1996
DOI: 10.1016/0098-1354(94)00012-d
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Computer-assisted approach to develop a new prediction method of liquid viscosity of organic compounds

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Cited by 30 publications
(41 citation statements)
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“…Earlier, QSPR studies on the viscosity of conventional moleculartype organic compounds have been performed, and the results are summarized in Table 5 [70][71][72][73][74][75][76]. As indicated in Table 5, for molecular-type organic compounds, the most important factor that affects the viscosity is generally the intermolecular hydrogenbonding interactions; the dipole moment (i.e., the polarizability mostly arising from polar atoms), which mainly reflects the intermolecular van der Waals interactions, gives remarkable contributions to the viscosity; the steric bulk, shape, and size of a molecule also have some effects on the viscosity.…”
Section: Comparison With Organic Compoundsmentioning
confidence: 99%
“…Earlier, QSPR studies on the viscosity of conventional moleculartype organic compounds have been performed, and the results are summarized in Table 5 [70][71][72][73][74][75][76]. As indicated in Table 5, for molecular-type organic compounds, the most important factor that affects the viscosity is generally the intermolecular hydrogenbonding interactions; the dipole moment (i.e., the polarizability mostly arising from polar atoms), which mainly reflects the intermolecular van der Waals interactions, gives remarkable contributions to the viscosity; the steric bulk, shape, and size of a molecule also have some effects on the viscosity.…”
Section: Comparison With Organic Compoundsmentioning
confidence: 99%
“…Hence the QSPR approach is a general and reliable method to predict various physicochemical properties. Suzuki et al 6 used a combination of partial least-squares (PLS) and QSPR techniques to search for correlations between viscosity and 18 parameters, mostly experimental. They found five significant PLS components and proposed a nine-descriptor model for a set of 237 compounds which gave a squared correlation coefficient (R …”
Section: Introductionmentioning
confidence: 99%
“…It is also regarded as empirical modeling which relies on reported experimental data from chemical processes. It is difficult to generate a prediction model using mathematical modeling containing various chemical reaction equations and constants, while empirical modeling has the advantage that a prediction model can be set up with reported experimental data easily (Suzuki, Ohtaguchi, & Koide, 1996;Kim, Lee, Chung, & Choi, 2005;Kim, Lee, Chung, & Choi, 2006). In this study, the partial least squares (PLS) method, which is a multivariate analysis method, was used in order to establish a prediction model based on the experimental FP data of binary liquid mixtures including n-butanol þ n-propionic acid, M.E.K.…”
Section: Multivariate Statistical Analysis Methodsmentioning
confidence: 98%