selectivity for Cu(II) detection. Combining lithography and plasma technology provides a versatile platform for developing the scalable ring structure of copper for highly sensitive and selective Cu(II) sensing.