A stochastic kinetic study of preparing fatty acid from rapeseed oil via subcritical hydrolysis

Hanjie Xiao, Yizhe Li and Hua Wang

Applied Energy, 2017, vol. 204, issue C, 1084-1093

Abstract: A kinetic model based on the elementary reaction velocity theory is useful for investigating the kinetic rules of chemical reactions under subcritical and supercritical conditions. This model can be used to determine the stochastic relations between the hydrolysis products and conversion time in subcritical water based on the molecular collision theory. First, hydrolysis reaction experiments using rapeseed oil were conducted, and the collected data were used to verify the effectiveness of this stochastic kinetic model. The results showed that the kurtosis of this model was 1.11922, skewness was −1.49277 and mean error of the system was 0.81499, which was relatively small. Meanwhile, the adjustment coefficient (Adj. R2) was 0.98923, which indicated that this model is highly significant, that is, it can accurately depict the microscopic stochastic process of the rapeseed oil hydrolysis reaction. Furthermore, it verifies that the stochastic theory and molecular collision theory are feasible under subcritical conditions, which is a breakthrough in the field of the kinetic study of high-temperature and high-pressure reaction systems. Furthermore, the model reveals the changing rules of the reaction order and reaction velocity of the rapeseed oil hydrolysis reaction, which provides an important reference for parameter optimization of industrial reactor design.

Keywords: Sub-critical; Stochastic kinetics; Hydrolysis reaction; Rapeseed oil; Simulation (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S030626191730507X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:204:y:2017:i:c:p:1084-1093

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2017.05.013

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().