Modeling of the electrospinning process using rheological and physical chemistry approaches and enhancement of electrospun mats

Abstract Fiber diameter and defect-free morphology, particularly the suppression of bead formation, are critical to the performance of electrospun fibers. This study employs complementary physicochemical and rheological approaches to predict fiber morphology using poly(butylene succinate) (PBS) dissolved in a DMF–chloroform solvent blend, with poly(methyl methacrylate) (PMMA) incorporated in selected samples. Guided by Colby’s theory, specific viscosity measurements identified 6.067 % PBS as the minimum concentration for fiber formation and 21 % PBS as the concentration producing uniform, defect-free fibers, while the critical entanglement concentration (Ce) was determined from specific viscosity. From a rheological perspective, the interactions among electrical, elastic, and capillary forces were analyzed using Feng’s Slender Body model, which yielded results consistent with Yu and Fridrikh’s formulations while avoiding reliance on imaging-derived jet parameters. The specific-viscosity-based approach provided predictions with relatively low error margins of approximately 2–5 % compared with more complex rheological methods. Although the model slightly overestimated fiber morphology parameters, it provides a practical approach for predicting electrospinning outcomes and defect formation.

Authors

Institutions

Publication Details

Journal
International Polymer Processing
Published
2026-10-30
DOI
https://doi.org/10.1515/ipp-2026-0047
Primary Topic
Electrospun Nanofibers in Biomedical Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling of the electrospinning process using rheological and physical chemistry approaches and enhancement of electrospun mats

Hadi Shirali, Mehdi Rafizadeh, Barman Abdali
International Polymer Processing
Electrospun Nanofibers in Biomedical Applications
article

Modeling of the electrospinning process using rheological and physical chemistry approaches and enhancement of electrospun mats

Hadi Shirali, Mehdi Rafizadeh, Barman Abdali
article en

Abstract

Abstract Fiber diameter and defect-free morphology, particularly the suppression of bead formation, are critical to the performance of electrospun fibers. This study employs complementary physicochemical and rheological approaches to predict fiber morphology using poly(butylene succinate) (PBS) dissolved in a DMF–chloroform solvent blend, with poly(methyl methacrylate) (PMMA) incorporated in selected samples. Guided by Colby’s theory, specific viscosity measurements identified 6.067 % PBS as the minimum concentration for fiber formation and 21 % PBS as the concentration producing uniform, defect-free fibers, while the critical entanglement concentration (Ce) was determined from specific viscosity. From a rheological perspective, the interactions among electrical, elastic, and capillary forces were analyzed using Feng’s Slender Body model, which yielded results consistent with Yu and Fridrikh’s formulations while avoiding reliance on imaging-derived jet parameters. The specific-viscosity-based approach provided predictions with relatively low error margins of approximately 2–5 % compared with more complex rheological methods. Although the model slightly overestimated fiber morphology parameters, it provides a practical approach for predicting electrospinning outcomes and defect formation.

International Polymer Processing
Amirkabir University of Technology (IR)
Openalex Percentile: Top 28%
Electrospun Nanofibers in Biomedical Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon