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Inorganic semiconductors exhibit multifarious physical properties, but they are prevailingly brittle, impeding their application in flexible and hetero-shaped electronics. The exceptional plasticity discovered in InSe crystal indicates the existence of abundant plastically deformable two-dimensional van der Waals (2D vdW) materials, but the conventional trial-and-error method is too time-consuming and costly. Here we report on the discovery of tens of potential 2D chalcogenide crystals with plastic deformability using a nearly automated and efficient high-throughput screening methodology. Seven candidates e.g., famous MoS2, GaSe, and SnSe2 2D materials are carefully verified to show largely anisotropic plastic deformations, which are contributed by both interlayer and cross-layer slips involving continuous breaking and reconstruction of chemical interactions. The plasticity becomes a new facet of 2D materials for deformable or flexible electronics.

In engineering structures that are subject to cyclic loading, monitoring and assessing fatigue crack growth (FCG) plays a crucial role in ensuring reliability. In this study, the acoustic emission (AE) technique was used to monitor the FCG behavior of 2.25Cr1Mo0.25V steel in real-time. Specifically, an AE multi-parameter analysis was conducted to qualitatively assess the crack growth condition and quantitatively correlate the crack growth rate with AE. Various AE parameters were extracted from AE signals, and the performances of different AE parameters were analyzed and discussed. The results demonstrated that four stages of FCG, which correspond to macrocrack initiation, stable crack growth with low crack growth rate, stable crack growth with high crack growth rate, and unstable crack growth, are distinctly identified by several AE time domain parameters. The sudden and continuous occurrence of many AE signals with high count (>100) and high energy (>40 mV·ms) can provide early and effective warning signs for accelerated crack growth before final failure occurs. Moreover, linear correlations between crack growth rate and different AE parameters are established for quantifying crack growth. Based on the AE multi-parameter analysis, it was found that the count, energy, and kurtosis are superior AE parameters for both qualitatively and quantitatively characterizing the FCG in 2.25Cr1Mo0.25V steel. Results from this research provide an AE strategy based on multi-parameter analysis for effective monitoring and assessment of FCG in engineering materials.

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