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    Comparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study
    (Columbus, Ohio : American Chemical Society, 2020) Guo S.; Beleites C.; Neugebauer U.; Abalde-Cela S.; Afseth N.K.; Alsamad F.; Anand S.; Araujo-Andrade C.; Aškrabić S.; Avci E.; Baia M.; Baranska M.; Baria E.; Batista De Carvalho L.A.E.; De Bettignies P.; Bonifacio A.; Bonnier F.; Brauchle E.M.; Byrne H.J.; Chourpa I.; Cicchi R.; Cuisinier F.; Culha M.; Dahms M.; David C.; Duponchel L.; Duraipandian S.; El-Mashtoly S.F.; Ellis D.I.; Eppe G.; Falgayrac G.; Gamulin O.; Gardner B.; Gardner P.; Gerwert K.; Giamarellos-Bourboulis E.J.; Gizurarson S.; Gnyba M.; Goodacre R.; Grysan P.; Guntinas-Lichius O.; Helgadottir H.; Grošev V.M.; Kendall C.; Kiselev R.; Kölbach M.; Krafft C.; Krishnamoorthy S.; Kubryck P.; Lendl B.; Loza-Alvarez P.; Lyng F.M.; Machill S.; Malherbe C.; Marro M.; Marques M.P.M.; Matuszyk E.; Morasso C.F.; Moreau M.; Muhamadali H.; Mussi V.; Notingher I.; Pacia M.Z.; Pavone F.S.; Penel G.; Petersen D.; Piot O.; Rau J.V.; Richter M.; Rybarczyk M.K.; Salehi H.; Schenke-Layland K.; Schlücker S.; Schosserer M.; Schütze K.; Sergo V.; Sinjab F.; Smulko J.; Sockalingum G.D.; Stiebing C.; Stone N.; Untereiner V.; Vanna R.; Wieland K.; Popp J.; Bocklitz T.
    The variable configuration of Raman spectroscopic platforms is one of the major obstacles in establishing Raman spectroscopy as a valuable physicochemical method within real-world scenarios such as clinical diagnostics. For such real world applications like diagnostic classification, the models should ideally be usable to predict data from different setups. Whether it is done by training a rugged model with data from many setups or by a primary-replica strategy where models are developed on a 'primary' setup and the test data are generated on 'replicate' setups, this is only possible if the Raman spectra from different setups are consistent, reproducible, and comparable. However, Raman spectra can be highly sensitive to the measurement conditions, and they change from setup to setup even if the same samples are measured. Although increasingly recognized as an issue, the dependence of the Raman spectra on the instrumental configuration is far from being fully understood and great effort is needed to address the resulting spectral variations and to correct for them. To make the severity of the situation clear, we present a round robin experiment investigating the comparability of 35 Raman spectroscopic devices with different configurations in 15 institutes within seven European countries from the COST (European Cooperation in Science and Technology) action Raman4clinics. The experiment was developed in a fashion that allows various instrumental configurations ranging from highly confocal setups to fibre-optic based systems with different excitation wavelengths. We illustrate the spectral variations caused by the instrumental configurations from the perspectives of peak shifts, intensity variations, peak widths, and noise levels. We conclude this contribution with recommendations that may help to improve the inter-laboratory studies. © 2020 American Chemical Society.
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    Glow discharge optical emission spectrometry for quantitative depth profiling of CIGS thin-films
    (Cambridge : Royal Society of Chemistry, 2019) Kodalle, T.; Greiner, D.; Brackmann, V.; Prietzel, K.; Scheu, A.; Bertram, T.; Reyes-Figueroa, P.; Unold, T.; Abou-Ras, D.; Schlatmann, R.; Kaufmann, C.A.; Hoffmann, V.
    Determining elemental distributions dependent on the thickness of a sample is of utmost importance for process optimization in different fields e.g. from quality control in the steel industry to controlling doping profiles in semiconductor labs. Glow discharge optical emission spectrometry (GD-OES) is a widely used tool for fast measurements of depth profiles. In order to be able to draw profound conclusions from GD-OES profiles, one has to optimize the measurement conditions for the given application as well as to ensure the suitability of the used emission lines. Furthermore a quantification algorithm has to be implemented to convert the measured properties (intensity of the emission lines versus sputtering time) to more useful parameters, e.g. the molar fractions versus sample depth (depth profiles). In this contribution a typical optimization procedure of the sputtering parameters is adapted to the case of polycrystalline Cu(In,Ga)(S,Se)2 thin films, which are used as absorber layers in solar cell devices, for the first time. All emission lines used are shown to be suitable for the quantification of the depth profiles and a quantification routine based on the assumption of constant emission yield is used. The accuracy of this quantification method is demonstrated on the basis of several examples. The bandgap energy profile of the compound semiconductor, as determined by the elemental distributions, is compared to optical measurements. The depth profiles of Na-the main dopant in these compounds-are correlated with measurements of the open-circuit voltage of the corresponding devices, and the quantification of the sample depth is validated by comparison with profilometry and X-ray fluorescence measurements.