Magnetic Field-Enhanced SERS Detection of Hemozoin Biomarkers from Blood Using Ag Nanorods

This study presents a portable and highly sensitive method for point-of-care malaria detection in blood samples, leveraging the nanoscale plasmonic properties of glancing angle deposition (GLAD)-fabricated silver nanorod (AgNR) substrates for surface-enhanced Raman spectroscopy (SERS). The vertically aligned and anisotropic AgNR architecture enables the formation of dense electromagnetic hotspots, facilitating enhanced interaction with target analytes. The detection strategy focuses on hemozoin, a paramagnetic crystalline byproduct of the malaria parasite, which serves as an intrinsic biomarker. To further improve analyte localization at plasmonic hotspots, an external magnetic field (0.3 T) was applied during Raman measurements, exploiting the paramagnetic nature of hemozoin. The application of the magnetic field resulted in a 10-fold increase in SERS signal intensity compared to conventional measurements without magnetization. Distinct spectral differences were observed between healthy and malaria-positive samples. Magnetically assisted SERS achieved a limit of detection (LOD) as low as 10 –14 M (6 parasites/μL), significantly outperforming the LOD of 10 –12 M (616 parasites/μL) obtained without the magnetic field. Notably, this study demonstrates label-free, direct detection from whole blood without any preprocessing, requiring only a few microliters of sample. Distinct spectral differences were observed between healthy and malaria-positive samples, where hemozoin-specific Raman signatures were selectively amplified over background hemoglobin signals. Principal component analysis (PCA) of SERS data from clinical whole blood and plasma samples showed clear separation between healthy and infected cohorts, with magnetically enhanced measurements exhibiting improved sensitivity and clustering. Overall, this work highlights the synergistic role of nanoscale AgNR architecture and magnetic field-assisted analyte enrichment in enabling rapid, label-free, and field-deployable malaria diagnostics, with strong potential for early-stage infection detection in resource-limited settings.