Scientific literature is replete with descriptions of novel adsorbent materials, making the selection of such adsorbents for gas storage and separation a trudging task, and often resulting in overlooked materials. Here, we use a high throughput methodology o process a dataset of 28 000 adsorption isotherms from the NIST adsorption database (ISODB) and generate key performance indicators applicable to ambient temperature binary separation on 1500 materials in the collection, with 30 adsorbed guests. The procedure is validated against high-quality laboratory isotherms to confirm the accuracy of the derived indicators. The results are then collated in a powerful online dashboard, which can be used to explore the binary correlations. Finally, we use this toolchain to scrutinize several challenging and industrially relevant case studies and highlight somematerials which may be promising for further analysis.
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