Non-kinetic phenomena in thermal analysis data; Computational fluid dynamics reactor studies

Gibson, Rebecca L.; Simmons, Mark; Stitt, E. Hugh; Liu, Li; Gallen, Robert W.

doi:10.1016/j.cej.2021.130774

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“…This work has highlighted the importance of selecting a suitable baseline correction method for thermal analysis data. To remove the human/experiential factor which can be associated with this preprocessing step, this work has recommended the Berggren model prediction for a three-thermal event system [32].…”

Section: Discussionmentioning

confidence: 99%

Selection of Formal Baseline Correction Methods in Thermal Analysis

et al. 2021

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Baseline correction is a key step in processing of thermal analysis data. Whilst this is a common step, techniques range from linear baselines to use of high‐order polynomials. When considering a formal baseline correction (those without physical or experimental justification), only linear correction methods should be used: linear with time, linear with temperature, and linear with extent of reaction. The absence of baseline correction should also be considered. An in silico study shows that the wrong baseline correction can significantly impact the parameters obtained from kinetic modeling. The four baseline correction methods are demonstrated with a mass spectrometry dataset. It is recommended that the selection of correction method should be based on comparison of Akaike weights.

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Section: Discussionmentioning

confidence: 99%