Now showing 1 - 10 of 14
  • Publication
    Chemometric methods applied in the image plane to correct striping noise in hyperspectral chemical images of biomaterials
    Array detectors improve data collection speed in hyperspectral chemical imaging, yet are prone to striping noise patterns in the image plane, which is difficult to remove. This type of noise affects spectral features and disturbs visual impression of the scene. We found that this type of noise depends on the material composition and setting parameters, ie, pixel size, and it also varies in accordance with the signal intensity of the observed wavelength. To address this, we proposed a new correction method on the basis of the application of chemometric techniques in the image plane of each wavelength. To verify the effectiveness of this method, infrared transmission images of the 2″ × 2″ positive, 1951 USAF Hi‐Resolution Target and biomaterial samples were obtained with a 16‐element (8 × 2) pixel array detector. Point detector images of some samples were also acquired and used as reference images. The proposed correction method produced substantial improvements in the visual impression of intensity images. Principal components analysis was performed to inspect spectral changes after preprocessing, and the results suggested that the major spectral features were not altered while the stripes on intensity images were removed. Spectral profiles and principal components analysis loadings inspection confirmed the smoothing ability of this correction method. As traditional preprocessing techniques, standard normal variate and derivative transformation were not able to remove line artifacts, especially on the biomaterial images. Overall, the proposed method was effective for removing striping noise patterns from infrared images with a minimal alteration of the valuable hyperspectral image information.
      109Scopus© Citations 3
  • Publication
    Photoinduced Enhanced Raman from Lithium Niobate on Insulator Template
    © 2018 American Chemical Society. Photoinduced enhanced Raman spectroscopy from a lithium niobate on insulator (LNOI)-silver nanoparticle template is demonstrated both by irradiating the template with 254 nm ultraviolet (UV) light before adding an analyte and before placing the substrate in the Raman system (substrate irradiation) and by irradiating the sample in the Raman system after adding the molecule (sample irradiation). The photoinduced enhancement enables up to an ∼sevenfold increase of the surface-enhanced Raman scattering signal strength of an analyte following substrate irradiation, whereas an ∼threefold enhancement above the surface-enhanced signal is obtained for sample irradiation. The photoinduced enhancement relaxes over the course of ∼10 h for a substrate irradiation duration of 150 min before returning to initial signal levels. The increase in Raman scattering intensity following UV irradiation is attributed to photoinduced charge transfer from the LNOI template to the analyte. New Raman bands are observed following UV irradiation, the appearance of which is suggestive of a photocatalytic reaction and highlight the potential of LNOI as a photoactive surface-enhanced Raman spectroscopy substrate.
      353Scopus© Citations 13
  • Publication
    A review of recent trends in polymer characterization using non-destructive vibrational spectroscopic modalities and chemical imaging
    (Elsevier, 2015-10-01) ;
    This review focuses on the recent developments in vibrational spectroscopy and chemical imaging (i.e. Raman, Near Infrared, Mid Infrared) to characterize polymers in diverse forms, their behaviour and transient phenomenon. First, important polymeric properties and traditional methods of their characterization are outlined. Then relative advantages & disadvantages have been presented of different characterization methods are presented. This is followed by a detailed review of applications of chemical imaging and spectroscopic techniques in polymer characterization, including the limitations encountered. The article ends with a discussion on the future of chemical imaging with regards to polymer characterization.
      1181Scopus© Citations 43
  • Publication
    FTIR Spectroscopy for Molecular Level Description of Water Vapor Sorption in Two Hydrophobic Polymers
    (IEEE, 2019-09-26) ;
    This work aims to investigate the sorption of water vapor in two hydrophobic polymers, i.e., polytetrafluoroethylene (PTFE) and polyurethane (PU) with water contact of 119 and 104, respectively, by using Fourier transform infrared (FTIR) spectroscopy combined with gravimetric analysis. Sample spectra were measured in a controlled humidity cell. Results demonstrated the absence of water molecules in PTFE after exposure to 100% RH for 2 hours. In contrast, the spectroscopic data provided strong evidence that PU film continued to sorb water as exposure time increased. The interaction between water molecules and PU polymer chain was characterized by the dynamics of hydrogen bonding. The hydrogen bonding between N-H and C=O groups was reduced by the sorbed water, as evidenced by the shift of NH to a higher frequency. Second derivative of difference spectra suggested the presence of multiple water species involved in different types of hydrogen bonding interaction at water/PU interface. Results also revealed that the sorbed water in PU film cannot be eliminated via evaporation at room temperature.
