4.6 Article

Influence of pH on the kinetics of hydrolysis reactions: the case of epichlorohydrin and glycidol

Journal

REACTION CHEMISTRY & ENGINEERING
Volume 7, Issue 10, Pages 2211-2223

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/d2re00191h

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Funding

  1. ENI S.p.A

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In this study, the conditions for the formation of harmful compounds during the use of GL and EPI in aqueous environments were identified and corresponding processes to prevent their formation were designed. Experimental results showed that temperature, pH, and chloride ion concentration were crucial factors for the formation of these compounds. The developed kinetic model provided a prediction of reaction rates and served as a basis for optimizing processes by considering the critical role of pH.
Glycidol (GL) and epichlorohydrin (EPI) are two widely used molecules in chemical, pharmaceutical and food industry applications. However, their use in aqueous environments causes the formation of compounds, like monochloropropanediol (MCPD) and dichloropropanol (DCP), reported as dangerous for human health and therefore regulated by severe law restrictions. To identify the conditions leading to such species and design the corresponding processes in order to prevent their formation, hydrolysis and chlorination of EPI and GL, together with dehydrohalogenation of DCP and MCPD, have been systematically analysed. Different reaction conditions in terms of temperature, pH and chloride ion concentration have been experimentally investigated and the concentration of the involved species was tracked over time by gas chromatography and high-performance liquid chromatography. These experimental data were fitted through a kinetic model, which allowed a general expression of the observed rate constant of each reaction as a function of temperature and pH to be quantified. In particular, the reaction rates are conveniently expressed as combinations of three contributions: alkaline, neutral and acid. The corresponding rate laws explicitly account for the critical role of pH. The developed mechanistic model exhibits good prediction ability and may represent the basis for optimising processes employing EPI and GL.

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