Since the first successful story was reported in the middle of 1990s, combinatorial materials science has attracted more and more attentions in the materials community. In the past two decades, a great amount of effort has been made to develop combinatorial high-throughput approaches for materials research. However, few high-throughput mechanical characterization methods and tools were reported. To date, a number of micro-scale mechanical characterization tools have been developed, which provided a basis for combinatorial high-throughput mechanical characterization. Many existing micro-mechanical testing apparatuses can be pertinently modified for high-throughput characterization. For example, automated scanning nanoindentation is used for measuring the hardness and elastic modulus of diffusion multiple alloy samples, and cantilever beam arrays are used to parallelly characterize the thermal mechanical behavior of thin films with wide composition gradients. The interpretation of micro-mechanical testing data from thin films and micro-scale samples is most critical and challenging, as the mechanical properties of their bulk counterparts cannot be intuitively extrapolated due to the well-known size and microstructure dependence. Nevertheless, high-throughput mechanical characterization data from combinatorial micro-scale samples still reflect the dependence trend of the mechanical properties on compositions and microstructure, which facilitates the understanding of intrinsic materials behavior and the fast screening of bulk mechanical properties. After the promising compositions and microstructure are pinned down, bulk samples can be prepared to measure the accurate properties and verify the combinatorial high-throughput characterization results. By developing combinatorial high-throughput mechanical characterization methods and tools, in combination with high-throughput synthesis, the structural materials research would be promoted by accelerating the discovery, development, and deployment of high performance structural materials, and by providing full spectrum of materials data for mapping composition-microstructure-mechanical properties. The latter would significantly improve the advanced structural materials design using materials genome engineering approach in the future.
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