PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
October 15, 2025Communications Engineering1 citationsOpen Access

Electrostatic adhesion mitigates aerodynamic losses from gap formations in feathered wings

View Full Paper
KHKevin HaughnJAJeffrey T. AulettaJHJohn T. Hrynuk

Key Points

  • Electrostatic feather fastening enhances maneuverability and aerodynamic efficiency in small uncrewed aircraft.
  • Feathers with electrostatic adhesion outperform passive systems, improving performance at higher velocities.
  • Engineered feather designs can mimic natural wing morphing, adapting to complex and dynamic environments.
  • Incorporating electrostatic adhesion into wing designs can address aerodynamic losses from surface gaps.

Abstract

Abstract Birds morph the shape of their wings during flight to achieve impressive maneuverability and adapt to dynamic environments, such as cities and forests. Engineers have explored using avian-inspired designs with feather-based wing morphing to achieve similar capabilities with small uncrewed aircraft. However, engineered feather designs haven’t incorporated the microscopic structural features that prevent feather separation for natural fliers within dynamic airflows and during wing shape changes. Without a fastening mechanism, gaps can form throughout the wing’s surface that impair maneuverability and shorten flight range. Here we show how electrostatic feather fastening adapts aerodynamic force generation to improve maneuverability and efficiency. Further, the electrostatically adhered feathers offered a preferable relationship with velocity, improving on passive feather aerodynamics and often generating responses comparable or favorable to the baseline engineered wing at higher flow speeds. As small aircraft are expected to fly faster, further, and with advanced aerobatic capability, feathered morphing wings incorporating electrostatic adhesion will advance aircraft adaptability for successful operation in complex environments.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Haughn et al. (2025) studied this question.

synapsesocial.com/papers/68f01110f081da0584b568f5https://doi.org/10.1038/s44172-025-00452-z
Ask AI
Helpful
Bookmark
Share
View Full Paper