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Quantitative high-throughput measurement of bulk mechanical properties using commonly available equipment.

Justin E GriffithYusu ChenQingsong LiuQifeng WangJeffrey J RichardsDanielle Tullman-ErcekKenneth R ShullMuzhou Wang
Published in: Materials horizons (2022)
Machine learning approaches have introduced an urgent need for large datasets of materials properties. However, for mechanical properties, current high-throughput measurement methods typically require complex robotic instrumentation, with enormous capital costs that are inaccessible to most experimentalists. A quantitative high-throughput method using only common lab equipment and consumables with simple fabrication steps is long desired. Here, we present such a technique that can measure bulk mechanical properties in soft materials with a common laboratory centrifuge, multiwell plates, and microparticles. By applying a homogeneous force on the particles embedded inside samples in the multiwell plate using centrifugation, we show that our technique measures the fracture stress of gels with similar accuracy to a rheometer. However, our method has a throughput on the order of 10 3 samples per run and is generalizable to virtually all soft material systems. We hope that our method can expedite materials discovery and potentially inspire the future development of additional high-throughput characterization methods.
Keyphrases
  • high throughput
  • single cell
  • machine learning
  • high resolution
  • rna seq
  • small molecule
  • current status
  • mass spectrometry
  • robot assisted