Mobility Control of Mechanical Bonds to Modulate Energy Dissipation in Mechanically Interlocked Networks

Mechanically interlocked networks (MINs) with dense mechanical bonds can amplify the dynamic behaviors of the mechanical bonds to exhibit decent mechanical properties. Energy dissipation resulting from mechanical bond motion is essential for improving toughness, yet effective strategies to optimize this process remain underexplored. Here, by designing mechanical bond models with controllable mobility, we establish a fortification strategy for the two key factors governing energy dissipation, host-guest recognition and sliding friction, thereby enabling mechanical property enhancement of mechanically interlocked materials. Specifically, the [2]rotaxanes in MIN-<b>1</b> and MIN-<b>2</b> exhibit identical axle structures, with MIN-<b>1</b> incorporating a small benzo-21-crown-7 ring and MIN-<b>2</b> incorporating a large benzo-24-crown-8 ring. Strain rate-dependent cyclic tensile tests reveal that the energy required to drive mechanical bond motion in MIN-<b>1</b> and MIN-<b>2</b> is 510 and 260 kJ/m<sup>3</sup>, respectively, indicating that the small wheel size enhances host-guest recognition. Furthermore, the apparent activation energy for the sliding motion of the mechanical bonds in MIN-<b>1</b> (11.0 kJ/mol) is higher than that in MIN-<b>2</b> (6.70 kJ/mol), suggesting increased sliding friction in MIN-<b>1</b>. Due to these two aspects, MIN-<b>1</b> exhibits superior energy dissipation performance (damping capacity = 92%) compared to MIN-<b>2</b> (78%), translating to a higher toughness (7.50 vs 5.70 MJ/m<sup>3</sup>).

Authors

Institutions

Publication Details

Journal
Journal of the American Chemical Society
Published
2025-03-11
DOI
https://doi.org/10.1021/jacs.5c00108
Citations
11
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
7.85
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mobility Control of Mechanical Bonds to Modulate Energy Dissipation in Mechanically Interlocked Networks

Zhewen Guo, Xuzhou Yan, Xue Yang, Ruixue Bai et al.
11 citations
Journal of the American Chemical Society
Modular Robots and Swarm Intelligence
7.85
article

Mobility Control of Mechanical Bonds to Modulate Energy Dissipation in Mechanically Interlocked Networks

Zhewen Guo, Xuzhou Yan, Xue Yang, Ruixue Bai, Lin Cheng, Zhaoming Zhang, Wenbin Wang, Wei Yu
article en
11 citations

Abstract

Mechanically interlocked networks (MINs) with dense mechanical bonds can amplify the dynamic behaviors of the mechanical bonds to exhibit decent mechanical properties. Energy dissipation resulting from mechanical bond motion is essential for improving toughness, yet effective strategies to optimize this process remain underexplored. Here, by designing mechanical bond models with controllable mobility, we establish a fortification strategy for the two key factors governing energy dissipation, host-guest recognition and sliding friction, thereby enabling mechanical property enhancement of mechanically interlocked materials. Specifically, the [2]rotaxanes in MIN-<b>1</b> and MIN-<b>2</b> exhibit identical axle structures, with MIN-<b>1</b> incorporating a small benzo-21-crown-7 ring and MIN-<b>2</b> incorporating a large benzo-24-crown-8 ring. Strain rate-dependent cyclic tensile tests reveal that the energy required to drive mechanical bond motion in MIN-<b>1</b> and MIN-<b>2</b> is 510 and 260 kJ/m<sup>3</sup>, respectively, indicating that the small wheel size enhances host-guest recognition. Furthermore, the apparent activation energy for the sliding motion of the mechanical bonds in MIN-<b>1</b> (11.0 kJ/mol) is higher than that in MIN-<b>2</b> (6.70 kJ/mol), suggesting increased sliding friction in MIN-<b>1</b>. Due to these two aspects, MIN-<b>1</b> exhibits superior energy dissipation performance (damping capacity = 92%) compared to MIN-<b>2</b> (78%), translating to a higher toughness (7.50 vs 5.70 MJ/m<sup>3</sup>).

Journal of the American Chemical SocietyVol. 147(12)
Shanghai Jiao Tong University (CN)
Affordable and clean energy
Openalex Percentile: Top 2%
Modular Robots and Swarm Intelligence
7.85
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.