• Title, Summary, Keyword: QSPR

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A modified scaled variable reduced coordinate (SVRC)-quantitative structure property relationship (QSPR) model for predicting liquid viscosity of pure organic compounds

  • Lee, Seongmin;Park, Kiho;Kwon, Yunkyung;Park, Tae-Yun;Yang, Dae Ryook
    • The Korean Journal of Chemical Engineering
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    • v.34 no.10
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    • pp.2715-2724
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    • 2017
  • Liquid viscosity is an important physical property utilized in engineering designs for transportation and processing of fluids. However, the measurement of liquid viscosity is not always easy when the materials have toxicity and instability. In this study, a modified scaled variable reduced coordinate (SVRC)-quantitative structure property relationship (QSPR) model is suggested and analyzed in terms of its performance of prediction for liquid viscosity compared to the conventional SVRC-QSPR model and the other methods. The modification was conducted by changing the initial point from triple point to ambient temperature (293 K), and assuming that the liquid viscosity at critical temperature is 0 cP. The results reveal that the prediction performance of the modified SVRC-QSPR model is comparable to the other methods as showing 7.90% of mean absolute percentage error (MAPE) and 0.9838 of $R^2$. In terms of both the number of components and the performance of prediction, the modified SVRC-QSPR model is superior to the conventional SVRC-QSPR model. Also, the applicability of the model is improved since the condition of the end points of the modified model is not so restrictive as the conventional SVRC-QSPR model.

Improved QSPR Prediction of Heats of Formation of Alkenes (개선된 QSPR 방법에 의한 알켄의 생성열)

  • Duchowicz, P.;Castro, E.A.
    • Journal of the Korean Chemical Society
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    • v.44 no.6
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    • pp.501-506
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    • 2000
  • Some previous linear equations to predict hydrocarbon heats of formation are generalized. The basic molecular descriptors used for the QSPR analysis are atoms and chemcal bonds. This particular choice makes the method extremely simple and quite inexpensive. The predictions for a set of 19 alkenes yield deviations which are similar to experimental uncertainties. Some possible extensions of the method are pointed out.

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QSPR Models for Chromatographic Retention of Some Azoles with Physicochemical Properties

  • Polyakova, Yulia;Jin, Long Mei;Row, Kyung-Ho
    • Bulletin of the Korean Chemical Society
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    • v.27 no.2
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    • pp.211-218
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    • 2006
  • This work deals with 24 substances composed of nitrogen-containing heterocycles. The relationships between the chromatographic retention factor (k) and those physicochemical properties which are relevant in quantitative structure-properties relationship (QSPR) studies, such as the polarizability $(\alpha)$, molar refractivity (MR), lipophilicity (logP), dipole moment $(\mu)$, total energy $(E_{tot})$, heat of formation $(\Delta H_f)$, molecular surface area $(S_M)$, and binding energy $(E_b)$, were investigated. The accuracy of the simple linear regressions between the chromatographic retention and the descriptors for all of the compounds was satisfactory (correlation coefficient, $0.8 \leq r \leq 1.0$). The QSPR models of these nitrogen-containing heterocyclic compounds could be predicted with a multiple linear regression equation having the statistical index, r = 1.000. This work demonstrated the successful application of the multiple linear approaches through the development of accurate predictive equations for retention factors in liquid chromatography.

QSPR Studies on Impact Sensitivities of High Energy Density Molecules

  • Kim, Chan-Kyung;Cho, Soo-Gyeong;Li, Jun;Kim, Chang-Kon;Lee, Hai-Whang
    • Bulletin of the Korean Chemical Society
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    • v.32 no.12
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    • pp.4341-4346
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    • 2011
  • Impact sensitivity, one of the most important screening factors for novel high energy density materials (HEDMs), was predicted by use of quantitative structure-property relationship (QSPR) based on the electrostatic potential (ESP) values calculated on the van der Waals molecular surface (MSEP). Among various 3D descriptors derived from MSEP, we utilized total and positive variance of MSEP, and devised a new QSPR equation by combining three other parameters. We employed 37 HEDMs bearing a benzene scaffold and nitro substituents, which were also utilized by Rice and Hare. All the molecular structures were optimized at the B3LYP/6-31G(d) level of theory and confirmed as minima by the frequency calculations. Our new QSPR equation provided a good result to predict the impact sensitivities of the molecules in the training set including zwitterionic molecules.

