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   Active learning facilitated adsorption predictions in porous materials by incorporating “alchemical” molecules, fugacity, and material features (PC1, PC2) using Gaussian process regression. 

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   Paul Ryan Tumminello, Rebecca Meredith (April 2018, Arkansas Aerospace Proceedings)

   The study of water adsorption on mineral surfaces is fundamental to soil and atmospheric science. The physiochemical effects of mineral aerosol influence atmospheric chemistry and climate as well as soil moisture. Iron-containing minerals are abundant on Earth as well as Mars, where the existence and location of surface water is uncertain. Experimental water adsorption measurements have been conducted as a function of relative humidity (RH) on goethite (α-FeO(OH)), a common component of atmospheric mineral dust and Martian crustal material. Water adsorption on goethite was monitored using Horizontal Attenuated Total Reflectance Fourier Transform Infrared (HATR-FTIR) spectroscopy equipped with a flow cell and quantified according to Beer’s Law. Water content as a function of RH was analyzed using type II adsorption isotherms to model multilayer water adsorption. Brunauer Emmet and Teller (BET), Frenkel Halsey and Hill (FHH) and Freundlich adsorption isotherms were applied to model the experimental data. Monolayer water coverage was found to be 4.758x1013 molecules/cm2 based on BET analysis. FHH Adsorption Activation Theory (AT) was used to predict cloud condensation nuclei (CCN) activity of goethite under Earth’s atmospheric conditions. Results aid in the effort of climate prediction on Earth as well as locating liquid water on Mars’ surface. 

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3. Multilayer Random Sequential Adsorption

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4. Tellurite Adsorption onto Bacterial Surfaces

   https://doi.org/10.1021/acs.est.1c01001  

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