Polarized and Evanescent Guided Wave Surface-Enhanced Raman Spectroscopy of Ligand Interactions on a Plasmonic Nanoparticle Optical Chemical Bench
Bibliographic record
Abstract
This study examined applications of polarized evanescent guided wave surface-enhanced Raman spectroscopy to determine the binding and orientation of small molecules and ligand-modified nanoparticles, and the relevance of this technique to lab-on-a-chip, surface plasmon polariton and other types of field enhancement techniques relevant to Raman biosensing. A simplified tutorial on guided-wave Raman spectroscopy is provided that introduces the notion of plasmonic nanoparticle field enhancements to magnify the otherwise weak TE- and TM-polarized evanescent fields for Raman scattering on a simple plasmonic nanoparticle slab waveguide substrate. The waveguide construct is called an optical chemical bench (OCB) to emphasize its adaptability to different kinds of surface chemistries that can be envisaged to prepare optical biosensors. The OCB forms a complete spectroscopy platform when integrated into a custom-built Raman spectrograph. Plasmonic enhancement of the evanescent field is achieved by attaching porous carpets of Au@Ag core shell nanoparticles to the surface of a multi-mode glass waveguide substrate. We calibrated the OCB by establishing the dependence of SER spectra of adsorbed 4-mercaptopyridine and 4-aminobenzoic acid on the TE/TM polarization state of the evanescent field. We contrasted the OCB construct with more elaborate photonic chip devices that also benefit from enhanced evanescent fields, but without the use of plasmonics. We assemble hierarchies of matter to show that the OCB can resolve the binding of Fe2+ ions from water at the nanoscale interface of the OCB by following the changes in the SER spectra of 4MPy as it coordinates the cation. A brief introduction to magnetoplasmonics sets the stage for a study that resolves the 4ABA ligand interface between guest magnetite nanoparticles adsorbed onto host plasmonic Au@Ag nanoparticles bound to the OCB. In some cases, the evanescent wave TM polarization was strongly attenuated, most likely due to damping by inertial charge carriers that favor optical loss for this polarization state in the presence of dense assemblies of plasmonic nanoparticles. The OCB offers an approach that provides vibrational and orientational information for (bio)sensing at interfaces that may supplement the information content of evanescent wave methods that rely on perturbations in the refractive index in the region of the evanescent wave.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".