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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Rotureau, Patricia
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (20/20 displayed)
- 2019Estimating the adsorption efficiency of sugar-based surfactants from QSPR modelscitations
- 2017Conformations of n-alkyl-α/β-D-glucopyranoside surfactants : Impact on molecular propertiescitations
- 2016Predictive models for amphiphilic properties of sugar-based surfactants
- 2015How to use QSPR type approaches to predict the properties of green chemicals
- 2015Data analysis of sugar-based surfactant properties : towards quantitative structure property relationships
- 2015Mixture descriptors toward the development of Quantitative Structure-Property Relationship models for the flash points of organic mixturescitations
- 2014Développement de modèles QSPR validés pour la prédiction de la stabilité thermique des peroxydes organiques
- 2013Predicting the physico-chemical properties of chemicals based on QSPR models
- 2013QSPR prediction of physico-chemical properties for REACHcitations
- 2013Prediction of thermal properties of organic peroxides using QSPR models
- 2012Global and local quantitative structure-property relationship models to predict the impact sensitivity of nitro compoundscitations
- 2012Development of validated QSPR models for impact sensitivity of nitroaliphatic compoundscitations
- 2011Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanismscitations
- 2010Excited state properties from ground state DFT descriptors : A QSPR approach for dyescitations
- 2010QSPR modeling of thermal stability of nitroaromatic compounds : DFT vs AM1 calculated descriptorscitations
- 2010Predicting explosibility properties of chemicals from quantitative structure-property relationshipscitations
- 2009On the prediction of thermal stability of nitroaromatic compounds using quantum chemical calculationscitations
- 2009Predicting explosibility properties of chemicals from quantitative structure-property relationships
- 2008Vers la prédiction des propriétés d’explosibilité des substances chimiques par les outils de la chimie quantique et les méthodes statistiques QSPR
- 2008Quantitative structure-property relationship studies for predicting explosibility of nitroaromatic compounds
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document
Predicting the physico-chemical properties of chemicals based on QSPR models
Abstract
Quantitative Structure-Property Relationship models (QSPR) are predictive methods based on correlations between the molecular structures of chemicals and their macroscopic properties. Such methods have been up to now mainly devoted to biological, toxicological applications but their use to predict physico-chemical properties is of growing interest in recent years. In particular, in the framework of the European REACH regulation, the development of such models was recommended as an alternative to experimental tests for reasons. Moreover, such methods represent pertinent tools in screening procedures to select the best performances in any functional properties (e.g. in chemical process) or ensuring at best against hazardous properties (like flammability, explosive or oxidizing properties). To evaluate their reliability, various validation tests are realized. In particular, a robust procedure was proposed by OCDE for their validation for regulatory purpose based on five principles related to the definition of endpoint, the transparency of the model algorithm, its applicability domain, its performances in terms of goodness of fit, robustness and predictive powers, and, if possible, mechanistic interpretation. In that context, INERIS, in collaboration with Chimie ParisTech, develops QSPR models for the prediction of hazardous physico-chemical properties of chemicals like explosive properties of nitro compounds or flammability of amines and organic peroxides. Models were derived according to the OECD validation procedures in view of being submitted to the EU Joint Research Center (JRC) for acceptance or to existing tools (like OECD/ECHA QSAR toolbox for integration.