Common data analysis errors in batch adsorption studies

Many models exist for describing the experimental results of batch adsorption which are used in research to study equilibrium, kinetics, and mechanisms of adsorption. In the process of statistically analyzing the experimental data, the adsorption literature contains errors that render the results unreliable. These errors include incorrect application of theoretical models and also incorrect application of statistical analysis. Some errors are so abundant in the adsorption literature that they have actually gained credibility and mistakenly taken for granted that these are sound scientific practices. This article highlights some common errors in adsorption data analysis that are frequently found in the literature and provides suggestions for more sound practices.

Research Highlights
► Linearization of models should be only done to improve the error-structure.
► R2 cannot be relied on solely to assess the goodness of fit.
► The plot of pore-diffusion models should be inspected carefully to identify segments.
► A distorted version of Boyd's model is common in the literature.