<p>Design of micro/nanotextured consumer product surfaces presents the opportunity to enrich tactile experiences and enhance the capabilities of haptic devices, enabling rich human-object interactions through the passive or active control of finger friction. The absence of a comprehensive model that can holistically represent the underlying physics at finger-material interface, however, inhibits reliable prediction of finger friction. Here, we develop a model for micro/nanostructured touch interfaces, accounting for contact mechanics, capillaries, electrostatic fields, and their mutual interactions. We experimentally validate this model and apply it to predicting the friction and adhesion of microparticle-coated plastic films for food packaging, and designing surface structures for electroadhesive surfaces to achieve both stronger effects and lower variability — essential features for high-volume consumer electronics. Our model has wide applicability in predictive design of micro/nanostructured surfaces with diverse haptic functionalities.</p>

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Predictive design of tactile friction for micro/nanostructured haptic surfaces

  • Yuan Ma,
  • Xinyi Li,
  • Xuezhi Ma,
  • Changhyun Choi,
  • Luke Kruse,
  • Shoufeng Lan,
  • M. Cynthia Hipwell

摘要

Design of micro/nanotextured consumer product surfaces presents the opportunity to enrich tactile experiences and enhance the capabilities of haptic devices, enabling rich human-object interactions through the passive or active control of finger friction. The absence of a comprehensive model that can holistically represent the underlying physics at finger-material interface, however, inhibits reliable prediction of finger friction. Here, we develop a model for micro/nanostructured touch interfaces, accounting for contact mechanics, capillaries, electrostatic fields, and their mutual interactions. We experimentally validate this model and apply it to predicting the friction and adhesion of microparticle-coated plastic films for food packaging, and designing surface structures for electroadhesive surfaces to achieve both stronger effects and lower variability — essential features for high-volume consumer electronics. Our model has wide applicability in predictive design of micro/nanostructured surfaces with diverse haptic functionalities.