Publication:
Quantifying and Predicting the Tensile Properties of Silicone Reinforced with Moringa oleifera Bark Fibers

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dc.citedby0
dc.contributor.authorAb Patar M.N.A.en_US
dc.contributor.authorManssor N.A.S.en_US
dc.contributor.authorIsa M.R.en_US
dc.contributor.authorJusoh N.A.I.en_US
dc.contributor.authorAbd Latif M.J.en_US
dc.contributor.authorSivasankaran P.N.en_US
dc.contributor.authorMahmud J.en_US
dc.contributor.authorid54394011300en_US
dc.contributor.authorid57196046283en_US
dc.contributor.authorid57193957146en_US
dc.contributor.authorid55793913200en_US
dc.contributor.authorid56136708400en_US
dc.contributor.authorid56183780500en_US
dc.contributor.authorid57200674664en_US
dc.date.accessioned2025-03-03T07:43:37Z
dc.date.available2025-03-03T07:43:37Z
dc.date.issued2024
dc.description.abstractTo obtain a better understanding of using Moringa oleifera bark (MOB) as a reinforcement in a silicone matrix, this study aimed to define the mechanical properties of this new material under uniaxial tension. Composite samples of 0 wt%, 4 wt%, 8 wt%, 12 wt%, and 16 wt% MOB powder were produced. The tensile properties were quantified mathematically using the neo-Hookean hyperelastic model. The collected data were employed to establish multiple inputs of an artificial neural network (ANN) to predict its material constant via MATLAB. The result showed that the material constant for the 16 wt% fiber content sample was 63.9% higher than pure silicone. This was supported by the tensile modulus testing, which indicated that the modulus increased as the fiber content increased. However, the elongation ratio (?) of the MOB-silicone biocomposite decreased slightly compared to the pure silicone. Lastly, the prediction of the material constant using an ANN recorded a 2.03% percentage error, which showed that it was comparable to the mathematical modelling. Therefore, the inclusion of MOB fibers into silicone produced a stiffer material and gradually improved the composite. Furthermore, the network that had multiple inputs (weighting, load, and elongation) was more reliable to produce precise predictions. ? 2024, North Carolina State University. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.15376/biores.19.2.3461-3474
dc.identifier.epage3474
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85191732886
dc.identifier.spage3461
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85191732886&doi=10.15376%2fbiores.19.2.3461-3474&partnerID=40&md5=5507bb206ab72ba28eaea74064a06710
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36645
dc.identifier.volume19
dc.pagecount13
dc.publisherNorth Carolina State Universityen_US
dc.relation.ispartofAll Open Access; Gold Open Access
dc.sourceScopus
dc.sourcetitleBioResources
dc.subjectBark
dc.subjectElasticity
dc.subjectFibers
dc.subjectForecasts
dc.subjectMoringa
dc.subjectNeural Networks
dc.subjectPolysilicones
dc.subjectTensile Properties
dc.subjectElasticity
dc.subjectFibers
dc.subjectForecasting
dc.subjectNeural networks
dc.subjectReinforced plastics
dc.subjectTensile testing
dc.subjectBark fiber
dc.subjectBiocomposite
dc.subjectFibers content
dc.subjectHyperelastic models
dc.subjectMaterials constants
dc.subjectmatrix
dc.subjectMoringa oleifera
dc.subjectMultiple inputs
dc.subjectNeo-hookean hyperelastic model
dc.subjectSilicone biocomposite
dc.subjectSilicones
dc.titleQuantifying and Predicting the Tensile Properties of Silicone Reinforced with Moringa oleifera Bark Fibersen_US
dc.typeReviewen_US
dspace.entity.typePublication
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