QSPR modeling of non-additive binary mixtures : application to the azeotropic behaviour
type: Dataset
description: Generally, QSPR models are limited to individual compounds. In this thesis we have developed a QSPR approach to predict non-additive properties of binary mixtures, more explicitly their azeotropic behavior. To achieve this, several types of quantitative and qualitative models have been developed. This approach is original for two reasons. First, little research has been published on mixtures whose properties are no additive. Second, several new methodological aspects have been introduced in this work. First of all "special" descriptors able to describe mixtures have been proposed. In addition, a robust protocol for obtaining and validating models was used, and a reliable models applicability domain was proposed. The methodology developed during this thesis demonstrates the consistency of a new concept - the QSPR models for mixtures. It is comparable to other conventional methods, though using only limited data.
identifier: NNT: 2012STRAF059
issued: 2026-05-09T17:32:50.167100
language: fr
modified: 2026-05-09T17:32:50.167105
contact point: Organization
  fn: CCSD
keyword: azeotrope
keyword: chemoinformatics
keyword: chemoinformatique
keyword: chimothechemical-sciencesother
keyword: evl
keyword: infoeu-reposemanticsdoctoralthesis
keyword: melanges
keyword: mixtures
keyword: qspr
keyword: theses
landing page: https://theses.hal.science/tel-00862598

QSPR modeling of non-additive binary mixtures : application to the azeotropic behaviour
type: Distribution
format: HTML
issued: 2026-05-09T17:32:50.173190
modified: 2026-05-09T17:32:50.156164
access URL: https://theses.hal.science/tel-00862598

test_moissonnage_selune
type: Agent