Crude Glycerol Hydrogenolysis to Bio-Propylene Glycol: Effect of Its Impurities on Activity, Selectivity and Stability

Author:

Gatti Martín12ORCID,Pompeo Francisco12ORCID,Nichio Nora12,Santori Gerardo12

Affiliation:

1. Centro de Investigación y Desarrollo en Ciencias Aplicadas (CINDECA), Facultad de Ciencias Exactas, Universidad Nacional de La Plata (UNLP)-CONICET, Calle 47, 257, La Plata 1900, Argentina

2. Facultad de Ingeniería, Universidad Nacional de La Plata (UNLP), Calle 1 esq. 47, La Plata 1900, Argentina

Abstract

The wide availability of crude glycerol and its low market price make this by-product of the biodiesel industry a promising raw material for obtaining high-value-added products through catalytic conversion processes. This work studied the effect of the composition of different industrial crude glycerol samples on the catalytic hydrogenolysis to 1,2-propylene glycol. A nickel catalyst supported on a silica–carbon composite was employed with this purpose. This catalyst proved to be active, selective to 1,2-propylene glycol and stable in the glycerol hydrogenolysis reaction in the liquid phase when analytical glycerol (99% purity) was employed. In order to determine the effect of crude glycerol composition on the activity, selectivity and stability of this catalyst, industrial crude glycerol samples were characterized by identifying and quantifying the impurities present in them (methanol, NaOH, NaCl and NaCOOH). Reaction tests were carried out with aqueous solutions of analytical glycerol, adding different impurities one by one in their respective concentration range. These results allowed for calculating activity factors starting from the ratio between the rate of glycerol consumption in the presence and in the absence of impurities. Finally, catalyst performance was evaluated employing the industrial crude glycerol samples, and a kinetic model based on the power law was proposed, which fitted the experimental results taking into account the effect of glycerol impurities. The fit allowed for predicting conversion values with an average error below 8%.

Funder

CONICET

UNLP

Publisher

MDPI AG

Subject

Process Chemistry and Technology,Chemical Engineering (miscellaneous),Bioengineering

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