“…As such, there is a need to better understand the behavior of these materials in order to engineer the next generation of materials that will fulfill these applications. While machine-learning aided materials informatics promises to dramatically accelerate materials design and discovery ( 2 ), validating materials characterization and performance through standard high-strain-rate testing techniques, i.e., plate impact ( 3 ), split Hopkinson bar ( 4 – 6 ), and gas gun impact ( 7 ), still remains a bottleneck in the high-strain-rate materials design cycle due to the low throughput nature and high cost of these testing techniques. In this regard, high-strain-rate nanoindentation has recently emerged as a potentially useful high-throughput testing technique ( 8 ), but it remains unclear whether small-scale measurements adequately capture material deformation behavior at macroscopic scales ( 9 – 12 ).…”