Citizen science datasets reveal drivers of spatial and temporal variation for anthropogenic litter on Great Lakes beaches.

Accumulation of anthropogenic litter (AL) on marine beaches and its ecological effects have been a major focus of research. Recent studies suggest AL is also abundant in freshwater environments, but much less research has been conducted in freshwaters relative to oceans. The Adopt-a-BeachTM (AAB) program, administered by the Alliance for the Great Lakes, organizes volunteers to act as citizen scientists by collecting and maintaining data on AL abundance on Great Lakes beaches. Initial assessments of the AAB records quantified sources and abundance of AL on Lake Michigan beaches, and showed that plastic AL was >75% of AL on beaches across all five Great Lakes. However, AAB records have not yet been used to examine patterns of AL density and composition among beaches of all different substrate types (e.g., parks, rocky, sandy), across land-use categories (e.g., rural, suburban, urban), or among seasons (i.e., spring, summer, and fall). We found that most AL on beaches are consumer goods that most likely originate from beach visitors and nearby urban environments, rather than activities such as shipping, fishing, or illegal dumping. We also demonstrated that urban beaches and those with sand rather than rocks had higher AL density relative to other sites. Finally, we found that AL abundance is lowest during the summer, between the US holidays of Memorial Day (last Monday in May) and Labor Day (first Monday in September) at the urban beaches, while other beaches showed no seasonality. This research is a model for utilizing datasets collected by volunteers involved in citizen science programs, and will contribute to AL management by offering priorities for AL types and locations to maximize AL reduction.

Effect of Dimensionality on the Photocatalytic Behavior of Carbon-Titania Nanosheet Composites: Charge Transfer at Nanomaterial Interfaces.

Due to their unique optoelectronic structure and large specific surface area, carbon nanomaterials have been integrated with titania to enhance photocatalysis. In particular, recent work has shown that nanocomposite photocatalytic performance can be improved by minimizing the covalent defect density of the carbon component. Herein, carbon nanotube-titania nanosheet and graphene-titania nanosheet composites with low carbon defect densities are compared to investigate the role of carbon nanomaterial dimensionality on photocatalytic response. The resulting 2D-2D graphene-titania nanosheet composites yield superior electronic coupling compared to 1D-2D carbon nanotube-titania nanosheet composites, leading to greater enhancement factors for CO2 photoreduction under ultraviolet irradiation. On the other hand, 1D carbon nanotubes are shown to be more effective titania photosensitizers, leading to greater photoactivity enhancement factors under visible illumination. Overall, this work suggests that carbon nanomaterial dimensionality is a key factor in determining the spectral response and reaction specificity of carbon-titania nanosheet composite photocatalysts.

Prediction range estimation from noisy Raman spectra with robust optimization.

Inferences need to be drawn in biological systems using experimental multivariate data. The number of samples collected in many such experiments is small, and the data are noisy. We present and study the performance of a robust optimization (RO) model for such situations. We adapt this model to generate a minimum and a maximum estimation of analyte concentration for a given sample, producing a prediction range. The calibration model was applied to sets of Raman spectra. In particular we used normal Raman measurements of pyridine/deuterated pyridine mixtures and spectra from a more complex glucose detection system based on surface-enhanced Raman spectroscopy. The results from the RO model were compared with prediction intervals estimated from partial least squares (PLS) method. We find that the RO prediction ranges included the actual concentration value of the sample more consistently than the 99% prediction intervals built with PLS methods.

Progress toward an in vivo surface-enhanced Raman spectroscopy glucose sensor.

BACKGROUND: In this report, we detail our current work towards developing a surface-enhanced Raman spectroscopy (SERS) based sensor for in vivo glucose detection. Despite years of innovations in the development of blood glucose monitors, there remains a need for accurate continuous glucose sensors to provide care to rising numbers of diagnosed diabetes patients and mitigate secondary health complications associated with this metabolic disorder. METHODS: SERS is a highly specific and sensitive optical technique suitable for direct detection of glucose. The SERS effect is highly distance dependent, thus the glucose molecules need to be within a few nanometers or adsorbed to an SERS-active surface. In our sensor, this is achieved with a self-assembled monolayer (SAM) that facilitates reversible interactions between glucose molecules and the surface. The amount of glucose near the surface is proportional to its concentration in the surrounding environment. RESULTS: We determined that the SAM-functionalized surface is stable for at least 10 days and provides rapid, reversible partitioning. In vitro experiments in bovine plasma as well as in vivo experiments in rats demonstrated quantitative detection. CONCLUSIONS: We show successful use of the SERS glucose sensor in rats, making it the first in vivo SERS sensor. Furthermore, we demonstrate free space transdermal detection of a SERS signal through the rat's skin as an initial step toward developing a transcutaneous sensor.

