One promising diagnostic tool for viral infection is surface enhanced Raman spectroscopy (SERS), which is a quick, sensitive light scattering technique that uses the energy of the bonds as a fingerprint to identify molecules. SERS yields enhanced Raman signals by positioning analytes near the surface of metal nanostructures and creating localized, electric fields around the metal with a resonant laser. Fundamentally, the vibrational signatures of peptides and proteins rely on their amino acid composition, secondary structure, and local environment. The SERS signals of these species are further complicated by interactions with the metal nanostructures. For instance, the SERS signals of a peptide can differ if the peptide is adsorbed to a gold nanostructured substrate versus a gold nanoparticle. As another example, tryptophan is an important aromatic residue within the binding domain of many proteins, but its SERS signal shows distinct differences from its Raman signal. These changes in tryptophan’s signal can impact the overall signal from the peptides or proteins it comprises. Using SERS for biosensing requires determining the vibrational signature of the target molecule, which then allows for identification. In SERS sensing of viruses, a common concern is signal variability based on the orientation of these large species on the nanostructure surface. Fortunately, capture molecules can improve signal reproducibility by forcing the analyte into a consistent surface orientation, as well as by selectively targeting the analyte to avoid interference. Peptides can be used to bind the surface proteins of viruses and capture them on SERS surfaces to identify their SERS signatures. In this work, we investigate the SERS signals of a SARS-CoV-2 spike-binding peptide both before and after spike protein binding, along with those of tryptophan and tryptophan-containing peptides, on gold SERS surfaces. Understanding the origins of these signals will provide a basis for the design of a peptide-surface protein-based SERS assay for SARS-CoV-2, along with other potential viruses in the future.

Cell cycle progression plays a vital role in regulating proliferation, metabolism and apoptosis. Specifically, assessing cell phase is of significant importance since the development of cancer is tightly linked with the dysregulation of cell cycle. However, investigating the cellular status in three-dimensional in vitro models and tissue is often limited to the complexity of sample preparation and the loss of structural integrity. The most common technique nowadays is flow cytometry, which requires a full disintegration of cellular organization and additional fluorescence staining. To overcome these challenges, Fourier transform infrared (FT-IR) spectroscopic imaging is introduced in this study. It is a powerful approach for analyzing biological samples by detecting the vibrational modes of indigenous molecules, thereby eliminating the need for stains and greatly expanding information beyond phase or intensity contrast of optical imaging. Drawing upon these advantages, we apply FT-IR imaging integrated with unsupervised learning technique to distinguish subtle biochemical compositions between cell phases while retaining a spatial distribution of the innate constituents. The spectral variation in DNA quantity from 2D cell culture is served as an indicator to understand the relative cell cycle stages in a 3D MCF10A acini model. We further evaluate the temporal dependence of these spectral changes throughout the acini formation and validate that cells present to be more proliferative in the early stages of acini formation compared to fully developed acini. Taken altogether, our study presents a computational approach to provide a comprehensive cell phase in tissue-like structure without any requisite for specific biomarker staining, which has the potential to accelerate pharmaceutical agents design with more defined targeted effects. Moreover, the integration of FT-IR spectroscopy and computational methodologies could also expand to the field of pathology and lead to an improvement for clinical diagnostics.

The instrumentation and methods to perform autofluorescence-detected photothermal mid-IR (AF-PTIR) microscopy are demonstrated experimentally and applied for chemically-selective label-free imaging of an active pharmaceutical ingredient (API) within a mixture with common pharmaceutical excipients. In AF-PTIR, the heat released from mid-IR absorption induces changes in two-photon excited UV-fluorescence (TPE-UVF) intensity. The spectral dependence of the fluorescence modulation locally informs on chemical composition with a spatial resolution dictated by the diffraction limit of visible light. AF-PTIR is shown to provide an additional level of selectivity in nonlinear optical imaging by mid-IR spectroscopy enabling mapping of the API distribution in the presence of TPE-UVF and second harmonic generation active excipients (Fig. 1). AF-PTIR provides high selectivity and sensitivity in image contrast for aromatic APIs, complementing broadly applicable commercial methods such as optical photothermal mid-IR (O-PTIR) microscopy. l0pt Figure Figure 1. (a), (c – f) – Bright field, second harmonic generation (SHG), TPE-UVF, AF-PTIR and O-PTIR images of the field of view respectively. (b) – Segmentation results showing the spatial distribution of individual components (lactose particles are shown in blue, indomethacin in green, TiO₂ in yellow and Mg stearate is shown in red).