      289Scopus© Citations 2
  • Publication
    FTIR and Raman imaging for microplastics analysis: State of the art, challenges and prospects
    Despite a substantial body of research to date for the detection of microplastics (MPs) in almost every environmental compartment there remains a lack of standardisation, and methodologies used by different research groups vary widely. Chemical imaging, which provides simultaneous measurement of physical (i.e. spatial) and chemical (i.e. spectroscopic) information, is recognized as a promising tool for MPs analysis. Herein, we first review the state-of-the-art chemical imaging methods, i.e., Fourier-transform infrared spectroscopy (FTIR) and Raman imaging, for the identification and quantification of MPs from different environmental samples. From a technical point of view (e.g., accuracy, speed optimizations and background effects), the limitations and analytical challenges are highlighted from extensive literature data. Finally, we suggest possible strategies and solutions to improve current practices towards an automated routine for MPs analysis.
      431Scopus© Citations 184
  • Publication
    Vibrational Spectroscopy for Analysis of Water for Human Use and in Aquatic Ecosystems
    Maintaining a clean water supply is one of the key challenges facing humanity today. Pollution, over-use and climate change are just some of the factors putting increased pressure on our limited water resources. Contamination of the water supply presents a high risk to public health, security and the environment; however, no adequate real-time methods exist to detect the wide range of potential contaminants. There is a need for rapid, low cost, multi target systems for water quality monitoring. Information rich techniques such as vibrational spectroscopy have been proposed for this purpose. This review presents developments in the applications of vibrational spectroscopy to water quality monitoring over the past 20 years, identifies emerging technologies and discusses future challenges.
      4426Scopus© Citations 23
  • Publication
    Investigation of plasticizer aggregation problem in casein based biopolymer using chemical imaging
    (Elsevier, 2019-02-01) ;
    This work aims to investigate the emergence of aggregates caused by redundant plasticizers in the protein matrix of casein based biopolymers using chemical imaging techniques. Near infrared (NIR) images (950–1671 nm) were first acquired and the spatial variations on macroscale with a pixel size of 0.4 mm × 0.5 mm were visualized. The introduction of plasticizers resulted in a strong hydrogen bonding matrix in the protein polymeric film as evidenced by analysis of Fourier transform near infrared (FT-NIR) spectral profiles in the range of 7500–4000 cm−1. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) images (4000–650 cm−1) coupled with principal components analysis (PCA) and multivariate curve resolution alternating least squares (MCR-ALS) analysis suggested the existence of sorbitol re-crystallization after 5 months storage in the ambient condition. Raman images with a higher pixel size of 1.2 µm × 1.2 µm indicated an uneven film surface caused by sorbitol migration and re-crystallization. A partial least squares (PLS) regression model was developed to predict plasticizer concentration based on the mean spectra of FT-NIR hypercubes, producing coefficient of determination in calibration (R2Cal) of 0.93, cross-validation (R2CV) of 0.92 and prediction (R2P) of 0.89. Visualization of aggregates in the image field was obtained by applying the developed PLS model in a pixel-wise manner using single-element and array detectors. The combined information from NIR and FT-NIR evidenced the occurrence of high plasticizer-concentrated regions in the film sample, while the combined information from FT-NIR and ATR-FTIR further confirms the phenomenon of sorbitol re-crystallization.
