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In ITER, a remote handling laser-induced breakdown spectroscopy (LIBS) system is considered to be able to observe regions where deposition of thick layers is expected to occur and assess the retention of fuel on wall structures. The H and D contents of surface layers on divertor and first-wall materials have been intensely studied by LIBS but mostly by depth profile analysis of D. As far as we know, quantitative analysis of H/D in BeW mixed layer by calibration free-LIBS (CF-LIBS) has not been performed. Thus, the aim of this work is the quantification of the relative concentrations of D and H in Be-based material samples by CF-LIBS. The samples used were Be/W(67:33) as mixed homogeneous coatings (2 μm) on Mo substrates. Laser ablation was performed using a 1064 nm laser with 5 ns pulses. In order to enhance the resolution to distinguish H, D and in future T from each other, two different pressures were used: high vacuum and 0.5 mbar of Ar. Suitable Be and W spectral lines (without interferences and self-absorption) have been selected for precise evaluation of the electron temperature, T e , of the plasma using the Boltzmann plots. The electron density, n e , was extracted from the Saha equation using the average electron temperatures obtained from the Stark broadening of the H α line. With these values, the D content of the samples has been calculated by CF LIBS as ∼4.7% ± 2.9%. These results are in a good agreement with thermal desorption spectroscopy measurements, which gives a 4–5 at% for the D content. In addition, the depth profile is similar to that recorded using secondary ion mass spectrometry.

Abstract.Computations are pervasive across many domains, where end users have to compose various heterogeneous computational entities to perform professional activities. Service-Oriented Architecture (SOA) is a widely used mechanism that can support such forms of compositions as it allows heterogeneous systems to be wrapped as services that can then be combined with each other. However, current SOA orchestration languages require writing scripts that are typically too low-level for end users to write, being targeted at professional programmers and business analysts. To address this problem, this paper proposes a composition approach based on an end user specification style called SCORE. SCORE is an architectural style that uses high-level constructs that can be tailored for different domains and automatically translated into executable constructs by tool support. We demonstrate the use of SCORE in two domainsdynamic network analysis and neuroscience, where users are intelligence analysts and neuroscientists respectively, who use the architectural style based vocabulary in SCORE as a basis of their domain-specific compositions that can be formally analyzed.