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 Experiment Video

Updated: May 28, 2026

Electrospinning Fundamentals: Optimizing Solution and Apparatus Parameters
07:57

Electrospinning Fundamentals: Optimizing Solution and Apparatus Parameters

Published on: January 21, 2011

Intelligent Optimization of Gas-Assisted Electrospinning via LLM-Guided Bayesian Inference.

Jun Zeng1,2, Rongguang Zhang1, Weicheng Ou3

  • 1State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou 510006, China.

Micromachines
|May 27, 2026
PubMed
Summary

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

3D qtz-Topology COFs With Bicarbazole-Centered Nodes for High-Performance Adsorption of C<sub>6</sub> VOCs.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Zinc homeostasis dysregulation in elderly patients with acute ischemic stroke: a multidimensional analysis integrating metallothionein, FADS1 activity, oxidative stress, and DNA integrity markers.

Frontiers in neurology·2026
Same author

Simulation and Response Surface Methodology for Predicting Mass Transfer in Coaxial Electrospun Core-Shell Fibers.

Micromachines·2026
Same author

High-Uniformity Core-Shell Nanofibers for Semiconductor Packaging: Process Optimization and Performance Study of Airflow-Assisted Coaxial Electrospinning.

Micromachines·2026
Same author

Biomimetic ECM collagen hydrogel induces chondrogenic differentiation of BMSCs by activating autophagy through POU5F1-mediated AMPK/mTOR signaling pathway.

Theranostics·2026
Same author

Hepatocytes functionally reprogrammed by KIAA1199-high colorectal cancer cells favour the accumulation of pro-metastatic Egr1<sup>+</sup> neutrophils.

Nature communications·2026

This study introduces an intelligent framework combining Large Language Models (LLMs) and Bayesian Optimization (BO) to optimize gas-assisted electrospinning for reproducible nanofiber fabrication. The method successfully achieved a minimum fiber diameter of 239 nm, advancing electronic device manufacturing.

Area of Science:

  • Materials Science
  • Nanotechnology
  • Chemical Engineering

Background:

  • Nanofiber structures are promising for semiconductor applications like thin dielectrics and flexible electronics due to tunable morphology.
  • Conventional electrospinning faces challenges in reproducibility and complex parameter control.
  • Achieving precise control over nanofiber diameter and morphology is critical for device performance.

Purpose of the Study:

  • To develop an intelligent optimization framework for gas-assisted electrospinning.
  • To improve the reproducibility and efficiency of nanofiber manufacturing.
  • To identify optimal process parameters for achieving ultra-fine nanofibers.

Main Methods:

  • Integration of Large Language Models (LLMs) with Bayesian Optimization (BO) for process control.
Keywords:
Bayesian optimizationgas-assisted electrospinninglarge language modelnanofiber uniformitysemiconductor manufacturing

More Related Videos

Molecular Entanglement and Electrospinnability of Biopolymers
07:59

Molecular Entanglement and Electrospinnability of Biopolymers

Published on: September 3, 2014

Related Experiment Videos

Last Updated: May 28, 2026

Electrospinning Fundamentals: Optimizing Solution and Apparatus Parameters
07:57

Electrospinning Fundamentals: Optimizing Solution and Apparatus Parameters

Published on: January 21, 2011

Molecular Entanglement and Electrospinnability of Biopolymers
07:59

Molecular Entanglement and Electrospinnability of Biopolymers

Published on: September 3, 2014

  • Utilizing a Gaussian Process Regression (GPR) surrogate model to navigate high-dimensional parameter spaces.
  • Comparative analysis against data-driven BO, knowledge-driven LLM, and Response Surface Methodology (RSM).

    • Main Results:

    • The proposed BO+LLM framework significantly outperformed existing methods in optimization.
    • A verified minimum nanofiber diameter of 239 nm was successfully achieved.
    • Identification of a critical multiphysics collaborative window balancing electrostatic and aerodynamic forces.

    Conclusions:

    • The intelligent BO+LLM framework offers a robust and reproducible pathway for nanofiber fabrication.
    • This approach enhances the manufacturing of advanced nanofiber-based electronic devices.
    • Optimized gas-assisted electrospinning is key to realizing the potential of nanomaterials in electronics.