Principal component analysis to enhance enantioselective Raman spectroscopy

Surface potential modulation as a tool for mitigating challenges in SERS-based microneedle sensors

Raman spectroscopic-based biosensing strategies are often complicated by low signal and the presence of multiple chemical species. While surface-enhanced Raman spectroscopy (SERS) nanostructured platforms are able to deliver high quality signals by focusing the electromagnetic field into a tight plasmonic hot-spot, it is not a generally applicable strategy as it often depends on the specific adsorption of the analyte of interest onto the SERS platform. This paper describes a strategy to address this challenge by using surface potential as a physical binding agent in the context of microneedle sensors. We show that the potential-dependent adsorption of different chemical species allows scrutinization of the contributions of different chemical species to the final spectrum, and that the ability to cyclically adsorb and desorb molecules from the surface enables efficient application of multivariate analysis methods. We demonstrate how the strategy can be used to mitigate potentially confounding phenomena, such as surface reactions, competitive adsorption and the presence of molecules with similar structures. In addition, this decomposition helps evaluate criteria to maximize the signal of one molecule with respect to others, offering new opportunities to enhance the measurement of analytes in the presence of interferants.

Chemometric analysis of enantioselective Raman spectroscopy data enables enantiomeric ratio determination

In-line determination of the enantiomeric ratio is still a challenge in process analytical technology (PAT). This study combines enantioselective Raman (esR) spectroscopy with partial least-squares regression (PLSR) to determine the enantiomeric fraction of the chiral molecule (5,6)-diphenyl-morpholin-2-one diluted in dimethyl sulfoxide (DMSO) as a proof-of-concept. Morpholinone derivates are potential candidates for pharmaceutical applications. The PLS weights were carefully analyzed in order to avoid misleading regression results, e.g. caused by sample impurities. A suitable PLSR model was found with two components and it was validated by a leave-one-out cross-validation. The enantiomeric fraction ef₍₊₎ could be calculated with deviations from the prepared ef₍₊₎ in the range of -0.031 and +0.052 from the esR spectra recorded at a half-wave retarder angle of 30.0°.