Effects of correlated parameters and uncertainty in electronic-structure-based chemical kinetic modelling


Kinetic models based on first principles are becoming common place in heterogeneous catalysis because of their ability to interpret experimental data, identify the rate-controlling step, guide experiments and predict novel materials. To overcome the tremendous computational cost of estimating parameters of complex networks on metal catalysts, approximate quantum mechanical calculations are employed that render models potentially inaccurate. Here, by introducing correlative global sensitivity analysis and uncertainty quantification, we show that neglecting correlations in the energies of species and reactions can lead to an incorrect identification of influential parameters and key reaction intermediates and reactions. We rationalize why models often underpredict reaction rates and show that, despite the uncertainty being large, the method can, in conjunction with experimental data, identify influential missing reaction pathways and provide insights into the catalyst active site and the kinetic reliability of a model. The method is demonstrated in ethanol steam reforming for hydrogen production for fuel cells.

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Figure 1: Correlations in parametric uncertainty and their effect on global SA predictions.
Figure 2: Quantification of the uncertainty in conversion, selectivity, rates, ethanol reaction order and apparent activation energy.
Figure 3: SRPA of the initial dehydrogenation steps and uncertainty distributions for fractional consumption and net rates.


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The ethanol mechanism and the DFT calculations were supported by the Catalysis Center for Energy Innovation, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Office of Basic Energy Sciences under award number DE-SC0001004. The uncertainty analysis formulation was supported by the US Department of Energy, Office of Basic Energy Sciences, under Contract No. DE-AC02-98CH10886 and Contract No. DE-SC0010723 and the sensitivity of model ensembles by grants R115-1342R1 and W911NF-15-2-0122 from the Defense Advanced Research Projects Agency. The DFT calculations were carried out at the TeraGrid provided by the Texas Advanced Computing Center of the University of Texas at Austin. The CGSA calculations were carried out on the clusters at the Center for Functional Nanomaterials at Brookhaven National Laboratory and the National Energy Research Scientific Computing Center.

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J.E.S. implemented the correlative SA, performed the calculations and analysed the results. W.G. performed the GPAW calculations. D.G.V. conceived the problem, M.A.K. formulated the mathematical foundations of the correlative SA and both supervised J.E.S. and W.G. All the authors contributed to writing the paper.

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Correspondence to Dionisios G. Vlachos.

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The authors declare no competing financial interests.

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Sutton, J., Guo, W., Katsoulakis, M. et al. Effects of correlated parameters and uncertainty in electronic-structure-based chemical kinetic modelling. Nature Chem 8, 331–337 (2016). https://doi.org/10.1038/nchem.2454

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