Deterministic and stochastic modeling of heterogeneous catalytic selective hydrogenation of vegetable oil

Vegetable oils (VO) can provide sustainable feedstock to substitute chemicals currently obtained from petrol. VO are majorly composed of saturated or unsaturated fatty acids with 18 carbon atoms (C18), free or esterifying glycerol. The monounsaturated C18 fatty acid (C18:1, oleic acid) is of industrial interest. Heterogeneous catalytic selective hydrogenation of VO is studied to maximize the fraction of C18:1 in VO. The current work investigates hydrogenation from the modelling point of view, examining the relation between deterministic models (based on classical ordinary differential equations) and stochastic models (implemented by dedicated algorithms). The investigation starts from experimental data of canola oil treated with H2 in presence of commercial Lindlar catalyst. Two reaction schemes were considered to develop the deterministic models. Two algorithms (Gillespie's stochastic simulation algorithm and tau-leaping) were implemented for stochastic simulations. The whole simulative work was carried out by MATLAB® 2023b. The deterministic model shows that consecutive hydrogenations of one double bond per step with pseudo-first order rate laws – the most straightforward reaction scheme considered in this work – interpret the experimental data well, provided that variable selectivity values are introduced. The stochastic simulations at different numbers of initial molecules allow a multiscale analysis of the system, confirming the reliability of the chosen reaction scheme and suggesting that the experimental system is in its thermodynamic limit, in the sense of statistical–mechanics, at all investigated conditions.