We present a simple model that uses a novel photon scattering approach to predict the depth profile response obtained when confocal Raman spectroscopy is applied both to silicon and to a number of related polymeric materials of varying optical clarity. This paper first provides an overview of the models proposed to date to demonstrate the evolution in understanding of the confocal Raman response of semi-transparent materials, based upon geometrical optics. A new model is then described that is based upon the twin notions of a permanent extended Raman illuminated volume and the degree of extinction of the incident and Raman scattered photons from the whole of the illuminated volume as it is gradually moved further into, or defocused above, the sample. The model's predictions are compared with empirical data from previous studies of a range of semi-crystalline polymers with different scattering properties and, by means of contrast, with that of a silicon sample. We show that, despite its inherent simplicity, the physics this model utilizes is able successfully to predict the form of the depth profile for each material, something that has not been achieved by any model previously proposed, and that the parameters used in the model scale with independent physical measurements. Finally the model is used to account for the fact that useful Raman spectra can be obtained when the laser is focused as much as 40 µm above the sample surface.

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This study considers confocal Raman spectroscopy as a means of identifying a range of synthetic polymeric adhesives used in textile conservation. Many of the synthetic adhesives applied to support fragile textiles in the 1970s are now showing signs of ageing and the textiles are therefore being presented for retreatment. With no record of the adhesive used, conservators are unsure of the appropriate protocol to remove the original adhesive prior to retreatment. We have shown that Raman spectroscopy lends itself to the analysis of these thin polymer layers as it is inherently non-destructive and can be applied in situ. We also found that, for particularly thin polymer layers (∼20 µm), the underlying textile often scatters far more efficiently than the overlying polymer and therefore the polymer cannot always be identified unambiguously in situ. Although thick, transparent polymer samples are known to produce maximum Raman peak intensity when the laser is focused a few microns below the sample surface, focusing on or just above (0-5 µm) the polymer layer is shown to maximize the ratio of polymer peak intensity to textile substrate peak intensity, thus facilitating identification of the polymer. Defocusing further to a point 20 µm above the upper surface is shown to reintroduce interference from the substrate spectrum to a level comparable to that acquired when focused within the thin polymer layer, closer to the textile substrate.

A series of semicrystalline polymers has been prepared through morphological control. Each of these has an identical refractive index but a different, well-defined, scattering behavior. From existing geometrical optical theories of confocal Raman spectroscopy, these materials should behave identically. Initially, the extent of scattering in each system was assessed quantitatively, from the near-infrared through the visible wavelength range, by UV/visible spectroscopy. The effect of optical scattering on the variation of intensity of the Raman scattered radiation with subsurface position was then examined in all four materials; the effect of surface roughness was also considered in the highest clarity system. Where surface effects are removed through careful sample preparation and the materials are interrogated using identical optical systems to mitigate against the impact of refractive index mismatch and other optical effects, the Raman response is strongly affected by the scattering characteristics of each material. A simple empirical relationship has been determined that adequately described all our specimens.

Until 2006 the performance of confocal Raman spectroscopy depth profiling was typically described and modeled through the application of geometrical optics, including refraction at the surface, to explain the degree of resolution and the precise form of the depth profile obtained from transparent and semicrystalline materials. Consequently a range of techniques, physical and analytical, was suggested to avoid the errors thus encountered in order to improve the practice of Raman spectroscopy, if not the understanding of the underlying mechanisms. These approaches were completely unsuccessful in accounting for the precise form of the depth profile, the fact that spectra obtained from laminated samples always contain characteristic peaks from all materials present both well above and below the focal point and that spectra can be obtained when focused some 40 mum above the sample surface. This paper provides further evidence that the physical processes underlying Raman spectroscopy are better modeled and explained through the concept of an extended illuminated volume contributing to the final Raman spectrum and modeled through a photon scattering approach rather than a point focus ray optics approach. The power of this numerical model lies in its ability to incorporate, simultaneously, the effects of degree of refraction at the surface (whether using a dry or oil objective lens), the degree of attenuation due to scatter by the bulk of the material, the Raman scattering efficiency of the material, and surface roughness effects. Through this we are now able to explain why even removing surface aberration and refraction effects through the use of oil immersion objective lenses cannot reliably ensure that the material sampled is only that at or close to the point of focus of the laser. Furthermore we show that the precise form of the depth profile is affected by the degree of flatness of the surface of the sample. Perhaps surprisingly, we show that the degree of flatness of the material surface is, in fact, more important than obtaining a precise refractive index match between the immersion oil and the material when seeking a high-quality depth profile or Raman spectrum from within a transparent or semicrystalline material, contrary to accepted norms that samples for interrogation by Raman spectroscopy require little preparation.

In this paper, we consider electrical treeing in a clarified propylene / ethylene copolymer; our interest in this stems, primarily, from its high optical clarity, which permits the acquisition of images of evolving trees (tree structure and light emission). In this paper we consider tree growth in this material and relate the discharge activity during growth, determined both through observations of optical emission and measurements of partial discharges in the external circuit, to the form of the trees that evolve. In particular, confocal Raman microprobe spectroscopy has been used to explore the local chemical composition, since this technique has the potential to provide spectroscopic data at high spatial resolutions (lateral -1 gm: vertical -2 pm) from within optically transparent media.

A computer model has been developed to predict the probability of recognition of particular shapes when viewed through a thermal imager employing either scanned or focal plane array detectors.This model is based on the results of a series of psychophysical trials during which human observers have considered over 120,000 images of shapes having a range of initial contrasts, and which have been degraded by various combinations of blurring and sampling. These computer generated images were presented to the observers in a random order and with a random degradation, using programmes to select images and display them on a computer monitor. After each presentation the observer decided which was the most likely shape to represent the image displayed on the screen. The responses collected have been used to calculate the human recognition probability of each image. A correlation has been found between the probability of recognition of any specified degraded shape and the relative contrast between the image of that shape, and the image of a similarly degraded circle of the same area. This model has been extended to include the effects of fixed pattern noise and applied to simplified images of cars and vans.

Far from being just cheap packaging materials, plastics may be the materials of tomorrow. Plastic can conduct electricity, and this opens up a host of high-tech possibilites in the home and in energy generation. These possibilities are discussed here along with how plastic can be recycled and perhaps even grown.