(18b) Predicting Explosibility Properties of Chemicals from Quantitative Structure-Property Relationships
AIChE Spring Meeting and Global Congress on Process Safety
2009
2009 Spring Meeting & 5th Global Congress on Process Safety
43rd Loss Prevention Symposium
Fires, Explosions and Reactive Chemicals
Monday, April 27, 2009 - 10:30am to 11:00am
Quantitative Structure-Property Relationship (QSPR) type methods have been up to now mainly devoted to biological, toxicological applications but their use for the prediction of physico-chemical properties is a growing interest for academic as for industrial scientists. In this context, an original approach associating QSPR methods and quantum chemical calculations for the prediction of chemicals explosibility properties is presented here.
Indeed, the new European regulation of chemicals named REACH (for ?Registration, Evaluation and Authorization of CHemicals?, entered into force in Europe in June 2007) implies that a tremendous number of substances (up to 30000) may require a new assessment of hazardous properties. But, the complete characterization of toxicological, ecotoxicological and physico-chemical hazards at an experimental level is incompatible in term of time and cost with the imposed calendar of REACH. Hence, there is a real need in evaluating capabilities of alternative methods (including QSPR methods) for assessing hazardous properties of chemical substances as a screening process.
This contribution focuses on the models that have been established to predict accurately the thermal stability of a series of potentially explosive nitroaromatic molecules. Descriptors related to the structure of the molecules (topological, geometrical, electronic, quantum chemical), partially obtained from Density Functional Theory (DFT) calculations, were computed and statistical analyses (linear, multilinear regressions) were performed to link correctly the adequate molecular descriptors with the experimental properties. These first results coupling theoretical calculations and QSPR methods open new perspectives for the prediction of other physico-chemical properties.
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