      113Scopus© Citations 3
  • Publication
    Feasibility of attenuated total reflection-fourier transform infrared (ATR-FTIR) chemical imaging and partial least squares regression (PLSR) to predict protein adhesion on polymeric surfaces
    Predicting the degree to which proteins adhere to a polymeric surface is an ongoing challenge in the scientific community to prevent non-specific protein adhesion and drive favourable protein-surface interactions. This work explores the potential of multivariate PLSR modelling in conjunction with Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) chemical imaging to investigate whether experimentally characterised surface chemistry can be used to predict surface protein adhesion. ATR-FTIR spectra were collected on dry and wetted polymeric surfaces, followed by evaluation of adhered fibrinogen on surfaces using the micro bicinchoninic (BCA) protein assay as a reference method. Partial Least Squares Regression (PLSR) models were built using IR spectra as the predictor variable. Overall the models built with 'wetted polymer' IR spectra performed better as compared to the models built using 'dry polymer' IR spectra (average coefficient of determination, R 2P 0.998, 0.996 respectively), with the lowest error in prediction (4 ± 0.6 μg) for ultra-high molecular weight polyethylene (UHMPE) as a test surface. This indicates the potential of this method to predict the degree to which protein adhesion occurs on polymeric surfaces using experimentally determined surface chemistry.
      105Scopus© Citations 5
  • Publication
    An efficient methodology for quantification of synergy and antagonism in single electron transfer antioxidant assays
    The development of new antioxidant compounds for incorporation in foods is a rapidly growing research area. The resulting interactions between complex antioxidant mixtures are a key issue; however, research in this area is still in its infancy. Experimental antioxidant models based on conventional dose¿responses, that can predict joint effects of chemical mixtures, are urgently needed. This paper illustrates a methodological procedure for single electron transfer (SET) antioxidant assays to determine the synergistic and antagonistic effects of combining binary mixtures of antioxidants. Despite the abundance of theories and procedures to describe the synergistic/antagonistic effects in SET assays, they appear to be inadequate. Some features hindering advances in this field include the lack of: (1) experimental design, as a result of the extended use of unambiguous and simplistic procedures to quantify the effects of joint responses, based on single-dose values; (2) detailed mathematical hypotheses to quantify dose¿response values, which in addition causes the associated difficulties for assessing the statistical consistence of the results; and (3) functional approaches that consider the possibility of interactive effects. This paper proposes solutions for each of these limitations. Established ideas from existing fields are used to replace the current simplistic procedures, in order to quantify the effects of joint responses. One of the common hypothesis (known as concentration addition) for describing the combined effects is established for SET assays. A dose dependent mathematical model representative of this hypothesis, based on probability functions with meaningful parameters, is applied. The interactive effects between antioxidants are introduced into the model with simple auxiliary functions that describe the variations induced by each antioxidant in the parameters that define the effects of the other. Finally, a comprehensive index to summarize the complex parametric responses in one single value is proposed. Although the approach was experimentally demonstrated just in two classical SET assays (DPPH and ABTS), the results could be directly expanded in future to other types of classical SET assays. The methodology proposed is more complex than some relatively common approaches; nevertheless we believe that it is free of the controversial aspects listed above. Statistically consistent responses of null, synergy and antagonism effects were found when characterizing the interactions between several pairs of individual and complex mixtures of chemical antioxidant agents.
      620Scopus© Citations 46
  • Publication
    Can attenuated total internal reflection-fourier transform infrared be used to understand the interaction between polymers and water? A hyperspectral imaging study
    This study investigates the potential use of attenuated total internal reflection-Fourier transform infrared (ATR-FT-IR) imaging, a hyperspectral imaging modality, to investigate molecular level trends in the interaction of water with polymeric surfaces of varying hydrophobicity. The hydrophobicity of two categories of polymeric biomaterials is characterised using contact angle (CA) measurements and their relationship with the band area of the OH stretching v S vibration of water over time is presented. This is supported with correlations between CA data and single wavenum-ber intensity values (univariate analysis). Multivariate analysis of the spectra captured at the OH stretch for all polymers is carried out using principal component analysis to study the spatial variation in the interaction between the polymeric surfaces and water. Finally, a comparison between the univariate and multivariate strategies is presented to understand the interaction between polymeric biomaterials and water.
      130Scopus© Citations 6