QSPR Study of the Absorption Maxima of Azobenzene Dyes

  • Xu, Jie;Wang, Lei;Liu, Li;Bai, Zikui;Wang, Luoxin
    • Bulletin of the Korean Chemical Society
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    • v.32 no.11
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    • pp.3865-3872
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    • 2011
  • A quantitative structure-property relationship (QSPR) study was performed for the prediction of the absorption maxima of azobenzene dyes. The entire set of 191 azobenzenes was divided into a training set of 150 azobenzenes and a test set of 41 azobenzenes according to Kennard and Stones algorithm. A seven-descriptor model, with squared correlation coefficient ($R^2$) of 0.8755 and standard error of estimation (s) of 14.476, was developed by applying stepwise multiple linear regression (MLR) analysis on the training set. The reliability of the proposed model was further illustrated using various evaluation techniques: leave-many-out crossvalidation procedure, randomization tests, and validation through the test set.

QSPR Analysis of Solvent Effect on Selectivity of 18-Crown-6 between $Nd^{3+}$ and $Eu^{3+}$ Ions: a Monte Carlo Simulation Study

  • Kim, Hag-Sung
    • Bulletin of the Korean Chemical Society
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    • v.27 no.12
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    • pp.2011-2018
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    • 2006
  • We have investigated the solvent effects on $\Delta log\;K_s $(the difference of stability constant of binding) and the different free energies of binding of $Nd^{3+}$ and $Eu^{3+}$ ions to 18-crown-6, i.e., the selectivity of $Nd^{3+}$ and $Eu^{3+}$ ions to 18-crown-6 using a Monte Carlo simulation of statistical perturbation theory (SPT) in diverse solvents. The stability constant ($\Delta log\;K_s $) of binding of $Nd^{3+}$ and $Eu^{3+}$ ions to 18-crown-6, in $CH_3OH$ was calculated in this study as -1.06 agrees well with the different experimental results of -0.44~-0.6, respectively. We have reported here the quantitative solvent-polarity relationships (QSPR) studied on the solvent effects the relative free energies of binding of $Nd^{3+}$ and $Eu^{3+}$ ions to 18-crown-6. From the calculated coefficients of QSPR, we have noted that solvent polarity (ET) and Kamlet -Tafts solvatochromic parameters (b ) dominate the differences in relative solvation Gibbs free energies of $Nd^{3+}$ and $Eu^{3+}$ ions but basicity (Bj) dominates the negative values in differences in the stability constant ($\Delta log\;K_s $) as well as the relative free energies of binding of $Nd^{3+}$ and $Eu^{3+}$ ions to 18-crown-6 and acidity (Aj) dominates the positive values in differences in the stability constant ($\Delta log\;K_s $) as well as the relative free energies of binding of $Nd^{3+}$ and $Eu^{3+}$ ions to 18-crown-6.

Molecular holographic QSPR analysis on the reactivity between glycine and ninhydrin analogues as latent fingerprints detector (잠재지문 검출제로서 Ninhydrin 유도체들과 Glycine과의 반응성에 관한 분자 홀로그래픽적인 QSPR 분석)

  • Kim, Se-Gon;Jang, Seok-Chan;Cho, Yun-Gi;Hwang, Tae-Yeon;Park, Sung-Woo;Sung, Nack-Do
    • Analytical Science and Technology
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    • v.20 no.4
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    • pp.339-346
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    • 2007
  • To search the ninhydrin derivatives that have high chromogenic and fluorogenic properties, molecular holographic quantitative structure property relationship (HQSPR) models on the reactivity between glycine and ninhydrin analogues as latent fingerprint detector were derived and investigated quantitatively. The ${\varepsilon}LUMO$ (e.v.) energy of ninhydrin molecule was an important factor to reactivity of ninhydrin. And, it is suggested that the nucleophilic reaction by orbital-controlled reaction from the frontier molecular orbital (FMO) interaction between glycine and ninhydrin derivatives was more superior than that of electrophilic reaction by charged controlled reaction. The analytical results in atomic contribution maps also shows that the reactivity of ninhydrin was increased by meta-substituents as strong electron withdrawing groups on the benzo ring. Therefore, it is sugested by HQSPR and QSPR model that the 5,6-dinitroninhydrin molecule would increase the reactivity as much as three times as compared to none substituted ninhydrin molecule.

