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Ion mobility spectrometry (IMS) is capable of providing real-time analysis of several impurities in inert gases. Because of its poor peak resolution, the IMS is susceptible to peak interferences. Previous study has shown that the detection limit and accuracy of [O.sub.2] measurement in [N.sub.2] suffers from peak interference. In many applications, the interference can be avoided by selecting a proper drift gas. For [N.sub.2] analysis, we have demonstrated that the peak interference of [O.sub.2] can be eliminated by using Ar as a drift gas. The use of Ar changes the chemical reactions that occur inside the drift region and results in different product ions. The peaks of new product ions are well-separated and do not coincide with the peak representing [O.sub.2].

Atmospheric pressure ionization mass spectrometry (APIMS) is being routinely used to quantify trace impurities in bulk gases used in the manufacture of semiconductor devices. APIMS has been successfully applied for the quantification of ppt levels of [O.sub.2], [H.sub.2]O, C[O.sub.2], and C[H.sub.4] in Ar, [N.sub.2], and He. However, it has not been successfully used to quantify trace impurities in bulk [O.sub.2] due to the low ionization potential of [O.sub.2]. APIMS relies on charge-transfer reaction between the ions of the bulk gas molecules and impurity molecules. Since all the relevant impurity molecules have ionization potentials higher than that of [O.sub.2], APIMS has not been used to analyze for impurities in [O.sub.2]. We report here the detection of sub-ppb levels of [H.sub.2]O in [O.sub.2] by making use of the clustering reaction between [[O.sub.2].sup.+] and [H.sub.2]O. The declustering region in an APIMS, which is normally used to break apart unwanted and interfering clusters, has to be carefully adjusted to keep intact the weakly bound cluster [[O.sub.2].sup.+][multiplied by][H.sub.2]O. Our results indicate a statistical detection limit of less than 300 ppt for the detection of [H.sub.2]O in [O.sub.2].

The use of ion mobility spectrometry (IMS) for the determination of trace moisture and oxygen in bulk nitrogen has been explored. IMS utilizes atmospheric pressure ionization to ionize trace impurities in the sample gas. Mobility differences between trace impurity ions are exploited to separate these ions. Our results indicate that an IMS can indeed be used to detect [is less than] 1 ppb [O.sub.2] and [H.sub.2]O in bulk nitrogen. Due to the nature of the interaction between trace moisture and oxygen, a multivariate calibration has to be used to obtain quantitative results, even at levels below 2 ppb.

Failure to appropriately account for the nonconstant variance in the calibration data often leads to unreasonable estimates of calibration parameters. In this paper, we contrast the normal regression-based approach (ordinary least squares) as applied to trace metals data collected via inductively coupled plasma mass spectrometry with a modified least-squares approach which explicitly uses the variance of the calibration data (weighted least squares). The use of ordinary least squares, in the case where the variance of the calibration data is not constant, results in inaccurate assessment of the intercept. The impact of this is to provide inaccurate results, at low concentration values. This is precisely the region of the greatest interest. In contrast, the use of a weighted least-squares approach results in the accurate determination of the intercept, thus providing accurate results at low concentration values. Method detection limits can also be calculated based on the two regression approaches. The weighted least-squares approach generally results in lower detection limits. Recovery experiments performed using a spiked blank indicate that use of the weighted approach is indeed representative of the performance of the instrument used to generate the calibration data.