2010
DOI: 10.1021/ac1006415
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Evaluation of the Identification Power of RPLC Analyses in the Screening for Drug Compounds

Abstract: The identification of drugs of abuse is an important issue in forensic science. The main goal is to trace and identify as many drugs as possible in the shortest possible time preferably with a simple analysis method. One possibility is to screen samples using a Liquid Chromatography -Diode Array Detection (LC-DAD) system. However, when simultaneously performing another analysis on a chromatographic column exhibiting selectivity differences from the first one, i.e., orthogonal or dissimilar columns, a greater n… Show more

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Cited by 10 publications
(4 citation statements)
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“…Co-eluted or structurally similar compounds in one chromatogram would likely be separated in the second chromatogram, since 2D-LC provides greatly enhanced peak capacity and selectivity [7]. Deng and co-workers developed an off-line 2D-RP/RP method for the separation of Dracaena Cochinchinensis (lour.).…”
Section: Introductionmentioning
confidence: 99%
“…Co-eluted or structurally similar compounds in one chromatogram would likely be separated in the second chromatogram, since 2D-LC provides greatly enhanced peak capacity and selectivity [7]. Deng and co-workers developed an off-line 2D-RP/RP method for the separation of Dracaena Cochinchinensis (lour.).…”
Section: Introductionmentioning
confidence: 99%
“…For traditional analytical methods, selectivity is defined as the ratio of the slope of the calibration curve for the target analyte to the slope of the calibration curve for a specified interferent [1]. It is desirable to generalize this metric for use with multivariate methods, where multiple interferents occur and dimensional chromatographic separations [6][7][8]. Our interest lies in applying these metrics to assess various attributes of comprehensive two-dimensional liquid chromatography (LC × LC), with and without the benefits of auxiliary spectroscopic data, more specifically by use of a diode array detector (DAD).…”
Section: Introductionmentioning
confidence: 99%
“…Separation and sample dimensionality both contribute to the observed fractional coverage of available separation space. There are many methods for determining fractional coverage of a multidimensional separation including correlation coefficients, , fractal dimensionality, geometric approaches such as a fan area, peak counting, and modified forms of box counting. Rutan et al have demonstrated the merits of the minimum convex hull method for estimating fractional coverage ( ) . The minimum convex hull defines the usable separation space by drawing the smallest convex polygon (i.e., all interior angles are ≤180°) around the outermost peaks of the 2D separation.…”
mentioning
confidence: 99%