A light-powered self-rotating liquid crystal elastomer drill

Yu, Yong; Hu, Haoyu; Wu, Haiyang; Dai, Yuntong; Li, Kai

doi:10.1016/j.heliyon.2024.e27748

Cited by 3 publications

(2 citation statements)

References 75 publications

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“…Mathematics 2024, 12, x FOR PEER REVIEW 2 of 7 [38,39], torsion [40,41], self-floating [42], swinging [43], swimming [44], buckling [45][46][47], jumping [48][49][50], rotation [51][52][53], chaos [54], and reverse [55,56]. Even several coupled self-excited oscillators that can move synchronously are proposed [57].…”

Section: Rotational Dynamics Of a Self-rotating Skipping Ropementioning

confidence: 99%

“…Recently, there has been an increase in the development of self-oscillating systems crafted from materials that react to stimuli, including but not limited to hydrogels [14,18,19], ionic gels [20], dielectric elastomers [21], and liquid crystal elastomers (LCEs) [22][23][24][25][26][27]. By using these materials, a variety of self-excited motion patterns have been demonstrated, including rolling [28][29][30][31], bending [32][33][34][35], vibration [36,37], telescoping [38,39], torsion [40,41], self-floating [42], swinging [43], swimming [44], buckling [45][46][47], jumping [48][49][50], rotation [51][52][53], chaos [54], and reverse [55,56]. Even several coupled self-excited oscillators that can move synchronously are proposed [57].…”

Section: Introductionmentioning

confidence: 99%

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Behavior Prediction and Inverse Design for Self-Rotating Skipping Ropes Based on Random Forest and Neural Network

Qiu,

Wu,

Dai

et al. 2024

Mathematics

Self Cite

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Self-oscillatory systems have great utility in energy harvesting, engines, and actuators due to their ability to convert ambient energy directly into mechanical work. This characteristic makes their design and implementation highly valuable. Due to the complexity of the motion process and the simultaneous influence of multiple parameters, computing self-oscillatory systems proves to be challenging, especially when conducting inverse parameter design. To simplify the computational process, a combined approach o0f Random Forest (RF) and Backpropagation Neural Network (BPNN) algorithms is employed. The example used is a self-rotating skipping rope made of liquid crystal elastomer (LCE) fiber and a mass block under illumination. Numerically solving the governing equations yields precise solutions for the rotation frequency of the LCE skipping rope under various system parameters. A database containing 138,240 sets of parameter conditions and their corresponding rotation frequencies is constructed to train the RF and BPNN models. The training outcomes indicate that RF and BPNN can accurately predict the self-rotating skipping rope frequency under various parameters, demonstrating high stability and computational efficiency. This approach allows us to discover the influences of distinct parameters on the rotation frequency as well. Moreover, it is capable of inverse design, meaning it can derive the corresponding desired parameter combination from a given rotation frequency. Through this study, a deeper understanding of the dynamic behavior of self-oscillatory systems is achieved, offering a new approach and theoretical foundation for their implementation and construction.

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Section: Rotational Dynamics Of a Self-rotating Skipping Ropementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Behavior Prediction and Inverse Design for Self-Rotating Skipping Ropes Based on Random Forest and Neural Network

Qiu,

Wu,

Dai

et al. 2024

Mathematics

Self Cite

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Self-oscillation of cantilevered silicone oil paper sheet system driven by steam

Zhao,

Dai,

Dai

et al. 2024

Thin-Walled Structures

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Self-Oscillation of a Liquid Crystal Elastomer String-Mass System Under Constant Gradient Temperature

Ge,

Liang,

2024

Journal of Applied Mechanics

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Recent experiments have found that a fiber-mass system can self-oscillate along the vertical direction under a non-uniform temperature field, which necessitates significant vertical space. To address the challenge in adapting to situations with limited vertical space, the current work introduces a self-oscillating string-mass system, comprising of a mass ball and a thermally responsive liquid crystal elastomer string exposed to a constant gradient temperature. By employing theoretical modeling and numerical simulation, we have identified two motion regimes of the system, namely, the static regime and the self-oscillation regime, and elucidated the mechanism of self-oscillation. Utilizing the analytical method, we derived the expressions for bifurcation point, amplitude, and frequency of the self-oscillation, and investigated the impact of system parameters on these aspects, which were verified by numerical solutions. Compared to a fiber-mass system, the string-mass system has superior stability to deal with small horizontal disturbances, can amplify its amplitude and frequency limited by small thermal deformation of material, and saves a significant amount of vertical space. Given these attributes, such self-oscillating string-mass system presents novel possibilities for designing energy harvesters, active machinery, and soft robots.

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A light-powered self-rotating liquid crystal elastomer drill

Cited by 3 publications

References 75 publications

Behavior Prediction and Inverse Design for Self-Rotating Skipping Ropes Based on Random Forest and Neural Network

Behavior Prediction and Inverse Design for Self-Rotating Skipping Ropes Based on Random Forest and Neural Network

Self-oscillation of cantilevered silicone oil paper sheet system driven by steam

Self-Oscillation of a Liquid Crystal Elastomer String-Mass System Under Constant Gradient Temperature

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