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

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.