QSPR analysis for predicting heat of sublimation of organic compounds (유기화합물의 승화열 예측을 위한 QSPR분석)

  • Park, Yu Sun;Lee, Jong Hyuk;Park, Han Woong;Lee, Sung Kwang
    • Analytical Science and Technology
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    • v.28 no.3
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    • pp.187-195
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    • 2015
  • The heat of sublimation (HOS) is an essential parameter used to resolve environmental problems in the transfer of organic contaminants to the atmosphere and to assess the risk of toxic chemicals. The experimental measurement of the heat of sublimation is time-consuming, expensive, and complicated. In this study, quantitative structural property relationships (QSPR) were used to develop a simple and predictive model for measuring the heat of sublimation of organic compounds. The population-based forward selection method was applied to select an informative subset of descriptors of learning algorithms, such as by using multiple linear regression (MLR) and the support vector machine (SVM) method. Each individual model and consensus model was evaluated by internal validation using the bootstrap method and y-randomization. The predictions of the performance of the external test set were improved by considering their applicability to the domain. Based on the results of the MLR model, we showed that the heat of sublimation was related to dispersion, H-bond, electrostatic forces, and the dipole-dipole interaction between inter-molecules.

QSPR model for the boiling point of diverse organic compounds with applicability domain (다양한 유기화합물의 비등점 예측을 위한 QSPR 모델 및 이의 적용구역)

  • Shin, Seong Eun;Cha, Ji Young;Kim, Kwang-Yon;No, Kyoung Tai
    • Analytical Science and Technology
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    • v.28 no.4
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    • pp.270-277
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    • 2015
  • Boiling point (BP) is one of the most fundamental physicochemical properties of organic compounds to characterize and identify the thermal characteristics of target compounds. Previously developed QSPR equations, however, still had some limitation for the specific compounds, like high-energy molecules, mainly because of the lack of experimental data and less coverage. A large BP dataset of 5,923 solid organic compounds was finally secured in this study, after dedicated pre-filtration of experimental data from different sources, mostly consisting of compounds not only from common organic molecules but also from some specially used molecules, and those dataset was used to build the new BP prediction model. Various machine learning methods were performed for newly collected data based on meaningful 2D descriptor set. Results of combined check showed acceptable validity and robustness of our models, and consensus approaches of each model were also performed. Applicability domain of BP prediction model was shown based on descriptor of training set.

Quantitative structure-property relationship (QSPR) for prediction of CO2 Henry's law constant in some physical solvents with consideration of temperature effects

  • Gorji, Ali Ebrahimpoor;Gorji, Zahra Eshaghi;Riahi, Siavash
    • The Korean Journal of Chemical Engineering
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    • v.34 no.5
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    • pp.1405-1415
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    • 2017
  • Different types of physical solvents have been utilized for $CO_2$ removal from natural gas in the sweetening process. In this work, quantitative structure-property relationship (QSPR) method is suggested to build powerful models to predict Henry's law constant ($H_{LC}$) for $CO_2$ in physical solvents. Modeling the $H_{LC}$ for $CO_2$ as a function of molecular descriptors was achieved by multiple linear regression and descriptor selection was by genetic algorithm. The main proposed model has two simple descriptors, including the number of hydroxyl groups and molecular weight of solvents at fixed temperature. Also, the effect of temperature was studied, and this operational variable was added to the mentioned simple descriptors. In this case, the data set is comprised of 77 $H_{LC}$ for $CO_2$ in solvents and at different temperatures. Several internal and external validation methods demonstrated the excellent ability for prediction, and the average relative deviation of main model was 6.48.