The ability to simultaneously obtain high spatial resolution images and chemical specific information is of interest in a variety of biological and physical processes. Surface-enhanced Raman scattering (SERS) is particularly suited for this purpose due to its ability to enhance signal from Raman vibrational modes by probing molecules near the surface of plasmonic metal nanostructures. The spatial resolution in SERS imaging is limited by the diffraction limit of light, limiting the resolution to hundreds of nanometers. However, Raman reporter molecules adsorbed to single nanoparticles experience temporal intensity fluctuations that enable the SERS signal to be fit with localization algorithms, such as stochastic optical reconstruction microscopy (STORM). STORM fittings can be applied to generate images with sub-diffraction limited localization of the emitting centers from the nanoparticles. In this work, we demonstrate a wide-field spectrally resolved SERS imaging approach where a transmission diffraction grating placed before the imaging array detector captures the image and first-order diffraction on the same detector. The first-order diffraction corresponds to the SERS spectrum and can be directly correlated to the location and features of a nanoparticle. STORM fitting both the spatial and spectral response results in improved localization in the spatial response and improved peak identification compared to the measured spectra in the spectral response. We show that spatially correlated Raman spectra from multiple nanoparticles in a wide-field of view are readily obtained on a 10-100 ms time scale, which enables spatially resolved monitoring of chemical processes.

We use cryogenic infrared vibrational predissociation spectroscopy of isolated, nitrile-containing vibrational probe molecules to provide benchmarks for the probe molecule spectral response. Popular probes, such as paracyanophenylalanine, and other nitrile-containing molecules are manipulated in solution to modify conformation and charge state prior to extraction and isolation using electrospray ionization and He buffer gas cooling to  10 K. The vibrational spectra of the cold, He- or H2-tagged molecules are collected in a linear predissociation regime and interpreted with the aid of electronic structure calculations. The results provide insight into the intrinsic spectral response of isolated nitrile vibrational reporters decoupled from solvent effects. Vibrational probe molecules are popularly employed to provide spectroscopic readouts of local electrostatic environments in phenomena including bulk solvation dynamics, interfacial proton transfer, and enzyme catalysis. A range of these molecules has been developed, allowing investigators to exploit absorption-free "windows" in the infrared spectrum to ease measurement. However, in the condensed phase it is often a challenge to separate the components of the reporter's response arising from external factors, such as local electric fields or hydrogen bonding, from those due to intrinsic factors such as molecular electrostatic potential or reporter isomerization.

l0pt Figure Although small microplastics pose a huge threat to aquatic environment and biological health, current microplastic monitoring procedures are rather time-consuming and laborious. With the help of the rapid coherent anti-Stokes Raman scattering microspectroscopy as a label-free molecular identification approach, we achieved microplastic monitoring in microfluidics with a high throughput of ~2150 events/s. The spectral refresh rate, i.e. the theoretical highest throughput, is 35 000 events/s by the apparatus, which is the highest speed for flow device monitoring up to the present. Also, we classified PS and PMMA microbeads based on their unique spectral peaks, and the classification was further verified by principal component analysis (PCA). Other sets of results under different flow velocities are further classified and verified by the PCA model trained by the first set of data, with a consistency more than 99%, which demonstrates the repeatability and consistency of our system in rapid monitoring.

Infrared (IR) spectroscopy using Quantum Cascade Lasers (QCLs) is an emerging technology that has opened new possibilities due to its numerous advantages such as shorter acquisition times and high signal-to-noise-ratio measurements. Furthermore, the intrinsic polarized source allows direct probing of other parameters, for instance, the dichroic properties of the samples. In particular, polarimetric detection can enhance structural and chemical contrasts and has been applied for imaging, chemical sensing, and biological tissue classification. While specific optical configurations are known to introduce polarization deviation and thus, less sensitivity in anisotropy detection, the influence on absorbance measurements has been downplayed as a systematic error. In this work, we characterize the polarization effects introduced by optical components. Using full-Stokes’ measurements, we investigate the polarization scrambling and other effects introduced by various factors such as focusing optics, optical coatings, and incident source polarization. With this thorough analysis, we account for most of the polarization deviation factors introduced in typical experimental systems. Lastly, we optimize spectrometer design based on the characterization and demonstrate infrared absorbance spectra of polymer films with higher precision and anisotropy sensitivity.

