Ultrasensitive mechanical crack-based sensor inspired by the spider sensory system

By Daeshik Kang, P. Pikhitsa, Y. Choi, Chanseok Lee, Sungsoo Shin, Linfeng Piao, Byeonghak Park, Kahp Y. Suh, Tae‐il Kim, Mansoo Choi. Nature, 2014

1,443 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Cognitive Neuroscience, Polymers and Plastics

View Paper: https://www.semanticscholar.org/paper/29e16497d1362bdcd5bb06d4ac449ce23b31bbb3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Zhong Lin Wang
2. Caofeng Pan
3. Chuntai Liu
4. Ruomeng Yu
5. Changyu Shen
6. Rongrong Bao
7. K. Dai
8. J. Chen

In Cognitive Neuroscience

1. Caofeng Pan
2. Zhong Lin Wang
3. M. Zhang

In Polymers and Plastics

1. Zhong Lin Wang
2. Caofeng Pan
3. Chuntai Liu
4. Changyu Shen
5. K. Dai
6. Rongrong Bao
7. Ruomeng Yu
8. Uttandaraman Sundararaj

Citations in the corpus

• Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses (2023, neutral): “4a) [99, 100].”
• Fracture of graphene: a review (2015, background): “Inspired by spider’s crack-shaped slit organ, Kang et al. (2014) designed an ultrahigh sensitivity sensor based on nanoscale crack junctions by introducing parallel cracks in a nanoscale platinum layer deposited on top of a soft polymer.”