Modeling electrospun nanofibers: An overview from theoretical, empirical, and numerical approaches
Electrospinning is a sophisticated material process to manufacture well-tailored nanofibers for fiber reinforcement, tissue scaffolding, drug delivery, nanofiltration, cosmetics, and protective clothing. Abundant information and knowledge are reported from experimental observation and material chara...
| Main Authors: | , , |
|---|---|
| Format: | Journal Article |
| Published: |
Taylor & Francis
2016
|
| Online Access: | http://hdl.handle.net/20.500.11937/44751 |
| _version_ | 1848757091285598208 |
|---|---|
| author | Mohammadzadehmoghadam, S. Dong, Yu Davies, I. |
| author_facet | Mohammadzadehmoghadam, S. Dong, Yu Davies, I. |
| author_sort | Mohammadzadehmoghadam, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Electrospinning is a sophisticated material process to manufacture well-tailored nanofibers for fiber reinforcement, tissue scaffolding, drug delivery, nanofiltration, cosmetics, and protective clothing. Abundant information and knowledge are reported from experimental observation and material characterization to determine and control nanofiber properties. However, experimental results need to be interpreted systematically through theoretical, analytical, and numerical models for the optimization of fiber diameter and alignment, porosity, and estimation of mechanical properties of electrospun nanofibers. This paper provides a comprehensive review on current status of modeling approaches used in electrospun nanofibers to elucidate their systematic research approaches including material fabrication, experimental characterization, and modeling. |
| first_indexed | 2025-11-14T09:22:35Z |
| format | Journal Article |
| id | curtin-20.500.11937-44751 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:22:35Z |
| publishDate | 2016 |
| publisher | Taylor & Francis |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-447512017-09-13T15:41:03Z Modeling electrospun nanofibers: An overview from theoretical, empirical, and numerical approaches Mohammadzadehmoghadam, S. Dong, Yu Davies, I. Electrospinning is a sophisticated material process to manufacture well-tailored nanofibers for fiber reinforcement, tissue scaffolding, drug delivery, nanofiltration, cosmetics, and protective clothing. Abundant information and knowledge are reported from experimental observation and material characterization to determine and control nanofiber properties. However, experimental results need to be interpreted systematically through theoretical, analytical, and numerical models for the optimization of fiber diameter and alignment, porosity, and estimation of mechanical properties of electrospun nanofibers. This paper provides a comprehensive review on current status of modeling approaches used in electrospun nanofibers to elucidate their systematic research approaches including material fabrication, experimental characterization, and modeling. 2016 Journal Article http://hdl.handle.net/20.500.11937/44751 10.1080/00914037.2016.1180617 Taylor & Francis fulltext |
| spellingShingle | Mohammadzadehmoghadam, S. Dong, Yu Davies, I. Modeling electrospun nanofibers: An overview from theoretical, empirical, and numerical approaches |
| title | Modeling electrospun nanofibers: An overview from theoretical, empirical, and numerical approaches |
| title_full | Modeling electrospun nanofibers: An overview from theoretical, empirical, and numerical approaches |
| title_fullStr | Modeling electrospun nanofibers: An overview from theoretical, empirical, and numerical approaches |
| title_full_unstemmed | Modeling electrospun nanofibers: An overview from theoretical, empirical, and numerical approaches |
| title_short | Modeling electrospun nanofibers: An overview from theoretical, empirical, and numerical approaches |
| title_sort | modeling electrospun nanofibers: an overview from theoretical, empirical, and numerical approaches |
| url | http://hdl.handle.net/20.500.11937/44751 |