Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer–Emmett–Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of micro‐ and mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already‐measured raw adsorption isotherms were provided to sixty‐one labs, who were asked to calculate the corresponding BET areas. This round‐robin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called “BET surface identification” (BETSI), expands on the well‐known Rouquerol criteria and makes an unambiguous BET area assignment possible.

Information on mixture adsorption equilibrium is vital in developing adsorption-based separation processes. Because measuring mixture adsorption is more difficult than measuring single-component adsorption, far more data of the latter kind are available. Previous efforts to compile experimental mixture adsorption data for gases have given data sets with at most a few dozen examples. Here, we report the results of systematic literature meta-analysis that produced a data set of more than 900 gas mixture adsorption experiments. This collection includes data from 125 different binary mixtures including 60 different molecular species and information from 333 different adsorbents. We refer to this data set as the Binary adsorption ISOtherm ExperimeNtal 2020 (BISON-20) Database. Because the BISON-20 data set enormously expands the number and variety of experimental results for binary gas adsorption that are readily available, it will be a useful resource for future efforts in developing new materials or processes for gas separations. As initial applications of the BISON-20 data set, we show how identifying replicate measurements can be used to assess the reliability of binary adsorption data, how the accuracy of Ideal Adsorbed Solution Theory (IAST) can be systematically tested using experimental data, and how trends in selectivity for gas separations across many materials can be examined.

Systematic collection of replicate experimental data via literature meta-analysis is a powerful approach for assessing the reproducibility of physical properties data. In this paper, we use meta-analysis to examine the adsorption equilibrium of alcohols in porous materials using a collection of more than 500 alcohol isotherm measurements. We report consensus isotherms (after rejecting outliers) using experimentally measured replicates for 11 systems with methanol, ethanol, 1-propanol, or 2-methylpropan-1-ol adsorption as well as assess experimental reproducibility for another 50 systems with these adsorbates, 1-butanol or 2-phenylethan-1-ol. Our analysis indicates that ∼20% of reported adsorption isotherms for alcohols are outliers, an observation that is similar to earlier analyses of CO2 adsorption experiments. We compare a variety of replicate experiments using metal–organic framework adsorbents with predictions from molecular simulations using generic force fields in order to examine the ability of these simulations to predict alcohol adsorption in these materials.

Identification of independent experimental replicate measurements of well-defined physical properties provides a useful way to assess the reproducibility of literature reports of these properties. Prior meta-analysis of this kind for single-component adsorption of CO2 and alcohols in nanoporous materials showed that ∼20% of reported isotherms for these molecules were inconsistent with available replicate measurements. In this paper, we extend this analysis to the single-component adsorption of alkanes in nanoporous materials using a collection of 2998 experimental isotherms. Among these isotherms, 846 replicates were identified and analyzed. Many more replicates are available for CH4 adsorption than for any other alkane. Our analysis finds that 15% of the replicate alkane isotherms are inconsistent with other replicate measurements. After discarding these outlier isotherms we report graphical and numerical consensus isotherms for 93 independent combinations of adsorbate, adsorbent, and temperature as well as an assessment of another 124 independent systems for which two replicate isotherms are available.

Using adsorption isotherm data to determine heats of adsorption or predict mixture adsorption using the ideal adsorbed solution theory (IAST) relies on accurate fits of the data with continuous, mathematical models. Here, we derive an empirical two-parameter model to fit isotherm data of IUPAC types I, III, and V in a descriptive way based on the Bass model for innovation diffusion. We report 31 isotherm fits to existing literature data covering all six types of isotherms, various adsorbents, such as carbons, zeolites, and metal–organic frameworks (MOFs), as well as different adsorbing gases (water, carbon dioxide, methane, and nitrogen). We find several cases, especially for flexible MOFs, where previously reported isotherm models reached their limits and either failed to fit the data or could not sufficiently be fitted due to stepped type V isotherms. Moreover, in two instances, models specifically developed for distinct systems are fitted with a higher R 2 value compared to the models in the original reports. Using these fits, it is demonstrated how the new Bingel–Walton isotherm can be used to qualitatively assess the hydrophilic or hydrophobic behavior of porous materials from the relative magnitude of the two fitting parameters. The model can also be employed to find matching heats of adsorption values for systems with isotherm steps using one, continuous fit instead of partial, stepwise fits or interpolation. Additionally, using our single, continuous fit to model stepped isotherms in IAST mixture adsorption predictions leads to good agreement with the results from the osmotic framework adsorbed solution theory that was specifically developed for these systems using a stepwise, approximate fitting, which is yet far more complex. Our new isotherm equation accomplishes all of these tasks with only two fitted parameters, providing a simple, accurate method for modeling a variety of adsorption behavior.