No 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.

No abstract

Gas–liquid reactions (such as aqueous phase hydrogenations) are frequently mass transport limited. Characterization of reactor overall mass transport performance is key to the successful transfer of reactions across scales or between plants. Despite this need, prediction of mass-transfer performance remains elusive. In this paper, the authors adapt the pressure step method of Teramoto et al. for use in a 1.3 m3 vessel by explicitly accounting for background pressure loss. The method is found to produce theoretically sound results rapidly, with measured hydrogen solubility in water agreeing well with the literature. The measured values of the overall mass-transfer coefficient, k L a, are compared to those predicted by published correlations and modeling tools, which are found to give generally poor predictive performance.