The combinatorial optimization simulated annealing algorithm is applied to the analysis of Rutherford backscattering data. The analysis is fully automatic, i.e., it does not require time-consuming human intervention. The algorithm is tested on a complex iron-cobalt silicide spectrum, and all the relevant features are successfully determined. The total analysis time using a PC 486 processor running at 100 MHz is comparable to the data collection time, which opens the way for on-line automatic analysis.

Rutherford backscattering spectrometry (RBS) and related techniques have long been used to determine the elemental depth profiles in films a few nanometres to a few microns thick. However, although obtaining spectra is very easy, solving the inverse problem of extracting the depth profiles from the spectra is not possible analytically except for special cases. It is because these special cases include important classes of samples, and because skilled analysts are adept at extracting useful qualitative information from the data, that ion beam analysis is still an important technique. We have recently solved this inverse problem using the simulated annealing algorithm. We have implemented the solution in the 'IBA DataFurnace' code, which has been developed into a very versatile and general new software tool that analysts can now use to rapidly extract quantitative accurate depth profiles from real samples on an industrial scale. We review the features, applicability and validation of this new code together with other approaches to handling IBA (ion beam analysis) data, with particular attention being given to determining both the absolute accuracy of the depth profiles and statistically accurate error estimates. We include examples of analyses using RBS, non-Rutherford elastic scattering, elastic recoil detection and non-resonant nuclear reactions. High depth resolution and the use of multiple techniques simultaneously are both discussed. There is usually systematic ambiguity in IBA data and Butler's example of ambiguity (1990 Nucl. Instrum. Methods B 45 160-5) is reanalysed. Analyses are shown: of evaporated, sputtered, oxidized, ion implanted, ion beam mixed and annealed materials; of semiconductors, optical and magnetic multilayers, superconductors, tribological films and metals; and of oxides on Si, mixed metal silicides, boron nitride, GaN, SiC, mixed metal oxides, YBCO and polymers.

Nanocomposites consisting of a dielectric matrix, such as TiO2, with embedded noble metal nanoparticles (NPs) possess specific optical properties due to the surface plasmon resonance (SPR) effect, interesting for several applications. The aim of this work is to demonstrate that these properties are sensitive to the nanostructure of magnetron-sputtered TiO2/Au thin films, which can be tuned by annealing. We study the role of the shape and size distribution of the NPs, as well as the influence of the crystallinity and phase composition of the host matrix on the optical response of the films. All these characteristics can be modified by vacuum annealing treatments of the deposited films. A theoretical interpretation and modeling of the experimental results obtained is presented. The model involves a modified Maxwell-Garnett approach for the effective dielectric function of the composite (describing the SPR effect) and the transfer matrix formalism for multilayer optics. Input data are based on the experimental information obtained from the detailed structural characterization of the films. It is shown that the annealing treatments can be used for controlling the optical properties of the composite films, making them attractive for decorative coatings.