Curating Metal-Organic Frameworks to Compose Robust Gas Sensor Arrays in Dilute Conditions

Abstract

Metal-organic frameworks (MOFs)-- tunable, nano-porous materials-- are alluring recognition elements for gas sensing. Mimicking human olfaction, an array of cross-sensitive, MOF-based sensors could enable analyte detection in complex, variable gas mixtures containing confounding gas species. Herein, we address the question: given a set of MOF candidates and their adsorption properties, how do we select the optimal subset to compose a sensor array that accurately and robustly predicts the gas composition via monitoring the adsorbed mass in each MOF? We first mathematically formulate the MOF-based sensor array problem under dilute conditions. Instructively, the sensor array can be viewed as a linear map from <i>gas composition space</i> to <i>sensor array response space</i> defined by the matrix <b>H</b> of Henry coefficients of the gases in the MOFs. Characterizing this mapping, the singular value decomposition of <b>H </b>is a useful tool for evaluating MOF subsets for sensor arrays, as it determines the sensitivity of the predicted gas composition to measurement error, quantifies the magnitude of the response to changes in composition, and recovers which direction in gas composition space elicits the largest/smallest response. To illustrate, on the basis of experimental adsorption data, we curate MOFs for a sensor array with the objective of determining the concentration of CO<sub>2</sub> and SO<sub>2</sub> in the gas phase.

Computational Design of MOF-Based Electronic Noses for Dilute Gas Species Detection: Application to Kidney Disease Detection

“…Our approach for array design was borrowed from Sturluson et al, who showed that the array with the best sensitivity could be determined by performing a singular value decomposition on the matrix of Henry’s coefficients for each array, with the best array having the largest minimum singular value . In our work, we used CLACs rather than Henry’s coefficients, but otherwise this method is identical.…”

“…In our previous works, we used computational methods to rapidly design gas-sensing arrays for the detection of methane and carbon dioxide, using metal–organic frameworks (MOFs) as the sensing elements. − MOFs are high-surface-area porous crystals that have been widely explored for gas storage and separation − and more recently have gained attention for gas-sensing applications. − MOFs offer advantages for gas-sensing that stem from their structural and chemical diversity, tunability, and high internal surface areas, resulting in impressive gas adsorption with varied sensitivity. Furthermore, as crystalline materials, their gas adsorption properties can be predicted using well-established computational techniques. , …”

“…A similar strategy was first developed by Sturluson et al In their work, they computationally evaluated Henry’s coefficients for a set of gases (carbon dioxide and sulfur dioxide) and designed sensing arrays of MOFs. However, the key difference between their work and ours is our simultaneous consideration of both trace and nontrace gas species (i.e., gases for which Henry’s law would not apply).…”

Genetic Algorithm Design of MOF-Based Gas Sensor Arrays for CO₂-in-Air Sensing

“…Recently, a number of studies have investigated the use of metal-organic frameworks (MOFs) for improving electronic noses [16][17][18][19][20]. MOFs are promising materials for gas adsorption applications due to their nanoporous nature, high internal surface areas, and ease of tunability [21][22][23][24][25][26][27].…”

“…Similarly, there has been little work on systematically finding the best combinations of MOFs for an array, and with thousands of MOFs to choose from, and thus well over 10 50 possible arrays, determining the top performing arrays is highly non-trivial. A recent paper by Sturluson et al made significant progress in this area by computationally designing MOF-based gas sensing arrays for the detection of CO2 and SO2 in dilute conditions [20]. In their paper, they calculated the Henry's coefficients for each gas/MOF to design an array of elements with maximal complementarity, and consequently the best signal.…”