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Predictive Models for Thermal Behavior of Chemicals with Quantitative Structure-Property Relationships
Most processes in the chemical industry involve potentially hazardous steps. It is thus of critical importance to perform risk assessments and to know the thermal behavior of the chemicals at stake. A widely used thermal analysis, differential scanning calorimetry, allows verifying if the compounds...
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Published in: | Chemical engineering & technology 2015-04, Vol.38 (4), p.645-650 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Most processes in the chemical industry involve potentially hazardous steps. It is thus of critical importance to perform risk assessments and to know the thermal behavior of the chemicals at stake. A widely used thermal analysis, differential scanning calorimetry, allows verifying if the compounds are stable towards heat or if they decompose above certain temperatures. This information helps setting the appropriate handling and storage conditions for safe operations. The time and resources needed for these experimental investigations would be reduced if the testing phase could be better targeted and guided using reliable predictive methods. This work helps to answer these needs by proposing predictive models for thermal stability based on the quantitative structure‐property relationships method.
Chemicals involved in a process should be thoroughly characterized in order to properly design and implement appropriate safety measures. Experiments demanding resources could be lightened through predictive simulations. Application of predictive quantitative structure‐property relationship to differential scanning calorimetry data offers early estimations of chemicals' thermal stability. |
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ISSN: | 0930-7516 1521-4125 |
DOI: | 10.1002/ceat.201400548 |