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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
Places of action
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document
How to use QSPR type approaches to predict the properties of green chemicals
Abstract
Faced with current energetic and environmental concerns, the development of safer and cleaner products is a great challenge for industry and a priority at R&D level. It concerns a large diversity of chemicals and applications and encourages innovations in products, in raw materials, and in the involved processes. Complementary to experimental means, INERIS developed Quantitative Structure-Property Relationship models (QSPR) for the prediction of physico-chemical properties of various families of chemicals like amines, organic peroxides, ionic liquids or surfactants. QSPR models 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 [1]. In addition, quantum chemical tools are used not only to compute relevant molecular descriptors (notably issued from the Conceptual Density Functional Theory) but also to evidence the underlying chemical mechanisms. The development of such models is notably recommended, in the framework of the European REACH regulation, as an alternative to experimental tests for reasons. So, models are derived according to the OECD validation procedures [2] in view of being submitted to the EU Joint Research Center (JRC) for acceptance or to existing tools (like OECD/ECHA QSAR toolbox [3]) for integration. Such methods also 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 or explosive properties) for the development of safer products (safety-by-design) or for substitution purpose. In this presentation, we propose to exemplify some key obtained models and we discuss how such models will help in the development of safe green chemicals.