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Gowen, Aoife
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Gowen, Aoife
Official Name
Gowen, Aoife
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Now showing 1 - 3 of 3
- PublicationVibrational Spectroscopy for Analysis of Water for Human Use and in Aquatic Ecosystems(Taylor & Francis, 2012-11-12)
; ; ; 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.Scopus© Citations 26 4877 - PublicationFTIR Spectroscopy for Molecular Level Description of Water Vapor Sorption in Two Hydrophobic PolymersThis 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.
Scopus© Citations 3 337 - PublicationPredictive modelling of the water contact angle of surfaces using attenuated total reflection-Fourier transform infrared (ATR-FTIR) chemical imaging and partial least squares regression (PLSR)(Royal Society of Chemistry, 2018-06-19)
; ; ; The static water contact angle (CA) quantifies the degree of wetting that occurs when a surface encounters a liquid, e.g. water. This property is a result of factors such as surface chemistry and local roughness and is an important analytical parameter linked to the suitability of a surface for a given bioanalytical process. Monitoring the spatial variation in wettability over surfaces is increasingly critical to analysts and manufacturers for improved quality control. However, CA acquisition is often time-consuming because it involves measurements over multiple spatial locations, independent sampling and the need for a single instrument operator. Furthermore, surfaces exposed to local environments specific to an intended application may affect the surface chemistry thereby modifying the surface properties. In this study, Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) chemical imaging data acquired from wet and dry polymer surfaces were used to develop multivariate predictive models for CA prediction. Partial Least Squares Regression (PLSR) models were built using IR spectra from surfaces presenting differences in the experimentally measured CA in the range 16°-141°. The best performing PLSR models were locally developed and combined to make a global model utilising wet IR spectra which performed well (R2p = 0.98, RMSECV ∼ 5°) when tested on an independent experimental set. This model was subsequently applied to IR spectra acquired from a surface exhibiting spatial differences in surface chemistry and the CA with a reasonable confidence and precision (prediction error within 10°), demonstrating the potential of this method for prediction of the spatially varying CA as a non-destructive in-line process monitoring technique.314Scopus© Citations 7