مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Cites:

Information Journal Paper

Title

QUANTITATIVE STRUCTURE–RETENTION RELATIONSHIP ANALYSIS OF NANOPARTICLE COMPOUNDS

Pages

  107-110

Abstract

 Genetic algorithm and partial least square (GA-PLS), the kernel PLS (KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between RETENTION TIME (RT) and descriptors for 15 NANOPARTICLE COMPOUNDS which obtained by the comprehensive two dimensional gas chromatography system (GC×GC). Application of the DODECANETHIOL monolayer-protected gold nanoparticle (MPN) column was for a high-speed separation as the second column of GC×GC. The L-M ANN model with the final optimum network architecture of [9-4-1] gave a significantly better performance than the other models. This is the first research on the quantitative structure–retention relationship (QSRR) of the NANOPARTICLE COMPOUNDS using the GA-PLS, GA-KPLS and L-M ANN.

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    • Cite

    APA: Copy

    NOORIZADEH, H., & FARMANY, A.. (2011). QUANTITATIVE STRUCTURE–RETENTION RELATIONSHIP ANALYSIS OF NANOPARTICLE COMPOUNDS. JOURNAL OF PHYSICAL AND THEORETICAL CHEMISTRY, 8(2), 107-110. SID. https://sid.ir/paper/587930/en

    Vancouver: Copy

    NOORIZADEH H., FARMANY A.. QUANTITATIVE STRUCTURE–RETENTION RELATIONSHIP ANALYSIS OF NANOPARTICLE COMPOUNDS. JOURNAL OF PHYSICAL AND THEORETICAL CHEMISTRY[Internet]. 2011;8(2):107-110. Available from: https://sid.ir/paper/587930/en

    IEEE: Copy

    H. NOORIZADEH, and A. FARMANY, “QUANTITATIVE STRUCTURE–RETENTION RELATIONSHIP ANALYSIS OF NANOPARTICLE COMPOUNDS,” JOURNAL OF PHYSICAL AND THEORETICAL CHEMISTRY, vol. 8, no. 2, pp. 107–110, 2011, [Online]. Available: https://sid.ir/paper/587930/en

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