Jenna’s paper on optimizing information content in MOF arrays for gas sensing takes the top prize in Pitt’s Department of Chemical & Petroleum Engineering.
The image depicts the overall approach of this work to optimize MOF array selection for methane-air gas mixtures. A MOF based electronic nose is modeled via atomistic simulations. The results are used to gather information regarding an unknown gas mixture to quantify the performance of various array configurations.
The algorithm presented in the paper acts as an efficient screening tool for MOF array selection.
J. A. Gustafson and C. E. Wilmer. “Optimization of information content in MOF sensor arrays for analyzing methane-air mixtures..” Sensors and Actuators B: Chemical 267. (2018): 483-493. DOI: 10.1016/j.snb.2018.04.049