Stable isotope quality assurance using the 'Calibrated IRMS' strategy

Procedures in our laboratory have always been directed towards complete understanding of all processes involved and corrections needed etc., instead of relying fully on laboratory reference materials. This rather principal strategy (or attitude) is probably not optimal in the economic sense, and is not necessarily more accurate either. Still, it has proven to be very rewarding in its capability to detect caveats that go undiscovered in the standard way of measurement, but that do influence the accuracy or reliability of the measurement procedure. An additional benefit of our laboratory procedures is that it makes us capable of assisting the International Atomic Energy Agency (IAEA) with primary questions like mutual scale assignments and comparison of isotope ratios of the same isotope in different matrices (like delta(18)O in water, carbonates and atmospheric CO(2)), establishment of the (17)O-(18)O relation, and the replenishment of the calibration standards. Finally, for manual preparation systems with a low sample throughput ( and thus only few reference materials analysed) it may well be the only way to produce reliable results

Ice-liquid isotope fractionation factors for O-18 and H-2 deduced from the isotopic correction constants for the triple point of water

The stable isotopes of water are extensively used as tracers in many fields of research. For this use, it is essential to know the isotope fractionation factors connected to various processes, the most important of which being phase changes. Many experimental studies have been performed on phase change fractionation over the last decades. Whereas liquid-vapour fractionation measurements are relatively straightforward, vapour-solid and liquid-solid fractionation measurements are more complicated, as maintaining equilibrium conditions when a solid is involved is difficult. In this work, we determine the ice-liquid isotope fractionation factors in an indirect way, by applying the Van't Hoff equation. This equation describes the relationship of the fractionation factors with isotope-dependent temperature changes. We apply it to the recently experimentally determined isotope dependences of the triple point temperature of water [Faghihi V, Peruzzi A, Aerts-Bijma AT, et al. Accurate experimental determination of the isotope effects on the triple point temperature of water. I. Dependence on the H-2 abundance. Metrologia. 2015;52:819-826; Faghihi V, Kozicki M, Aerts-Bijma AT, et al. Accurate experimental determination of the isotope effects on the triple point temperature of water. II. Combined dependence on the O-18 and O-17 abundances. Metrologia. 2015;52:827-834]. This results in new values for the H-2 (deuterium) and O-18 fractionation factors for the liquid-solid phase change of water, which agree well with existing, direct experimental data [Lehmann M, Siegenthaler U. Equilibrium oxygen- and hydrogen-isotope fractionation between ice and water. J Glaciol. 1991;37:23-26]. For H-2, the uncertainty is improved by a factor of 3, whereas for O-18 the uncertainty is similar. Our final results are (S-L) (H-2/H-1)=1.02093(13), and (S-L) (O-18/O-16)=1.002909(25), where the latter is the weighted average of the previous experimental study and this work

The use of wavelet analysis and the mixture model to study phase-locking related to task-set reconfiguration

Abstract Wavelet analysis provides information on the time course of the phase and amplitude of oscillations in non-stationary signals. The results of wavelet analysis are equivalent to those of the faster method of complex demodulation. We combined this method with the mixture model to identify differences in the time course of synchrony between brain areas during task-set reconfiguration. The mixture model provides a trial-by-trial likelihood of intention activation , that is, of subjectdriven reconfiguration prior to stimulus presentation. This allows prepared and nonprepared conditions to be distinguished within the switch condition, identical in every way except for the odds of preparation. Preliminary results could not, due to equipment failures, be reliably interpreted, but did indicate that this combined approach may provide interesting results in the future

Biogenic Carbon Fraction of Biogas and Natural Gas Fuel Mixtures Determined with 14C

This study investigates the accuracy of the radiocarbon-based calculation of the biogenic carbon fraction for different biogas and biofossil gas mixtures. The focus is on the uncertainty in the C-14 reference values for 100% biogenic carbon and on the C-13-based isotope fractionation correction of the measured C-14 values. The separately (AMS) measured CO2 and CH4 fractions of 8 different biogas samples showed C-14 values between 102% and 116% (pMC). The delta C-13 values of these samples varied between -6% and +31% for the CO2 fraction and between -28% and -62% for the CH4 fraction. The uncertainty in calculated biogenic carbon fractions due to uncertainty in the C-14 reference values depends on the available information about the origin of the used biogenic materials. It varies between +/- 0.5% and +/- 3.5% (absolute) depending on the type of biogas. A method is proposed to minimize this uncertainty for different groups of biogases. The calculated biogenic carbon fraction deviates up to +/- 2.5% for biofossil gas mixtures, if the applied isotope fractionation correction is based on the delta C-13 value of the mixed biofossil sample instead of the biogenic delta C-13 value. Combination of both error sources shows that the uncertainty in the calculated biogenic carbon fraction varies between +/- 0.7% and +/- 4.5%, depending on the type of biogas in the sample