Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Accurate prediction of discontinuous crack paths in random porous media via a generative deep learning model.

Proceedings of the National Academy of Sciences of the United States of America·2024
Same author

Growth of Double-Network Tough Hydrogel Coatings by Surface-Initiated Polymerization.

ACS applied materials & interfaces·2024
Same author

High-cycle fatigue life prediction of L-PBF AlSi10Mg alloys: a domain knowledge-guided symbolic regression approach.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2023
Same author

A potential paradigm in CRISPR/Cas systems delivery: at the crossroad of microalgal gene editing and algal-mediated nanoparticles.

Journal of nanobiotechnology·2023
Same author

Alignment of Heptagonal Diimide and Triazine Enables Narrowband Pure-Blue Organic Light-Emitting Diodes with Low Efficiency Roll-Off.

Angewandte Chemie (International ed. in English)·2023
Same author

Nomogram combining clinical and radiological characteristics for predicting the malignant probability of solitary pulmonary nodules measuring ≤ 2 cm.

Frontiers in oncology·2023

Related Experiment Video

Updated: Sep 16, 2025

Hollow Microneedle-based Sensor for Multiplexed Transdermal Electrochemical Sensing
08:19

Hollow Microneedle-based Sensor for Multiplexed Transdermal Electrochemical Sensing

Published on: June 1, 2012

14.5K

Puncturing soft substrates with microneedle Arrays: Experiments, simulations, and machine learning predictions.

Nan Hu1, Junjie Liu1, Qifang Zhang1

  • 1School of Mechanics and Aerospace Engineering, Sichuan Province Key Laboratory of Advanced Structural Materials Mechanical Behavior and Service Safety, Southwest Jiaotong University, Chengdu, Sichuan, 611756, China.

Journal of the Mechanical Behavior of Biomedical Materials
|July 6, 2025
PubMed
Summary

This study reveals how microneedle geometry impacts insertion force and depth. Optimized designs, informed by experiments and simulations, enhance microneedle array performance for medical applications.

Keywords:
Machine learningMicroneedle arraysOptimal designPuncture of soft materialsPuncture simulation

More Related Videos

Author Spotlight: Innovative Microneedle-Based Strategies for Enhanced Exosome Delivery and Stability
07:41

Author Spotlight: Innovative Microneedle-Based Strategies for Enhanced Exosome Delivery and Stability

Published on: July 12, 2024

2.6K
Polymeric Microneedle Array Fabrication by Photolithography
08:15

Polymeric Microneedle Array Fabrication by Photolithography

Published on: November 17, 2015

12.3K

Related Experiment Videos

Last Updated: Sep 16, 2025

Hollow Microneedle-based Sensor for Multiplexed Transdermal Electrochemical Sensing
08:19

Hollow Microneedle-based Sensor for Multiplexed Transdermal Electrochemical Sensing

Published on: June 1, 2012

14.5K
Author Spotlight: Innovative Microneedle-Based Strategies for Enhanced Exosome Delivery and Stability
07:41

Author Spotlight: Innovative Microneedle-Based Strategies for Enhanced Exosome Delivery and Stability

Published on: July 12, 2024

2.6K
Polymeric Microneedle Array Fabrication by Photolithography
08:15

Polymeric Microneedle Array Fabrication by Photolithography

Published on: November 17, 2015

12.3K

Area of Science:

  • Biomedical Engineering
  • Materials Science
  • Nanotechnology

Background:

  • Microneedle arrays are advanced medical tools for drug delivery, tissue adhesion, and neural signal recording.
  • Optimizing microneedle array design requires understanding the influence of geometric features on puncture performance in soft tissues.

Purpose of the Study:

  • To investigate the effects of individual microneedle geometry (diameter, tip angle) on puncture mechanics.
  • To analyze how array-level geometric factors (height difference, spacing, tip angle, diameter) influence the puncture force and efficiency of planar, arrow-shaped, and wave-shaped microneedle arrays.
  • To develop a predictive model for microneedle array puncture force using artificial neural networks.

Main Methods:

  • Puncture experiments were conducted on single microneedles and three types of microneedle arrays (planar, arrow-shaped, wave-shaped).
  • Finite element simulations were employed to complement experimental data.
  • An artificial neural network (ANN) was trained using 152 simulation results to predict puncture force based on geometric parameters.

Main Results:

  • Reducing microneedle diameter and tip angle decreased critical puncture force and depth.
  • Increased spacing between microneedles enhanced both puncture efficiency and peak force across all array types.
  • Height variation significantly impacted peak puncture force in wave-shaped arrays; larger tip angles reduced efficiency, but this was mitigated in array and wave designs.
  • Smaller diameters lowered peak puncture force and improved puncture efficiency for all tested arrays.

Conclusions:

  • Microneedle array geometry, including spacing and individual needle dimensions, critically influences puncture performance.
  • The developed ANN model accurately predicts microneedle array puncture force, offering a valuable tool for design optimization.
  • Findings provide crucial insights for designing more effective microneedle systems for various biomedical applications.