Foundry-based waveguide-enhanced Raman spectroscopy in the visible.

Waveguide-enhanced Raman spectroscopy (WERS) is an analytical technique frequently employed for chemical and biological sensing. Operation at visible wavelengths to harness the inverse fourth power with excitation wavelength signal scaling of Raman scattering intensity is desirable, to combat the inherent inefficiency of Raman spectroscopy. Until now, WERS demonstrations in the visible have required custom materials and fabrication, resulting in high losses and low yields. In this work, we demonstrate a silicon nitride (SIN) visible WERS platform fabricated in a 300 mm complementary metal-oxide semiconductor (CMOS) foundry. We measure the propagation loss, coupling loss, WERS signal, and background for WERS spirals designed for 532 nm and 633 nm pump wavelengths. We compare these results to the state-of-the-art near-infrared WERS platform at 785 nm. Further, we theoretically validate the relative performance of each of these WERS configurations, and we discuss the optimal WERS configuration at visible wavelengths. We conclude that a configuration optimized for 785 nm pumping provides the greatest signal-to-background ratio in the fingerprint region of the spectrum, and pumping at 633 nm maximizes Stokes signal out to 3000 cm-1.

Quantitative Raman Cross-Sections and Band Assignments for Fentanyl and Fentanyl Analogs.

Raman cross sections and spectra were measured for five synthetic opioid fentanyl analogs: fentanyl citrate, sufentanil citrate, alfentanil HCl, carfentanil oxalate, and remifentanil HCl. The measurements were performed with excitation wavelengths in the visible (532 nm) and near infrared (785 nm). In addition, density functional theory (DFT) calculations were employed to generate simulated spectra of the compounds and aid in identification of the observed spectral modes. These cross-section measurements and calculations were also used to assess results from a series of measurements of fentanyls cut with other powdered materials. These measurements are valuable for assessment of field-deployable Raman chemical sensors for detection of fentanyl and fentanyl analogs, including when mixed with other materials.

Semi-automated detection of trace explosives in fingerprints on strongly interfering surfaces with Raman chemical imaging.

We have previously demonstrated the use of wide-field Raman chemical imaging (RCI) to detect and identify the presence of trace explosives in contaminated fingerprints. In this current work we demonstrate the detection of trace explosives in contaminated fingerprints on strongly Raman scattering surfaces such as plastics and painted metals using an automated background subtraction routine. We demonstrate the use of partial least squares subtraction to minimize the interfering surface spectral signatures, allowing the detection and identification of explosive materials in the corrected Raman images. The resulting analyses are then visually superimposed on the corresponding bright field images to physically locate traces of explosives. Additionally, we attempt to address the question of whether a complete RCI of a fingerprint is required for trace explosive detection or whether a simple non-imaging Raman spectrum is sufficient. This investigation further demonstrates the ability to nondestructively identify explosives on fingerprints present on commonly found surfaces such that the fingerprint remains intact for further biometric analysis.