Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

External factor variable connectivity index.

Qian-Nan Hu1, Yi-Zeng Liang, Ya-Li Wang

  • 1Institute of Chemometrics and Intelligent Analytical Instruments, College of Chemistry and Chemical Engineering, Central South University, Changsha, 410083, P. R. China.

Journal of Chemical Information and Computer Sciences
|May 28, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Immunomodulatory effects of cannabis use: a multi-omics study in people living with HIV.

Brain, behavior, & immunity - health·2026
Same author

Formation Process and Solid-Liquid Phase Equilibrium of Cs(Cl, Br) Solid Solutions in Aqueous Solution.

The journal of physical chemistry. B·2026
Same author

Multi-omics Data Integration.

Advances in experimental medicine and biology·2026
Same author

Simultaneous In-Depth Single-Cell Proteomic and Metabolomic Analysis.

Analytical chemistry·2026
Same author

HIV immunological non-responders show low SKAP1 concentration and DNA hypermethylation in the SKAP1 promotor region: Low Skap1 in HIV Immunological Non-Responders.

AIDS (London, England)·2026
Same author

Interferon-related inflammaging links epigenetic age acceleration to multimorbidity.

Cell genomics·2026
Same journal

Future Papers.

Journal of chemical information and computer sciences·2016
Same journal

Future Papers.

Journal of chemical information and computer sciences·2016
Same journal

Future Papers.

Journal of chemical information and computer sciences·2016
Same journal

Future Papers.

Journal of chemical information and computer sciences·2016
Same journal

Future Papers.

Journal of chemical information and computer sciences·2016
Same journal

Future Papers.

Journal of chemical information and computer sciences·2016
See all related articles

A novel external factor variable connectivity index (EFVCI) was developed to predict alkane boiling points. This new index shows high accuracy, outperforming existing methods in correlating molecular structure with physical properties.

Area of Science:

  • Quantitative Structure-Property Relationships (QSPR)
  • Cheminformatics
  • Physical Organic Chemistry

Background:

  • Predicting physicochemical properties like boiling point is crucial in chemistry.
  • Existing molecular descriptors often struggle to capture complex interatomic interactions accurately.

Purpose of the Study:

  • To introduce a new variable index, the external factor variable connectivity index (EFVCI).
  • To assess the efficacy of EFVCI in correlating molecular structure with the boiling points of acyclic alkanes.

Main Methods:

  • The EFVCI divides atomic attributes into innate (outer-shell electrons) and external (perturbation by other atoms) components.
  • A topological structure interpretation is used for the EFVCI.
  • Regression analysis was performed on 149 acyclic alkanes to correlate boiling points with EFVCI.

Related Experiment Videos

Main Results:

  • The EFVCI demonstrated a strong correlation with the boiling points of acyclic alkanes.
  • Optimal EFVCI values approached a constant (-0.29) for the series.
  • High regression quality was achieved (R = 0.9986, s = 2.26, F = 7088.4).
  • EFVCI performance was favorably compared to the variable connectivity index and molecular connectivity index.

Conclusions:

  • The EFVCI is a promising new descriptor for predicting boiling points.
  • EFVCI effectively captures the influence of external factors on molecular properties.
  • This index offers improved accuracy over traditional connectivity indices for QSPR studies.