Prediction of the Kováts Retention Indices of Thiols by Use of Quantum Chemical and Physicochemical Descriptors

Zhu, Xiaoming; Wang, W.; Schramm, K.‐W.; Niu, William

doi:10.1365/s10337-007-0237-3

Chroma

2007

DOI: 10.1365/s10337-007-0237-3

|View full text |Cite

Prediction of the Kováts Retention Indices of Thiols by Use of Quantum Chemical and Physicochemical Descriptors

Xiaoming Zhu

W. Wang

K.‐W. Schramm

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2009

2023

Publication Types

Select...

Article5

Relationship

Self Cite0

Independent5

Authors

Journals

Cited by 8 publications

(1 citation statement)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The quantitative structure-property relationship (QSPR) method provides a convenient tool to predict physicochemical properties of chemicals from only molecular structural information, and this may also provide insight into the main factors that influence physicochemical properties of chemicals [14][15][16][17]. R air was influenced by the molecular weight, the substitution patterns of chlorine in PCB, and K oa of POP [2,10,11,18].…”

mentioning

confidence: 99%

QSPR study about sampling rates of semipermeable membrane devices for monitoring of organochlorine pesticides in Alps air

et al. 2011

View full text Add to dashboard Cite

Organochlorine pesticides (OCP) were monitored at the Weissfluhjoch site (Switzerland) and the top of Mt. Sonnblick (Austria) with a low volume active air sampler and semipermeable membrane devices (SPMD). The air sampling rates (R air ) of the SPMD for OCP were calculated. Statistical tests showed that there was no significant difference between R air at the two different sampling sites. Quantitative structure-property relationship (QSPR) models of the R air of the SPMD were developed for OCP using partial least square (PLS) regression. Quantum chemical descriptors computed by the semi-empirical PM6 method were used as predictor variables. The cumulative variance of the dependent variable explained by the PLS components and determined by cross-validation (Q 2 cum ) was >0.818 for each optimal model. This indicates that the model has good predictive ability and robustness. The R air of the SPMD for OCP is related to the total energy, the van der Waals area and the total dipole moment of the OCP molecules. The main factors governing R air values of OCP are intermolecular interactions and the energy required for cavity-formation in dissolution of OCP into triolein of the SPMD. The linear correlation coefficient between predicted and experimental values were all >0.921. air sampling rate, semipermeable membrane device, organochlorine pesticides, quantitative structure-property relationship Citation:Zhu X H, Ding G H, Levy W, et al. QSPR study about sampling rates of semipermeable membrane devices for monitoring of organochlorine pesticides in Alps air.

show abstract

mentioning

confidence: 99%

QSPR study about sampling rates of semipermeable membrane devices for monitoring of organochlorine pesticides in Alps air

et al. 2011

View full text Add to dashboard Cite

show abstract

Quantitative Structure‐Retention Relationship Study of Mercapto‐Compounds by the Method of Dividing the Molecular Structure into Substructure

Liu

Cao

2009

QSAR Comb. Sci.

View full text Add to dashboard Cite

In order to investigate the quantitative structure-retention relationship in gas chromatography (GC) of mercapto-esters, alcohols, aldehydes, and ketones, the molecular structure RX is divided into two parts, R and X to generate structural parameter. It was proposed that the retention index (RI) is affected by three main factors for mercaptocompounds: alkyl group R, substituted group X, and interaction between R and X. On the basis of the PEI index previously developed by Cao, the novel total polarizability effect index (TPEI) combining with odd-even index (OEI) previously developed in our team, were used to predict the RI of mercapto-compounds. A high quality model (R 2 ¼ 0.9839, s ¼ 23.5, F ¼ 1432.2) was generated using only calculated descriptors and multiple linear regression techniques. Good results were also obtained for the external data set.

show abstract

Accurate prediction of isothermal gas chromatographic Kováts retention indices

Anjum

Liigand

Milford

et al. 2023

Journal of Chromatography A

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Prediction of the Kováts Retention Indices of Thiols by Use of Quantum Chemical and Physicochemical Descriptors

Cited by 8 publications

References 26 publications

QSPR study about sampling rates of semipermeable membrane devices for monitoring of organochlorine pesticides in Alps air

QSPR study about sampling rates of semipermeable membrane devices for monitoring of organochlorine pesticides in Alps air

Quantitative Structure‐Retention Relationship Study of Mercapto‐Compounds by the Method of Dividing the Molecular Structure into Substructure

Accurate prediction of isothermal gas chromatographic Kováts retention indices

Contact Info

Product

Resources

About