(269h) A Bayesian Approach to Curate the Optimal Sensing Elements for a Quantitative Gas Sensor Array

Our objective is to showcase a Bayesian computational method to curate the optimal combination of sensing elements for a gas sensor array. We achieve this objective by treating the gas sensing task as a statistical inverse problem. As an illustrative example, we demonstrate our method by curating the optimal pair of zeolitic imidazolate frameworks for a gravimetric sensor array for CO₂/C₂H₄ sensing.