scholarly journals UV-Vis/FT-NIR in situ monitoring of visible-light induced polymerization of PEGDA hydrogels initiated by eosin/triethanolamine/O2

2016 ◽  
Vol 7 (3) ◽  
pp. 592-602 ◽  
Author(s):  
Kaja Kaastrup ◽  
Alan Aguirre-Soto ◽  
Chen Wang ◽  
Christopher N. Bowman ◽  
Jeffrey W. Stansbury ◽  
...  

Coupled UV-Vis/FT-NIR spectroscopy was applied to the study of the eosin-activated photopolymerization of hydrogels in the presence of oxygen; a relationship between signal loss and network formation was established.

2012 ◽  
Vol 31 (1) ◽  
pp. 155-163 ◽  
Author(s):  
Lalehvash Moghaddam ◽  
Llewellyn Rintoul ◽  
Peter J. Halley ◽  
Graeme A. George ◽  
Peter M. Fredericks

2017 ◽  
Vol 6 (10) ◽  
pp. 1109-1113 ◽  
Author(s):  
Jia Niu ◽  
Zachariah A. Page ◽  
Neil D. Dolinski ◽  
Athina Anastasaki ◽  
Andy T. Hsueh ◽  
...  

2018 ◽  
Vol 11 (05) ◽  
pp. 1850027 ◽  
Author(s):  
Hongxia Huang ◽  
Haibin Qu

As unsafe components in herbal medicine (HM), saccharides can affect not only the drug appearance and stabilization, but also the drug efficacy and safety. The present study focuses on the in-line monitoring of batch alcohol precipitation processes for saccharide removal using near-infrared (NIR) spectroscopy. NIR spectra in the 4000–10,000-cm[Formula: see text] wavelength range are acquired in situ using a transflectance probe. These directly acquired spectra allow characterization of the dynamic variation tendency of saccharides during alcohol precipitation. Calibration models based on partial least squares (PLS) regression have been developed for the three saccharide impurities, namely glucose, fructose, and sucrose. Model errors are estimated as the root-mean-square errors of cross-validation (RMSECVs) of internal validation and root-mean-square errors of prediction (RMSEPs) of external validation. The RMSECV values of glucose, fructose, and sucrose were 1.150, 1.535, and 3.067[Formula: see text]mg[Formula: see text]mL[Formula: see text], and the RMSEP values were 0.711, 1.547, and 3.740[Formula: see text][Formula: see text], respectively. The correlation coefficients [Formula: see text] between the NIR predictive and the reference measurement values were all above 0.94. Furthermore, NIR predictions based on the constructed models improved our understanding of sugar removal and helped develop a control strategy for alcohol precipitation. The results demonstrate that, as an alternative process analytical technology (PAT) tool for monitoring batch alcohol precipitation processes, NIR spectroscopy is advantageous for both efficient determination of quality characteristics (fast, in situ, and requiring no toxic reagents) and process stability, and evaluating the repeatability.


Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1099 ◽  
Author(s):  
Minoo Karbasi ◽  
Fathallah Karimzadeh ◽  
Keyvan Raeissi ◽  
Sami Rtimi ◽  
John Kiwi ◽  
...  

This study addresses the visible light-induced bacterial inactivation kinetics over a Bi2WO6 synthesized catalyst. The systematic investigation was undertaken with Bi2WO6 prepared by the complexation of Bi with acetic acid (carboxylate) leading to a flower-like morphology. The characterization of the as-prepared Bi2WO6 was carried out by X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), specific surface area (SSA), and photoluminescence (PL). Under low intensity solar light (<48 mW/cm2), complete bacterial inactivation was achieved within two hours in the presence of the flower-like Bi2WO6, while under visible light, the synthesized catalyst performed better than commercial TiO2. The in situ interfacial charge transfer and local pH changes between Bi2WO6 and bacteria were monitored during the bacterial inactivation. Furthermore, the reactive oxygen species (ROS) were identified during Escherichia coli inactivation mediated by appropriate scavengers. The ROS tests alongside the morphological characteristics allowed the proposition of the mechanism for bacterial inactivation. Finally, recycling of the catalyst confirmed the stable nature of the catalyst presented in this study.


2007 ◽  
Vol 29 (5) ◽  
pp. 417-429 ◽  
Author(s):  
S. Benali ◽  
D. Bertrand ◽  
J. Dupuy ◽  
G. Lachenal ◽  
A. Maazouz

2014 ◽  
Vol 118 (47) ◽  
pp. 27583-27593 ◽  
Author(s):  
Vyacheslav N. Kuznetsov ◽  
Alexei V. Emeline ◽  
Nadezhda I. Glazkova ◽  
Ruslan V. Mikhaylov ◽  
Nick Serpone

2021 ◽  
Vol 2 (1) ◽  
pp. 405-416
Author(s):  
Ayslan S. P. da Costa ◽  
J Manuela Goncalves ◽  
Hosana O. Á. Neta ◽  
Douglas Alves ◽  
Elton Franceschi ◽  
...  

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