AIChE Annual Meeting
Tuesday, November 15, 2022 - 2:18pm to 2:36pm
Discovery of novel materials has been significantly expedited by predictive modeling and machine learning. However, training these models requires large datasets of material properties, the generation of which requires improvement of materials characterization throughput. Although some high-throughput testing methods have been developed to combinatorically characterize mechanical properties, existing methods are limited by requiring custom instrumentation or slow sample fabrication steps. To address this issue, we have developed a high-throughput, quantitative, and widely accessible technique to measure the fracture strength of bulk soft materials. Our method involves embedding dense particles within gel samples in a multiwell plate, inverting the plate, and then centrifuging it at increasing speeds until the particles break out of the gels. Centrifugation applies a homogeneous force on all particles, so we can gauge material strength by measuring the centrifugal speed at which a sample fractures. We have analytically proven that this fracture speed is quantitatively related to the fracture strength of the material, which is verified by comparing centrifugal results to shear rheology measurements. Moreover, the throughput of our method is on the order of 103 samples per run, limited only by the number of wells in each plate. Measurements that would take weeks or months with classic mechanical testing can be performed in a single day with our method. Crucially, our technique only uses common or commercially available equipment, so virtually any lab can utilize it. We believe that our method is well-suited to revolutionize and accelerate development towards the next generation of smartly engineered materials.