Kyeol Chang

Use of temperature dependent Raman spectra to improve accuracy for analysis of complex oil-based samples: lube base oils and adulterated olive oils.

A simple and effective strategy to improve accuracy for Raman spectroscopic analysis of complex mixture samples by probing a measurement temperature yielding enhanced spectral selectivity has been demonstrated. For the evaluation, the determination of Kinematic Viscosity at 40 °C (KV@40) of lube base oil (LBO) samples was initially attempted. Partial least squares (PLS) was used to determine the KV@40 using Raman spectra of the samples collected at 8 different temperatures from 20 to 90 °C with 10 °C increments. Interestingly, the distinct temperature-induced spectral variation among the samples occurred at 50 °C, thereby resulting in the improved accuracy for determination of KV@40. Two-dimensional (2D) correlation analysis was also performed to find an additional supportive rationale for the improved accuracy. The strategy was further evaluated for the identification of soybean oil-adulterated olive oils using linear discriminant analysis (LDA). Similarly, the discrimination accuracy was improved around 80-90 °C due to the enhanced spectral selectivity between olive and soybean oils. In overall, these two results successfully demonstrate analytical effectiveness of the strategy.

Feasibility for non-destructive discrimination of natural and beryllium-diffused sapphires using Raman spectroscopy

Raman spectroscopy based non-destructive discrimination between natural and beryllium-diffused (Be-diffused) sapphires has been attempted. The initial examination of Raman image acquired on a sapphire revealed that microscopic structural and compositional heterogeneity was apparent in the sample, so acquisition of spectra able to represent a whole body of sapphire rather than a localized area was necessary for a reliable discrimination. For this purpose, a wide area illumination (WAI) scheme (illumination area: 28.3mm(2)) providing a large sampling volume was employed to collect representative Raman spectra of sapphires. Upon the diffusion of Be into a sapphire, the band shift originated from varied lattice structure by substitution of Be at cation sites was observed and utilized as a valuable spectral signature for the discrimination. In the domain of principal component (PC) scores, the groups of natural and Be-diffused sapphires were identifiable with minor overlapping and the cross-validated discrimination error was 7.3% when k-Nearest Neighbor (k-NN) was used as a classifier.

Simple electrochemical synthesis of an Au–Ag–Cu trimetallic nanodendrite and its use as a SERS substrate

An Au–Ag–Cu trimetallic nanodendrite was constructed by simple electrochemical methods and was evaluated as a surface enhanced Raman scattering (SERS) substrate. The motivation was to harmonize the individual merits of each SERS-active metal, the higher SERS efficiency of Ag, good surface stability of Au, and structural stability of Cu, in a single structure. For the fabrication, a Cu flower-like nanostructure was initially constructed by reduction of Cu2+ (electrodeposition). Next, a galvanic replacement reaction (GRR) was performed on the Cu framework in a solution of Ag+ to build Ag nanodendrites with coincidental release of Cu atoms into the solution as Cu2+. As the Ag nanodendrite grew, released Cu2+ redeposited, so a Ag–Cu bimetallic nanodendrite started to form. Next, a second GRR was performed with the newly prepared Ag–Cu nanodendrite in Au3+ solution to partially replace Ag and Cu by Au to construct the Au–Ag–Cu trimetallic nanodendrite. Based on examination of Raman peaks of rhodamine 6G (R6G, a reporter molecule), the Ag–Cu nanodendrite resulted in approximately 2.6 fold higher peak intensity compared to a Ag nanodendrite. Subsequent Au incorporation into the Ag–Cu nanodendrite greatly improved the stability of SERS measurements as well as increased the peak intensity further by 7.6 fold, thereby enabling the observation of Raman peaks of a 10−10 M R6G sample.

Axially perpendicular offset Raman scheme for reproducible measurement of housed samples in a noncircular container under variation of container orientation.

An axially perpendicular offset (APO) scheme that is able to directly acquire reproducible Raman spectra of samples contained in an oval container under variation of container orientation has been demonstrated. This scheme utilized an axially perpendicular geometry between the laser illumination and the Raman photon detection, namely, irradiation through a sidewall of the container and gathering of the Raman photon just beneath the container. In the case of either backscattering or transmission measurements, Raman sampling volumes for an internal sample vary when the orientation of an oval container changes; therefore, the Raman intensities of acquired spectra are inconsistent. The generated Raman photons traverse the same bottom of the container in the APO scheme; the Raman sampling volumes can be relatively more consistent under the same situation. For evaluation, the backscattering, transmission, and APO schemes were simultaneously employed to measure alcohol gel samples contained in an oval polypropylene container at five different orientations and then the accuracies of the determination of the alcohol concentrations were compared. The APO scheme provided the most reproducible spectra, yielding the best accuracy when the axial offset distance was 10 mm. Monte Carlo simulations were performed to study the characteristics of photon propagation in the APO scheme and to explain the origin of the optimal offset distance that was observed. In addition, the utility of the APO scheme was further demonstrated by analyzing samples in a circular glass container.