Biosensing with plasmonic nanosensors.

Recent developments have greatly improved the sensitivity of optical sensors based on metal nanoparticle arrays and single nanoparticles. We introduce the localized surface plasmon resonance (LSPR) sensor and describe how its exquisite sensitivity to size, shape and environment can be harnessed to detect molecular binding events and changes in molecular conformation. We then describe recent progress in three areas representing the most significant challenges: pushing sensitivity towards the single-molecule detection limit, combining LSPR with complementary molecular identification techniques such as surface-enhanced Raman spectroscopy, and practical development of sensors and instrumentation for routine use and high-throughput detection. This review highlights several exceptionally promising research directions and discusses how diverse applications of plasmonic nanoparticles can be integrated in the near future.

Lactate and sequential lactate-glucose sensing using surface-enhanced Raman spectroscopy.

Lactate production under anaerobic conditions is indicative of human performance levels, fatigue, and hydration. Elevated lactate levels result from several medical conditions including congestive heart failure, hypoxia, and diabetic ketoacidosis. Real-time detection of lactate can therefore be useful for monitoring these medical conditions, posttrauma situations, and in evaluating the physical condition of a person engaged in strenuous activity. This paper represents a proof-of-concept demonstration of a lactate sensor based on surface-enhanced Raman spectroscopy (SERS). Furthermore, it points the direction toward a multianalyte sensing platform. A mixed decanethiol/mercaptohexanol partition layer is used herein to demonstrate SERS lactate sensing. The reversibility of the sensor surface is characterized by exposing it alternately to aqueous lactate solutions and buffer without lactate. The partitioning and departitioning time constants were both found to be approximately 30 s. In addition, physiological lactate levels (i.e., 6-240 mg/dL) were quantified in phosphate-buffered saline medium using multivariate analysis with a root-mean-square error of prediction of 39.6 mg/dL. Finally, reversibility was tested for sequential glucose and lactate exposures. Complete partitioning and departitioning of both analytes was demonstrated.

In vivo glucose measurement by surface-enhanced Raman spectroscopy.

This paper presents the first in vivo application of surface-enhanced Raman scattering (SERS). SERS was used to obtain quantitative in vivo glucose measurements from an animal model. Silver film over nanosphere surfaces were functionalized with a two-component self-assembled monolayer, and subcutaneously implanted in a Sprague-Dawley rat such that the glucose concentration of the interstitial fluid could be measured by spectroscopically addressing the sensor through an optical window. The sensor had relatively low error (RMSEC = 7.46 mg/dL (0.41 mM) and RMSEP = 53.42 mg/dL (2.97 mM).

Real-time glucose sensing by surface-enhanced Raman spectroscopy in bovine plasma facilitated by a mixed decanethiol/mercaptohexanol partition layer.

A new, mixed decanethiol (DT)/mercaptohexanol (MH) partition layer with dramatically improved properties has been developed for glucose sensing by surface-enhanced Raman spectroscopy. This work represents significant progress toward our long-term goal of a minimally invasive, continuous, reusable glucose sensor. The DT/MH-functionalized surface has greater temporal stability, demonstrates rapid, reversible partitioning and departitioning, and is simpler to control compared to the tri(ethylene glycol) monolayer used previously. The data herein show that this DT/MH-functionalized surface is stable for at least 10 days in bovine plasma. Reversibility is demonstrated by exposing the sensor alternately to 0 and 100 mM aqueous glucose solutions (pH approximately 7). The difference spectra show that complete partitioning and departitioning occur. Furthermore, physiological levels of glucose in two complex media were quantified using multivariate analysis. In the first system, the sensor is exposed to a solution consisting of water with 1 mM lactate and 2.5 mM urea. The root-mean-squared error of prediction (RMSEP) is 92.17 mg/dL (5.12 mM) with 87% of the validation points falling within the A and B range of the Clarke error grid. In the second, more complex system, glucose is measured in the presence of bovine plasma. The RMSEP is 83.16 mg/dL (4.62 mM) with 85% of the validation points falling within the A and B range of the Clarke error grid. Finally, to evaluate the real-time response of the sensor, the 1/e time constant for glucose partitioning and departitioning in the bovine plasma environment was calculated. The time constant is 28 s for partitioning and 25 s for departitioning, indicating the rapid interaction between the SAM and glucose that is essential for continuous sensing.

