Overview

Metal-Organic Frameworks (MOFs) are a novel class of nanoporous materials which are being explored for numerous exiciting applications, including gas sensing. Owing to the huge number of building blocks, these porous cooridnation polymers exhibit a wide range of chemical and physical properties. By leveraging these differences, we can build sensors capable of simultaneously identifying hundreds of different compounds, and even determining thier concentratoions.

By using an array of sensing elements, we can build sensors capable of extracting highly dimensional information from gas mixtures. However, with hundreds of thousands of sensing materials to choose from, and an uncountably high number of array configurations, developing truly universal gas sensors will need to be aided by computational approaches. Using well-established computational techniques, we can conduct a high-throughput, detailed analysis of materials in silco to accelerate experimental work and device design.

With the ability to robotically "smell" in the same way the cameras robotically "see" or microphones robotically "hear", a huge number of exciting applications become possible, from advanced environmental monitoring to breath-based disease detection. The missing piece then becomes: how do we translate from sensor data into actionable information? By leveraging artificial intellegce and physics-informed algorithms, we can do exactly that, much in the same way that computer vision allows software to analyze and identify objects in images.