Results 161 to 170 of about 6,707 (205)
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Journal of Chemical Information and Computer Sciences, 2001
A quantitative structure property relationship study of the flash point of a diverse set of 271 compounds provided a general three-parameter QSPR model (R(2) = 0.9020, R(2)(cv) = 0.8985, s = 16.1). Use of the experimental boiling point as a descriptor gives a three-descriptor equation with R(2) = 0.9529.
Alan R. Katritzky +3 more
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A quantitative structure property relationship study of the flash point of a diverse set of 271 compounds provided a general three-parameter QSPR model (R(2) = 0.9020, R(2)(cv) = 0.8985, s = 16.1). Use of the experimental boiling point as a descriptor gives a three-descriptor equation with R(2) = 0.9529.
Alan R. Katritzky +3 more
openaire +3 more sources
International Journal of Quantitative Structure-Property Relationships, 2020
Predictive modeling of the properties of polymers and polymeric materials is getting more attention, while it is still very complicated due to complexity of these materials. In this review, we discuss main applications of quantitative structure-property/activity relationships (QSPR/QSAR) methods for polymers published recently.
Bakhtiyor Rasulev +1 more
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Predictive modeling of the properties of polymers and polymeric materials is getting more attention, while it is still very complicated due to complexity of these materials. In this review, we discuss main applications of quantitative structure-property/activity relationships (QSPR/QSAR) methods for polymers published recently.
Bakhtiyor Rasulev +1 more
openaire +1 more source
QSPR Treatment of Solvent Scales
Journal of Chemical Information and Computer Sciences, 1999The results of the quantitative structure−property relationship (QSPR) analysis of 45 different solvent scales and 350 solvents using the CODESSA program are presented. The QSPR models for each of the scales are constructed using only theoretical descriptors.
Alan R. Katritzky +4 more
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Journal of Computational Chemistry, 2008
AbstractClassical quantitative structure‐properties relationship (QSPR) statistical techniques unavoidably present an inherent paradoxical computational context. They rely on the definition of a Gram matrix in descriptor spaces, which is used afterwards to reduce the original dimension via several possible kinds of algebraic manipulations.
Ramon Carbó-Dorca +2 more
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AbstractClassical quantitative structure‐properties relationship (QSPR) statistical techniques unavoidably present an inherent paradoxical computational context. They rely on the definition of a Gram matrix in descriptor spaces, which is used afterwards to reduce the original dimension via several possible kinds of algebraic manipulations.
Ramon Carbó-Dorca +2 more
openaire +2 more sources
New QSPRs for Liquid Heat Capacity
Molecular Informatics, 2022AbstractQuantitative Structure‐Property Relationships (QSPRs) have found applications in many areas of chemistry and engineering as effective prediction methods. QSPRs use molecular descriptors to simplify complex molecular properties to a single value and have been used extensively for constant value properties.
Joseph Bloxham +4 more
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A genetic programming-based QSPR model for predicting solubility parameters of polymers
Chemometrics and Intelligent Laboratory Systems, 2015 In this study, linear and nonlinear quantitative structure-property relationship (QSPR) models, respectively called the multiple linear regression based QSPR (MLR-QSPR) model and the genetic programming based QSPR (GP-QSPR) model, were built to predict ...
Koc, Dilek Imren, Koc, Mehmet Levent
exaly +2 more sources
QSPR in Oral Bioavailability: Specificity or Integrality?
Mini-Reviews in Medicinal Chemistry, 2012During the last decade the technological advances in drug discovery changed the absorption, distribution, metabolism, excretion and toxicity (ADMET) profiles of New Chemical Entities (NCEs). Among ADMET processes, absorption plays an important role in the research and development of more effective orally administered drugs.
M Á, Cabrera-Pérez +5 more
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Analysis and refinement of the targeted QSPR method
Computers & Chemical Engineering, 2008Abstract The targeted quantitative structure–property relationship (TQSPR) method of Brauner et al. [Brauner, N., Stateva, R. P., Cholakov, G. St., & Shacham, M. (2006). A structurally “targeted” QSPR method for property prediction. Industrial & Engineering Chemistry Research, 45, 8430–8437] is analyzed in this study with respect to its various ...
Olaf Kahrs +5 more
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A QSPR for the plasticization efficiency of polyvinylchloride plasticizers
Journal of Molecular Graphics and Modelling, 2008A simple quantitative structure property relationship (QSPR) for correlating the plasticization efficiency of 25 polyvinylchloride (PVC) plasticizers was obtained using molecular modeling. The plasticizers studied were-aromatic esters (phthalate, terephthalate, benzoate, trimellitate), aliphatic esters (adipate, sebacate, azelate), citrates and a ...
Mridula, Chandola, Sujata, Marathe
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Automated QSPR through Competitive Workflow
Journal of Computer-Aided Molecular Design, 2005This paper describes a novel software architecture, Competitive Workflow, which implements workflow as a distributed and competitive multi-agent system. The implementation of a competitive workflow architecture designed to model important computer-aided molecular design workflows, the Discovery Bus, is described.
Leahy DE +4 more
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