Fluorescence excitation-emission matrix regional integration to quantify spectra for dissolved organic matter

Excitation-emission matrix (EEM) fluorescence spectroscopy has been widely used to characterize dissolved organic matter (DOM) in water and soil. However, interpreting the > 10,000 wavelength-dependent fluorescence intensity data points represented in EEMs has posed a significant challenge. Fluorescence regional integration, a quantitative technique that integrates the volume beneath an EEM, was developed to analyze EEMs. EEMs were delineated into five excitation-emission regions based on fluorescence of model compounds, DOM fractions, and marine waters or freshwaters. Volumetric integration under the EEM within each region, normalized to the projected excitation-emission area within that region and dissolved organic carbon concentration, resulted in a normalized region-specific EEM volume (phi(i,n)). Solid-state carbon nuclear magnetic resonance (13C NMR), Fourier transform infrared (FTIR) analysis, ultraviolet-visible absorption spectra, and EEMs were obtained for standard Suwannee River fulvic acid and 15 hydrophobic or hydrophilic acid, neutral, and base DOM fractions plus nonfractionated DOM from wastewater effluents and rivers in the southwestern United States. DOM fractions fluoresced in one or more EEM regions. The highest cumulative EEM volume (phi(T,n) = sigma phi(i,n)) was observed for hydrophobic neutral DOM fractions, followed by lower phi(T,n) values for hydrophobic acid, base, and hydrophilic acid DOM fractions, respectively. An extracted wastewater biomass DOM sample contained aromatic protein- and humic-like material and was characteristic of bacterial-soluble microbial products. Aromatic carbon and the presence of specific aromatic compounds (as indicated by solid-state 13C NMR and FTIR data) resulted in EEMs that aided in differentiating wastewater effluent DOM from drinking water DOM.

Omnidirectionally Stretchable High-Performance Supercapacitor Based on Isotropic Buckled Carbon Nanotube Films

The emergence of stretchable electronic devices has attracted intensive attention. However, most of the existing stretchable electronic devices can generally be stretched only in one specific direction and show limited specific capacitance and energy density. Here, we report a stretchable isotropic buckled carbon nanotube (CNT) film, which is used as electrodes for supercapacitors with low sheet resistance, high omnidirectional stretchability, and electro-mechanical stability under repeated stretching. After acid treatment of the CNT film followed by electrochemical deposition of polyaniline (PANI), the resulting isotropic buckled acid treated CNT@PANI electrode exhibits high specific capacitance of 1147.12 mF cm(-2) at 10 mV s(-1). The supercapacitor possesses high energy density from 31.56 to 50.98 μWh cm(-2) and corresponding power density changing from 2.294 to 28.404 mW cm(-2) at the scan rate from 10 to 200 mV s(-1). Also, the supercapacitor can sustain an omnidirectional strain of 200%, which is twice the maximum strain of biaxially stretchable supercapacitors based on CNT assemblies reported in the literature. Moreover, the capacitive performance is even enhanced to 1160.43-1230.61 mF cm(-2) during uniaxial, biaxial, and omnidirectional elongations.

Quantitative Measurement of Cardiac Markers in Undiluted Serum

Two mycocardial infarction biomarkers, myoglobin (MG) and cardiac troponin I (cTnI), were quantified at biological levels and in undiluted serum without sample pretreatment using surface plasmon resonance (SPR) sensors. To achieve detection of biomarkers in undiluted serum (72 mg/mL total protein concentration), minimization of the nonspecific signal from the serum protein was achieved by immobilizing the antibody for the biomarkers on an N-hydroxysuccinimide activated 16-mercaptohexadecanoic acid self-assembled monolayer. This monolayer reduces the nonspecific signal from serum proteins in such a manner that short exposure of the sensor to serum prior to analysis prevents any further nonspecific adsorption during analysis. Thus, sensing of MG and cTnI was achieved on the basis of the difference between signals from the active sensor and a reference sensor that captured background interference. This resulted in direct measurement of these biomarkers in undiluted serum. Detection limits for both markers were below 1 ng/mL, which is below the threshold needed to detect myocardial infarction. Detecting biomarkers in the low ng/mL range without signal amplification in such a complex matrix as serum corresponds to a selectivity of 108. The root-mean-square-error (RMSE) of calibration was below 2 ng/mL.

Quantification of cytokines involved in wound healing using surface plasmon resonance

Sensing of three cytokines related to chronic wound healing, interleukin-1 (IL-1), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-alpha), with detection limits at or below 1 ng/mL in buffered saline solution and spiked cell culture medium (CCM) has been achieved. Fiber-optic surface plasmon resonance (SPR) sensors are coated with an antibody binding layer and antibodies specific to the cytokine of interest are covalently attached to this layer. To achieve such detection limits in a complex medium such as CCM, total protein content of 4 mg/mL, the use of a novel N-hydroxysuccinimide ester of 16-mercaptohexadecanoic acid (NHS-MHA) is necessary. A comparison of the detection limits for IL-6 using currently widely used CM-dextran and NHS-MHA shows an improvement by a factor of 3 using NHS-MHA. The detection limits for the monitoring of cytokines in spiked saline solutions and CCM were similar for TNF-alpha and slightly higher for IL-1 and IL-6. The detection of each cytokine in the presence of interfering agents resulted in concentration prediction well within the error of calibration. The SPR sensors are stable in CCM after 20 min of pretreatment in CCM, minimizing the reliance on a reference sensor to quantify the cytokines in complex media. This technique enables a major advancement in the field of real-time monitoring of biologically relevant molecules in complex biological fluids.

