Mechanical sensors based on two-dimensional materials: Sensing mechanisms, structural designs and wearable applications

Abstract

Compared with bulk materials, atomically thin two-dimensional (2D) crystals possess a range of unique mechanical properties, including relatively high in-plane stiffness and large bending flexibility. The atomic 2D building blocks can be reassembled into precisely designed heterogeneous composite structures of various geometries with customized mechanical sensing behaviors. Due to their small specific density, high flexibility, and environmental adaptability, mechanical sensors based on 2D materials can conform to soft and curved surfaces, thus providing suitable solutions for functional applications in future wearable devices. In this review, we summarize the latest developments in mechanical sensors based on 2D materials from the perspective of function-oriented applications. First, typical mechanical sensing mechanisms are introduced. Second, we attempt to establish a correspondence between typical structure designs and the performance/multi-functions of the devices. Afterward, several particularly promising areas for potential applications are discussed, following which we present perspectives on current challenges and future opportunities.

Keywords: Bioelectronics; Materials in biotechnology; Materials science.

Graphical abstract

Figure 1

Structural designs and wearable applications of mechanical sensors based on 2D materials Adapted from Refs. [(Cheng et al., 2015) (Dinh et al., 2019) (Wang et al., 2019b) (Zhang et al., 2020) (Zhang and Tao, 2019) (Yang et al., 2018) (Yao et al., 2020), (Tao et al., 2017)].

Figure 2

2D geometries (A–C) (A) Lateral 2D crystal structures; (B) Vertical 2D crystal structures; (C) Heterogeneously designed 2D crystal composite structures.

Figure 3

Mechanoelectrical coupling mechanisms related to the interface-related sliding and cracking behaviors (A–D) (A) Slippage induced conductivity change between neighboring flakes; (B) Slippage induced buckling for graphene film after stretch and release (left), and the center strain in graphene during loading and unloading (right) (scale bars: 10 μm); (C) A tunneling pressure sensor based on graphene/h-BN/graphene sandwich structure (left) and corresponding measurement results (right); (D) A graphene-on-PET strain sensor based on fractured structures. Adapted from Refs. [(Hempel et al., 2012) (Jiang et al., 2014) (Xu et al., 2011), (Tian et al., 2014)].

Figure 4

Heterogeneous composite structures based on 2D crystals (A–C) (A) Ti₃C₂T_x-AgNW-PDA/Ni²⁺ sensor with a “brick-and-mortar” structure, and the corresponding electrical response under different strain; (B) Schematic illustration of sensing mechanism for GO-AgNW sensing film versus GO-AgNW-C60 sensing films; (C) Morphology of the graphene/TPU foam. Adapted from Refs. [(Shi et al., 2018c) (Shi et al., 2018b), (Liu et al., 2017a)].

Figure 5

Capacitive and piezoelectric principles (A and B) (A) Typical capacitive sensing and supercapacitive/iontronic sensing; (B) Typical piezoelectric d₁₁ and d₃₃ working modes.

Figure 6

High performance-oriented structural designs (A) Spider's legs inspired crack-type sensor with high sensitivity; (B) Fingertip skin inspired pressure sensor with high sensitivity due to the interlocking microstructure; (C) A graphene based helical spring accommodating ultra-large tensile strains (>1,000%); (D) Double-covered yarn-shaped graphene fiber with capability to differentiate various knee-related motions, such as knee flexing/extending, walking, jogging, jumping, and squatting jumping. Adapted from Refs. [(Cheng et al., 2015) (Dinh et al., 2019) (Wang et al., 2019b), (Zhang et al., 2020)].

Figure 7

Multifunction-oriented structural designs (A) Transient electronics that have abilities of strong adhesion and easy detachment from skin; (B) Schematic and optical images of deeply scratched graphene composites during the healing process (scale bar: 1 mm); (C) Variable structural coloration of graphene composite interphase under different strains; (D) Graphene based sensors with good gas permeability. Adapted from Refs. [(Zhang and Tao, 2019) (D'Elia et al., 2015) (Deng et al., 2017), (Sun et al., 2018)].

Figure 8

Wearable applications and machine learning-assisted smart sensors (A) Graphene textile strain sensor for human motion detection; (B) Graphene pressure sensor for various gait detection; (C) Graphene artificial throat based on the pattern recognition and machine learning with sound-sensing and sound-emitting ability; (D) Graphene vibrotactile sensitive sensors to recognize textures with an accuracy of 97% using a machine learning algorithm. Adapted from Refs. [(Yang et al., 2018) (Pang et al., 2018) (Tao et al., 2017), (Yao et al., 2020)].