Amphiphilic metabolites in gallbladder bile: Potential biomarkers for gallbladder diseases

ABSTRACT Gallbladder bile is one of the most abundant body fluids, and metabolic compositions of the bile are highly correlated with several gallbladder diseases (gallstones, gallbladder polyps, cholecystitis, and biliary tract cancer). The gallbladder diseases are generally diagnosed by several different imaging methods in the clinic; however, none of them can readily reveal detailed information about the diseases in molecular levels. Here, we have applied various nuclear magnetic resonance spectroscopy in order to identify and analyze composition of the human gallbladder bile, since the spectroscopic method provides not only structural information but also dynamic information of low- and high-weighted metabolites. In combination with both 1D Carr–Purcell–Meibom–Gill filtered 1H spectrum and 2D 1H–13C heteronuclear single quantum correlation spectrum, 15 metabolic compounds have been assigned in the bile specimen. Discrimination and classification analysis have been conducted by principal component analysis and support vector machine, respectively, so as to differentiate the gallbladder diseases, especially between gallstones and gallbladder polyps in here. From these investigations, we found two family of metabolites, namely bile acids (glycine and taurine conjugated cholic acids) and phosphatidylcholine, which play significant roles in discriminating gallstones, gallbladder polyps, and others.

Acquisition of a series of temperature-varied sample spectra to induce characteristic structural changes of components and selection of target-descriptive variables among them for multivariate analysis to improve accuracy

ABSTRACT As a means of improving the accuracy of Raman spectroscopic quantitative analysis, a strategy combining the generation of a series of temperature-varied spectra to make diverse and characteristic structural information of sample components widely available for calibration, and subsequent selection of more property-descriptive variables among these spectra, has been demonstrated. For the evaluation, Raman spectra of synthetic hydrocarbon mixtures, lube base oils (LBOs) and polyethylene (PE) pellets were acquired at regular intervals while the sample temperature gradually increased from cryogenic to near room temperature. To select target-descriptive variables from all of the snapshot (temperature-varied) spectra, a Markov blanket (MB) feature (variable) selection able to produce a minimal set of features without changing the original target distribution was adopted. The selection utilizes a conditional independence test to quickly obtain an optimal feature subset by simultaneously considering relevance to a target variable and redundancy between selected features without using any heuristic searching. When MB-selected variables were used for partial least squares (PLS) to determine the concentrations of components in the hydrocarbon mixtures, kinematic viscosity of 40°C (KV@40) of LBOs, and density of PE pellets, the accuracy was improved compared to the use of either all snapshot spectra without variable selection or an optimal single snapshot spectrum. The incorporation of component-specific and property-descriptive variables without redundant information for PLS was the origin of the improvement in accuracy. The proposed method could potentially be extended to the analysis of other complex samples including petroleum-driven samples, edible oils, and other polymers.

Interleaved incremental association Markov blanket as a potential feature selection method for improving accuracy in near-infrared spectroscopic analysis

The interleaved Incremental Association Markov Blanket (inter-IAMB) is described herein as a feature selection method for the NIR spectroscopic analysis of several samples (diesel, gasoline, and etchant solutions). Although the Markov blanket (MB) has been proven to be the minimal optimal set of features (variables) that does not change the original target distribution, variables selected by the existing IAMB algorithm could be redundant and/or misleading as the IAMB requires an unnecessarily large amount of learning data to identify the MB. Use of the inter-IAMB interleaving the grow phase with the shrink phase to maintain the size of the MB as small as possible by immediately eliminating invalid candidates could overcome this drawback. In this report, a likelihood-ratio (LR)-based conditional independence test, able to handle spectroscopic data normally comprising a large number of continuous variables in a small number of samples, was uniquely embedded in the inter-IAMB and its utility was evaluated. The variables selected by the inter-IAMB in complexly overlapped and feature-indistinct NIR spectra were used to determine the corresponding sample properties. For comparison, the properties were also determined using the IAMB-selected variables as well as the whole variables. The inter-IAMB was more effective in the selection of variables than the IAMB and thus able to improve the accuracy in the determination of the sample properties, even though a smaller number of variables was used. The proposed LR-embedded inter-IAMB could be a potential feature selection method for vibrational spectroscopic analysis, especially when the obtained spectral features are specificity-deficient and extensively overlapped.

Data on the concentration-dependent score variations and the results of 2D correlation analysis in the measurements of H2SO4, HNO3, and H3PO4 samples

Data presented here are related to the original paper “Concentration determination of inorganic acids that do not absorb near-infrared (NIR) radiation through recognizing perturbed NIR water bands by them and investigation of accuracy dependency on their acidities” published by same authors. Here, the concentration-dependent score variations and the results of 2D correlation analysis in the measurements of H2SO4, HNO3, and H3PO4 samples are included; while, the same analysis results obtained in the measurement of HCl samples are presented in the main manuscript. In addition, the correlation plots resulted in the measurements of HCl, H2SO4, HNO3, and H3PO4 samples are also separately shown.