Reactor modelling of treatment chamber for the inactivation of Escherichia coli by radio frequency electric field – mechanistic versus empirical approaches. Issue 12 (2nd July 2018)

• Record Type: Journal Article
• Authors: Masood, Hassan; Cullen, Patrick J; Lee, Nanju A; Trujillo, Francisco J
• Is Part Of: Journal of chemical technology & biotechnology. Volume 93:Issue 12(2018)
• Page Start: 3512
• Page End: 3525
• Publication Date: 2018-07-02
• Subjects: biochemical engineering -- bioprocesses -- disinfection -- process engineering; Biotechnology -- Periodicals; Chemistry, Technical -- Periodicals; Chemical engineering -- Periodicals; Industries -- Environmental aspects -- Periodicals; 660
• DOI: 10.1002/jctb.5712
• Languages: English
• ISSNs: 0268-2575

Abstract

Abstract: BACKGROUND: Inactivation of Escherichia coli, suspended in McIlvaine buffer, was investigated by the application of radio frequency electric field (RFEF) under single‐stage, multi‐stage and recirculation flow configurations using a parallel‐plate treatment chamber. Changes in the survival fraction were correlated, through predictive microbiology, as a function of key process parameters: electric field strength, temperature, time and flow rate, as well as the intrinsic media properties: pH and electrical conductivity. Various empirical models, including Hülsheger, Peleg, Geeraerd and Weibull were compared with mechanistic models, such as the first‐order exponential decay and the two‐term exponential models. Mechanistic models were employed to formulate reactor models by performing differential mass balances over the inactivation chambers, with plug‐flow‐reactor (PFR) assumption for single‐ and multi‐stage configurations, and differential PFR for recirculation configuration. RESULTS: The single‐stage configuration with variable flow rate was proven unsuitable for kinetic studies. Nonlinear logarithmic inactivation profiles were observed with multi‐stage and recirculation. The two‐term exponential mechanistic model effectively explained the kinetics of inactivation. Treatment chambers were successfully modelled mechanistically with reaction engineering principles. Common kinetic constants fitted the experimental data for all flow configurations. The intrinsic properties of media also influenced process kinetics. CONCLUSIONS: The presence of variable resistances amongst microbial population adds nonlinearity in RFEF processing with the extension of the treatment time. The research showed that unlike empirical models, the mechanistic approach can explain the complex inactivation behaviour for all flow configurations. © 2018 Society of Chemical Industry