Reduction of nonspecific protein binding on surface plasmon resonance biosensors

Reduction of the nonspecific serum protein adsorption on a gold surface to levels low enough to allow the detection of biomarkers in complex media has been achieved using the N-hydroxysuccinimide (NHS) ester of 16-mercaptohexadecanoic acid. Carboxymethylated dextran (CM dextran), which is widely used, nonspecifically adsorbs enough proteins to mask the signal from target biomarkers in complex solutions such as serum or blood. The use of short-chain thiols greatly reduces the amount of nonspecific protein adsorption. Mixed layers of 11-mercaptoundecanoic acid or the NHS ester of 11-mercaptoundecanoic acid mixed layers with either 11-mercaptoundecanol or undecanethiol, and 16-mercaptohexadecanoic acid or the NHS ester of 16-mercaptohexadecanoic acid with hexadecanethiol, were also investigated for nonspecific protein binding properties as well as for biomarker signal response. The NHS ester of 16-mercaptohexadecanoic acid exhibits the largest signal for the biomarker myoglobin (including CM dextran) while offering a significantly diminished amount of nonspecific binding. The sensor has also been shown to detect interleukin-6 in cell culture media containing protein concentrations of at least 4 mg/mL.

Excitation-emission matrix fluorescence spectroscopy in conjunction with multiway analysis for PAH detection in complex matrices

A field portable, single exposure excitation-emission matrix (EEM) fluorometer has been constructed and used in conjunction with parallel factor analysis (PARAFAC) to determine the sub part per billion (ppb) concentrations of several aqueous polycyclic aromatic hydrocarbons (PAHs), such as benzo(k)fluoranthene and benzo(a)pyrene, in various matrices including aqueous motor oil extract and asphalt leachate. Multiway methods like PARAFAC are essential to resolve the analyte signature from the ubiquitous background in environmental samples. With multiway data and PARAFAC analysis it is shown that reliable concentration determinations can be achieved with minimal standards in spite of the large convoluting fluorescence background signal. Thus, rapid fieldable EEM analyses may prove to be a good screening method for tracking pollutants and prioritizing sampling and analysis by more complete but time consuming and labor intensive EPA methods.

Three- and four-way parallel factor (PARAFAC) analysis of photochemically induced excitation–emission kinetic fluorescence spectra

Independently emerging fluorescence profiles of unknown, photochemically induced degradation products of several naturally non-fluorescent pesticides were monitored using single exposure excitation-emission fluorescence spectroscopy. Three-way parallel factor analysis (PARAFAC) was employed to uniquely resolve the pure fluorescent spectra of the overlapping photolysis products. The quantitative utility of EEM photolysis-based determinations was demonstrated by employing four-way PARAFAC models built from EEM time cubes of multiple fenvalerate samples. The 4-way PARAFAC models were then used to predict original pesticide concentrations resulting in conservative limit of detection and root mean square errors of calibration (RMSEC) of 3 microM each.

Mitigation of Rayleigh and Raman spectral interferences in multiway calibration of excitation-emission matrix fluorescence spectra

A weighted parallel factor analysis (W-PARAFAC) model is applied to excitation-emission matrix (EEM) fluorescence spectra of carbamate pesticides to aid with calibration in the presence of Raman scattering. Traditional PARAFAC inefficiently models the Raman scattering, resulting in prediction and calibration errors when a significant background is present. Four different weighting strategies were investigated and compared with subtraction of the appropriate sample background. Using a binary weighting strategy produced superior results, compared with a continuous distribution of weights. Further choice of weighting strategies, which are optimized to include either maximum analyte signal or to exclude a maximum amount of background scattering, is dependent on the degree of overlap and relative signal intensity.

A novel multivariate curve resolution-alternating least squares (MCR-ALS) methodology for application in hyperspectral Raman imaging analysis

Multivariate curve resolution-alternating least squares (MCR-ALS) applied to hyperspectral Raman imaging is extensively used to spatially and spectrally resolve the individual, pure chemical species within complex, heterogeneous samples. A critical aspect of performing MCR-ALS with hyperspectral Raman imaging is the selection of the number of chemical components within the experimental data. Several methods have previously been proposed to determine the number of chemical components, but it remains a challenging task that if done incorrectly, can lead to the loss of chemical information. In this work, we show that the choice of 'optimal' number of factors in the MCR-ALS model may vary depending on the relative contribution of the targeted species to the overall spectral intensity. In a data set consisting of 27 hyperspectral Raman images of TiO2 polymorphs, it was observed that the more dominant species were best resolved with a parsimonious model. However, species with intensities near the noise level often needed more factors to be resolved than was predicted by standard methods. Based on the observations in this data set, we propose a new method that employs approximate reference spectra for determining optimal model complexity for identifying minor constituents with MCR-ALS.

Photocatalytic Degradation-Excitation−Emission Matrix Fluorescence for Increasing the Selectivity of Polycyclic Aromatic Hydrocarbon Analyses

The application of photocatalysis enhancement to calibration of fluorescence excitation-emission matrixes (EEMs) with parallel factor (PARAFAC) analysis is described. In this study, three- and four-way PARAFAC analysis was employed to extract the fluorescent species' spectra from overlapping EEMs. Time-dependent photocatalysis degradation of the polycyclic aromatic hydrocarbons (PAHs) was employed to create an additional dimension for analysis. The consequent four-dimension degradation-EEM data cubes have greater selectivity for each PAH than do three-dimension EEM data cubes alone. On a scale of 0 to 1, with 0 being completely collinear spectra and 1 being orthogonal spectra, including the time-dependent measurements increased the selectivity an average of 21%, from 0.73 to 0.87.