naebe-towardspredictingthepiezoelectricity-2018.pdf (1.68 MB)
Towards predicting the piezoelectricity and physiochemical properties of the electrospun P(VDF-TrFE) nanogenrators using an artificial neural network
journal contribution
posted on 2018-04-01, 00:00 authored by M M Abolhasani, K Shirvanimoghaddam, H Khayyam, S M Moosavi, Nima Zohdi, Minoo NaebeMinoo NaebeElectrospun P(VDF-TrFE) nanogenrators with a wide range of piezoelectricity performance and physiochemical properties is fabricated through modification of the processing parameters such as polymer concentration, applied voltage, feed rate and electrospinning time/fibres mat thickness. In order to estimate and predict the relationships of the process parameters with the piezoelectricity performance and fibres morphology, an Artificial Neural Networks (ANN) model is developed. Results of the developed ANN model is found to be in a good agreement with experimental results with less than 5% error and shows the good potential to model physiochemical properties of the nanogenrators to predict untested conditions.
History
Journal
Polymer TestingVolume
66Pagination
178 - 188Publisher
ElsevierLocation
London, Eng.Publisher DOI
Link to full text
ISSN
0142-9418eISSN
1873-2348Language
engPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2018, ElsevierUsage metrics
Keywords
nanogeneratorpiezoelectricityartificial neural networknanofibreScience & TechnologyTechnologyPhysical SciencesMaterials Science, Characterization & TestingPolymer ScienceMaterials ScienceRESPONSE-SURFACE METHODOLOGYSTRENGTHENING MECHANISMSFERROELECTRIC PROPERTIESNANOFIBER DIAMETERPROCESS PARAMETERSPOLYMER MELTSOPTIMIZATIONPERFORMANCEMORPHOLOGYPRECURSORMechanical Engineering
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC