Selection of Formal Baseline Correction Methods in Thermal Analysis. Issue 2 (7th December 2021) - Gibson, Rebecca L.; Simmons, Mark J. H.; Stitt, E. Hugh; Horsburgh, Lockhart; Gallen, Robert W.
Abstract: 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. Abstract : Recommendations for formal baseline correction methods for thermal analysis data are given. When lacking physical or experimental justification, only linear baseline correction methods should be used, i.e., linear with time, linear with temperature, and linear with extent of reaction. The absence of baseline correction should also be considered. In silico and experimental data are demonstrated.