Glucose sensing using near-infrared surface-enhanced Raman spectroscopy: gold surfaces, 10-day stability, and improved accuracy.

This research presents the achievement of significant milestones toward the development of a minimally invasive, continuously monitoring, glucose-sensing platform based on the optical quantitation of glucose in interstitial fluid. We expand our initial successes in the measurement of glucose by surface-enhanced Raman scattering (SERS), demonstrating substantial improvements not only in the quality and optical properties of the substrate system itself but also in the robustness of the measurement methodology and the amenability of the technique to compact, diode laser-based instrumentation. Herein, we compare the long-term stability of gold to silver film over nanosphere (AuFON, AgFON) substrates functionalized with a partitioning self-assembled monolayer (SAM) using both electrochemical and SERS measurements. AuFONs were found to be stable for a period of at least 11 days. The switch to AuFONs not only provides a more stable surface for SAM formation but also yields better chemometric results, with improved calibration and validation over a range of 0.5-44 mM (10-800 mg/dL). Measured values for glucose concentrations in phosphate-buffered saline (pH approximately 7.4) based on 160 independent SERS measurements on AuFONs have a root-mean-square error of prediction of 2.7 mM (49.5 mg/dL), with 91% of the values falling within an extended A-B range on an expanded Clarke error grid. Furthermore, AuFONs exhibit surface plasmon resonances at longer wavelengths than similar AgFONs, which make them more efficient for SERS at near-infrared wavelengths, enabling the use of low-power diode lasers in future devices.

Rapid detection of an anthrax biomarker by surface-enhanced Raman spectroscopy.

A rapid detection protocol suitable for use by first-responders to detect anthrax spores using a low-cost, battery-powered, portable Raman spectrometer has been developed. Bacillus subtilis spores, harmless simulants for Bacillus anthracis, were studied using surface-enhanced Raman spectroscopy (SERS) on silver film over nanosphere (AgFON) substrates. Calcium dipicolinate (CaDPA), a biomarker for bacillus spores, was efficiently extracted by sonication in nitric acid and rapidly detected by SERS. AgFON surfaces optimized for 750 nm laser excitation have been fabricated and characterized by UV-vis diffuse reflectance spectroscopy and SERS. The SERS signal from extracted CaDPA was measured over the spore concentration range of 10(-14)-10(-12) M to determine the saturation binding capacity of the AgFON surface and to calculate the adsorption constant (Kspore=1.7 x 10(13) M(-1)). At present, an 11 min procedure is capable of achieving a limit of detection (LOD) of approximately 2.6 x 10(3) spores, below the anthrax infectious dose of 10(4) spores. The data presented herein also demonstrate that the shelf life of prefabricated AgFON substrates can be as long as 40 days prior to use. Finally, these sensing capabilities have been successfully transitioned from a laboratory spectrometer to a field-portable instrument. Using this technology, 10(4) bacillus spores were detected with a 5 s data acquisition period on a 1 month old AgFON substrate. The speed and sensitivity of this SERS sensor indicate that this technology can be used as a viable option for the field analysis of potentially harmful environmental samples.

Plasmonic properties of film over nanowell surfaces fabricated by nanosphere lithography.

In this work, a detailed and systematic study of the plasmonic properties of a novel film over nanowell surface is investigated. These nanostructures are fabricated using nanosphere lithography and reactive ion etching and structurally characterized by AFM and SEM. The resulting structures show remarkably narrow plasmon bands in reflectance spectra (as little as 0.10 eV) and greater sensitivity to external dielectric environment than has been seen in other nanoparticle systems, resulting in an improvement in the figure of merit (FOM = refractive index sensitivity (eV.RIU(-1))/full width at half-maximum (eV)) for refractive index sensing. Theoretical modeling for the plasmon spectra of these nanostructures is done using discrete dipole approximation code under periodic boundary conditions. The modeling results match the measurements accurately in aspects of the variation of the plasmon line shape with altering internanowell distance and dielectric environment.