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Figure 1.

Surface-enhanced Raman scattering (SERS) nanoparticles.

(a) Multiple flavors of nanoparticles exist where each nanoparticle contains a gold core coated with a Raman-active layer, encased in a silica shell. (b) Raman spectra of five nanoparticle flavors. (c) Example result from a least-squares routine showing the ability to demultiplex two different nanoparticles from a mixture under noisy conditions.

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Figure 2.

Quality Metrics.

Simulations of composite error as a function of two different spectral quality metrics, RFE (Eq. (3)) and SRI (Eq. (4)). Note that the RFE metric is highly sensitive to the broadband background level (B vs. 10B) whereas the SRI metric is relatively insensitive to these variations in background and provides a better indication of the “goodness-of-fit” for the SERS nanoparticles themselves.

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Figure 3.

Measurement apparatus.

(a) A spectrometer with CCD detector is used to capture Raman signals from a nanoparticle sample illuminated with a 785-nm laser source. See text for details. (b) Example of a strong signal with a high SRI and (c) a weak signal with a lower SRI, in which noise and broadband background signals increasingly dominate over the SERS signals. Representative SERS peaks are numbered 1–4 and the peak of the broadband background is labeled with a star.

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Figure 4.

Spectral quality characterization of single-flavor samples.

(a) Weights returned by the least-squares routine are linear over the range of measured concentrations. (b) Errors from multiple measurements of the same single-flavor sample are normally distributed. Shaded region indicates where 80% of the errors lie. (c) A plot of error vs. SRI, in which the reported error is the 80% confidence bound (e80). The simulations agree well with the results found experimentally.

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Figure 5.

Spectral quality characterization of two-flavor mixtures.

(a) Composite errors for multi-particle mixtures are gamma-distributed. Vertical lines indicate bounds for the 80th percentile of error values (e80) that may occur for a particular SRI. (b) A plot of error (e80) vs. SRI for a 1∶1 mixture of particle flavors and a 5∶1 mixture of flavors. Simulations (solid lines) closely predict experimental results. (c) A plot of the minimum SRI required to ensure a composite error ≤10% with 80% confidence. This dual-flavor example shows how the minimum SRI value depends upon the mixture ratio.

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Figure 6.

Spectral quality characterization of three-flavor mixtures.

The plot shows percent error (e80) in the ratio between particle flavors as a function of SRI.

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Figure 7.

Algorithm summary.

A flowchart illustrating how SRI may be used in practice to ensure that a SERS-based multiplexed molecular diagnostic is reliable. See text for details.

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