Prediction of the retentions of polybrominated dibenzo-p-dioxins (PBDDs) by using the retentions of polychlorinated dibenzo-p-dioxins (PCDDs)

Chromatographic and Ionization Properties of Polybrominated Diphenyl Ethers Using GC/High-Resolution MS with Metastable Atom Bombardment and Electron Impact Ionization

“…33 Results using the MAB-N 2 and EI GC programs were identical; only the results for the MAB-N 2 program are shown in Figure 1. Overall, the utility of such RRT models based on calculated physicochemical properties resides in the identification of previously unobserved congeners in environmental samples.…”

“…Similar linear relationships between GC-RRTs and observed and calculated physicochemical properties have been reported for polychlorinated biphenyls (PCBs), [26][27][28] polychlorinated diphenyl ethers (PCDEs), 29 polychlorinated dibenzo-p-dioxins 26,30 and dibenzofurans (PCDD/Fs), 26,31,32 and polybrominated dibenzo-p-dioxins (PBDDs). 33 Results using the MAB-N 2 and EI GC programs were identical; only the results for the MAB-N 2 program are shown in Figure 1. Overall, the utility of such RRT models based on calculated physicochemical properties resides in the identification of previously unobserved congeners in environmental samples.…”

Three-dimensional holographic vector of atomic interaction field for quantitative structure-retention relationship of purine bases

“…In the past significant work has been done for QSRR [1,2] researches, for retention index predictions, separation condition selections and retention mechanism exploration [3] . For example, QSRR models [4][5][6][7][8][9][10] were established by introducing such descriptors as molecular geometrical characteristics, topological structures and diversities of physicochemical parameters. However, it was difficult to construct QSRR model for organic and biological molecules because they were based on 2D structures without considering interactions among compounds, fixed phase and fluxion phase.…”

Development of a Multiple-Class High-Resolution Gas Chromatographic Relative Retention Time Model for Halogenated Environmental Contaminants

“…However, given the large number of potential contaminants and the lack of analytical standards, predictive tools are needed to assist researchers in screening environmental samples for novel compounds. Several models have been developed to predict relative GC retention times (GC-RRTs) of individual halogenated organic contaminant classes, such as those for PCBs, − PCDEs, PCDDs, , PCDFs, ,, and PBDDs, yet no further attempts have been made to develop a predictive GC-RRT model for more than one contaminant class after such an approach was successfully demonstrated by Ong and Hites …”

“…However, given the large number of potential contaminants and the lack of analytical standards, predictive tools are needed to assist researchers in screening environmental samples for novel compounds. Several models have been developed to predict relative GC retention times (GC-RRTs) of individual halogenated organic contaminant classes, such as those for PCBs, [4][5][6] PCDEs, 7 PCDDs, 4,8 PCDFs, 4,9,10 and PBDDs, 11 yet no further attempts have been made to develop a predictive GC-RRT model for more than one contaminant class after such an approach was successfully demonstrated by Ong and Hites. 4 The objective of this work was to identify a set of easily calculated variables that could be successfully used as descriptors in a predictive GC-RRT model for each of the following individual halogenated contaminant classes: PBDEs, PCDEs, PCBs, PCNs, PCDDs, PCDFs, PBDDs, PBDFs, and organochlorine pesticides.…”