The use of microscale thin polymer films is widespread in biomedical science and engineering, with applications in areas such as tissue engineering, drug delivery, microfluidic devices, bio-adhesion mediators, and bio-actuators. Much attention is devoted to the use of functional polymers that display stimuliresponsive behavior with the intention of providing "smart" coatings. One potential example is the use of thin thermoresponsive polymer films as drug eluting coatings on medical devices, where not only does the polymer function as a drug reservoir but it also acts as a biocompatibility modulator to improve device performance.Often these thin polymer coatings have to be applied to complex geometries, which can cause problems for in-situ analysis. Another important consideration is the fact that these films have large surface area to mass ratios and thus water uptake can be significant. This is serious because coating stability, device efficacy, and long-term storage are influenced by the physiochemical properties of the polymer which are modulated by water content. Thus, there is a need for a rapid, non-contact, non-destructive, analytical method capable of analyzing thermoresponsive polymers in solution, and in-situ of the solid-state on medical devices. Fluorescence spectroscopy based methods can deal with both sample types and provide additional benefits in terms of high sensitivity and low probe concentrations, which provide for minimal sample disruption. This article gives a brief overview of the application of various fluorescence methods for the physicochemical characterization of thermoresponsive polymers such as poly (N-isopropylacrylamide), PNIPAm.

Crude oil is defined as a mixture of hydrocarbons that existed in the liquid phase in natural underground reservoirs and remains liquid at atmospheric pressure after passing through surface separating facilities (joint American Petroleum Institute, American Association of Petroleum Geologists, and Society of Petroleum Engineers definition).1 Crude petroleum oils are complex mixtures of different compounds (mainly organic), which are obtained from an extensive range of different geological sources.2,3 Their physical appearance can vary from solid black tars to almost transparent liquids. In their natural state within an oilfield reservoir or entrapped within Hydrocarbon bearing Fluid Inclusions (HCFI), crude oils will also contain varying amounts of gasses (carbon dioxide, methane, etc.).4 This presents the analyst with considerable challenges when developing methods for the characterisation and analysis of crude oils.5 The non-contact, non-destructive, quantitative analysis of crude petroleum oils is a highly desirable objective for both research (e.g. study of microscopic HCFI) and industry (e.g. real-time assessment of oil production). Satisfying the needs of both macroscopic and microscopic applications is not straightforward, however, optical methods offer a convenient route to achieving these goals. Fluorescence spectroscopy is the best available optical technique, because it offers high sensitivity, good diagnostic potential, relatively simple instrumentation, and is perfectly suited to both microscopy and portable instrumentation

Structural analysis of proteins using the emission of intrinsic fluorophores is complicated by spectral overlap. Anisotropy resolved multidimensional emission spectroscopy (ARMES) overcame the overlap problem by the use of anisotropy, with chemometric analysis, to better resolve emission from different fluorophores. Total synchronous fluorescence scan (TSFS) provided information about all the fluorophores that contributed to emission while anisotropy provided information about the environment of each fluorophore. Here the utility of ARMES was demonstrated via study of the chemical and thermal denaturation of human serum albumin (HSA).Multivariate curve resolution (MCR) analysis of the constituent polarized emission ARMES data resolved contributions from four emitters: fluorescence from tryptophan (Trp), solvent exposed tyrosine (Tyr), Tyr in a hydrophobic environment, and room temperature phosphorescence (RTP) from Trp. The MCR scores, anisotropy, and literature validated these assignments and showed all the expected transitions during HSA unfolding. This new methodology for comprehensive intrinsic fluorescence analysis of proteins is applicable to any protein containing multiple fluorophores. (C) 2015 Elsevier B.V. All rights reserved.

The automated identification and quantification of illicit materials using Raman spectroscopy is of significant importance for law enforcement agencies. This paper explores the use of Machine Learning (ML) methods in comparison with standard statistical regression techniques for developing automated identification methods. In this work, the ML task is broken into two sub-tasks, data reduction and prediction. In well-conditioned data, the number of samples should be much larger than the number of attributes per sample, to limit the degrees of freedom in predictive models. In this spectroscopy data, the opposite is normally true. Predictive models based on such data have a high number of degrees of freedom, which increases the risk of models over-fitting to the sample data and having poor predictive power. In the work described here, an approach to data reduction based on Genetic Algorithms is described. For the prediction sub-task, the objective is to estimate the concentration of a component in a mixture, based on its Raman spectrum and the known concentrations of previously seen mixtures. Here, Neural Networks and k-Nearest Neighbours are used for prediction. Preliminary results are presented for the problem of estimating the concentration of cocaine in solid mixtures, and compared with previously published results in which statistical analysis of the same dataset was performed. Finally, this paper demonstrates how more accurate results may be achieved by using an ensemble of prediction techniques.

Accurate, non-contact pH sensing is of particular importance in the biological and clinical sciences. Fluorescence lifetime based pH sensing is potentially more useful than intensity based methods because of the reduced sensitivity to excitation source intensity variations, scattering effects, and photobleaching. In this work, we investigate the variation of fluorescence lifetime with pH for resorufin. The intensity averaged lifetime (τ) of resorufin sodium salt in 0.1M phosphate buffer shows an increase of > 3 ns over the 2 -10 pH range, with 90% of the signal change occurring between pH 4 and 8. The fluorescence is not quenched by chloride or oxygen and was unaffected by the ionic strength of the buffer. Resorufin is relatively insoluble in non-alkaline phosphate buffered solutions, but was estimated to increase by ~2 ns between pH 6 and 8. Resorufin and its sodium salt were both incorporated into sol-gels by either acid or base hydrolysis of tetra-methoxysilane (TMOS). Various surfactants were also added to the sol-gels in an attempt to optimise the fluorescence properties and pH sensitivity of the dyes, and to prevent cracking. The sols were then cast from petri-dishes or dip-coated onto acrylic and glass slides. The dyes retained their pH sensitivity, with showing an increase of approximately 2 ns over the pH range 6 - 8. However, leaching of the dye is observed at higher pH and attempt to minimise dye leaching and sol-gel cracking, poly(vinyl alcohol) (PVA) was cross-linked to the silica gel to form a more flexible matrix.