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Selection of Formal Baseline Correction Methods in Thermal Analysis
Author(s) -
Gibson Rebecca L.,
Simmons Mark J. H.,
Stitt E. Hugh,
Horsburgh Lockhart,
Gallen Robert W.
Publication year - 2022
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/ceat.202100120
Subject(s) - baseline (sea) , akaike information criterion , range (aeronautics) , selection (genetic algorithm) , computer science , mathematics , statistics , algorithm , artificial intelligence , engineering , oceanography , geology , aerospace engineering
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.