HFA134a (aka 1,1,1,2 tetrafluoroethane) is the most common propellant in pressure metered dose medical inhalers (PMDIs). Rapid and easy detection of this compound can benefit various human health and performance sectors to identify an unintended medication and confirm adherence. Current medical screening is commonly performed by urinalysis which can be significantly influenced by the rate at which the target compound is processed into urine. As an alternative to urine, breath represents a readily available, easily obtained, and relevant biofluid for airway medication screening while detection of PMDI propellant serves as a more general marker of use. In this study, we demonstrate the novel use of THz spectroscopy, performed with a recently developed table-top THz chemical sensor, to detect and quantify HFA134a in breath as a marker of recent inhaler use at physiologically relevant concentrations. THz chemical analysis facilitates a near instantaneous (few minutes up to 30 minutes) post inhalation detection of propellant. These time scales are shorter than most urinalysis. The compact, and semiautomated nature of the sensor is amenable to rapid analysis on-site with minimal supporting material and components. In this study, we analyzed breath from 10 human subjects. Samples were obtained prior to and after a single dose of an albuterol inhaler. Analysis of the breath samples was performed by the table-top THz sensor and gas chromatography coupled to mass spectrometry (GC-MS) for validation. THz sensing demonstrated reliable detection of HFA134a in nearly all samples. The breath concentrations determined by the THz sensor and GC-MS exhibited exponential decay of breath-HFA134a with time constants varying between 2.5 to 6 minutes. The current sensitivity of the THz sensor allows to monitor HFA143a levels up to 30 minutes post inhalation.

The mid-infrared (MIR) contains the strong absorption signatures of many molecules that are of extreme interest in real-world sensing applications. The miniaturization of spectroscopic sensing equipment made possible by silicon photonics has the potential to revolutionize emission sensing in the MIR. Nanophotonic devices have greatly benefited from telecommunication technology in the near infrared (NIR) region. The industry has reached a level of maturity where high volume production of integrated circuitry can be done at low cost. Silicon based photonic devices can now support optical signals in the MIR past 8 microns with losses approaching those of the telecommunications band [1] making the region attractive for sensing applications. Absorption sensing with photonic devices has been demonstrated in silicon on sapphire, silicon nitride [2], and other silicon-on-insulator platforms. These methodologies have demonstrated the ability to sense analyte concentrations as low as 5000 ppmv (parts per million by volume), which is the workplace limit in many constituencies [3]. We present our current state of research on the development of a high-quality factor MIR silicon-on-sapphire (SOS) photonic gas sensor for use in lab-on-a-chip sensing applications. An optical parametric oscillator (OPO) will be used as a MIR source to pump a grating coupled SOS ring cavity immersed in a controlled CO2 environment. The cavity will be geometrically engineered to allow for high sensitivity spectroscopy of trace CO2 near 2350cm-1. Design was conducted in COMSOL Multiphysics and Lumerical software suites. The sensor was patterned at Applied Nanotools in Edmonton, AB and is currently undergoing characterization in the laboratory at the University of Calgary. [1] R. Shankar et al., Applied Physics Letters, 102, 051108, 2013 [2] C. Ranacher et al., IEEE Photonics Journal, 10 (5), 2018 [3] C. Ranacher et al., Sensors and Actuators A: Physical, 277, pp. 117-123, 2018

Plasmonic nanostructures have paved the way for the development of surface enhanced Raman spectroscopy (SERS); a technique that takes advantage of the Raman signal specific to the molecular vibrational modes. SERS enhances the Raman signal up to 109-fold allowing for lower limits of detection. Through the illumination of the nanostructure with a laser, a localized surface plasmon resonance (LSPR) is excited and further the enhances the electric field at the surface of the nanostructure. While the excitation of the LSPR enhances the Raman signal, it can also generate hot carries that cause the formation of photoproducts that can change the Raman signal. Photoproducts have been reported for various nanostructures in different SERS experiments and can include cross-linking/dimerization, fragmentation, and radical formation. Understanding the parameters and occurrences of these photoproducts will allow for the ability to prevent them when not desired and generate them for further applications. Previously, our group has reported on radical formation with the amino acid tryptophan as well as 4-mercaptobenzoic acid, a common Raman reporter molecule. This work will use changes in the SERS signal to elaborate on the conditions and dynamics of these radical formation reactions associated with the plasmonic activity of nanostructures.