Applications of sensitivity analysis in chemistry

Sensitivity analysis is common in many areas of physics and chemistry.[1] With the accumulation of knowledge about kinetic mechanisms under investigation and with the advance of power of modern computing technologies, detailed complex kinetic models are increasingly used as predictive tools and as aids for understanding the underlying phenomena. A kinetic model is usually described by a set of differential equations representing the concentration-time relationship. Sensitivity analysis has been proven to be a powerful tool to investigate a complex kinetic model.[2][3][4]

Kinetic parameters are frequently determined from experimental data via nonlinear estimation. Sensitivity analysis can be used for optimal experimental design, e.g. determining initial conditions, measurement positions, and sampling time, to generate informative data which are critical to estimation accuracy. A great number of parameters in a complex model can be candidates for estimation but not all are estimable.[4] Sensitivity analysis can be used to identify the influential parameters which can be determined from available data while screening out the unimportant ones. Sensitivity analysis can also be used to identify the redundant species and reactions allowing model reduction.

## References

1. ↑ Saltelli, A.; Ratto, M.; Tarantola, S.; Campolongo, F. (2005). "Sensitivity Analysis for Chemical Models". Chemical Reviews 105 (7): 2811–2828. doi:10.1021/cr040659d. PMID 16011325.
2. ↑ Rabitz, H.; Kramer, M.; Dacol, D. (1983). "Sensitivity Analysis in Chemical Kinetics". Annual Review of Physical Chemistry 34: 419–461. doi:10.1146/annurev.pc.34.100183.002223. Bibcode: 1983ARPC...34..419R.
3. ↑ Turanyi, T. (1990). "Sensitivity analysis of complex kinetic systems. Tools and applications". Journal of Mathematical Chemistry 5 (3): 203–248. doi:10.1007/BF01166355.
4. ↑ 4.0 4.1 Komorowski, M.; Costa, M. J.; Rand, D. A.; Stumpf, M. P. H. (2011). "Sensitivity, robustness, and identifiability in stochastic chemical kinetics models". Proc Natl Acad Sci U S A 108 (21): 8645–50. doi:10.1073/pnas.1015814108. PMID 21551095. Bibcode: 2011PNAS..108.8645K.

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