Twist-assisted intrinsic toughening in two-dimensional transition metal dichalcogenides

Xiaodong Zheng, Shizhe Feng, Chi Shing Tsang, Quoc Huy Thi, Wei Han, Lok Wing Wong, Haijun Liu, Chun-Sing Lee, Shu Ping Lau, Thuc Hue Ly*, Zhiping Xu*, Jiong Zhao*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

3 Citations (Scopus)

Abstract

Material fractures are typically irreversible, marking a one-time event leading to failure. Great efforts have been made to enhance both strength and fracture toughness of bulk materials for engineering applications, such as by introducing self-recovery and secondary breaking behaviours. In low-dimensional structures, two-dimensional materials often exhibit exceptional strength but accompanied by extreme brittleness. Here we discover that the toughness of two-dimensional materials can be enhanced without sacrificing strength—by simply twisting the layers. Through in situ scanning transmission electron microscopy, supported by nanoindentation and theoretical analysis, we reveal that twisted bilayer structures enable sequential fracture events: initial cracks heal to form stable grain boundaries, which then shield subsequent fracture tips from stress concentration. This process consumes additional energy compared with conventional fracture, with toughness enhancement tunable through twist angle adjustment. The intrinsic toughening mechanism via twisting, along with the emerging electronic properties of twistronics that are currently attracting substantial attention, presents an exciting opportunity for future devices. © The Author(s), under exclusive licence to Springer Nature Limited 2025.
Original languageEnglish
JournalNature Materials
Online published1 Apr 2025
DOIs
Publication statusOnline published - 1 Apr 2025

Funding

This work was supported by the National Natural Science Foundation of China (grant nos. 52173230, 52222218, 52272045, 12425201 and 52090032), Hong Kong Research Grant Council Collaborative Research Fund (project nos. AoE/P-701/20 and C5067-23G), the Hong Kong Research Grant Council General Research Fund (project nos. 15301623, 11312022, 15302522 and 11300820), the City University of Hong Kong (project nos. 7006005, 9680241 and 9678303), The Hong Kong Polytechnic University (project no. SAC9), Environment and Conservation Fund (project no. 34/2022), The Innovation and Technology Fund (project no. ITS/014/23), the Shenzhen Science, Technology and Innovation Commission (project no. SGDX20230821092059005), The State Key Laboratory of Marine Pollution (SKLMP) Seed Collaborative Research Fund SKLMP/SCRF/0037 and The Research Institute for Advanced Manufacturing of The Hong Kong Polytechnic University. The computation was performed on the Explorer 1000 cluster system of the Tsinghua National Laboratory for Information Science and Technology.

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