Study On The Regulation Mechanism Of The Chemical Composition Of Kenaf Fiber On Its Mechanical Properties

Bast fibers have advantageous features such as light-weight,high specific tensile strength and modulus,easy for processing,absorbing CO2 during their growth and easily degradable.These advantages make the bast fibers widely used in the textile and composite areas.The physical properties of natural bast fibers such as chemical composition content,fiber diameter and tensile properties are highly affected by environmental issues such as environmental changes and fiber extraction methods.These irregularities of the bast fibers seriously affect its utilization.The chemical composition of bast fibers include cellulose,hemicellulose,lignin,pectin,wax,hydrotrope,their content varies from the breed,producing area,batch and growth position on the plant.The chemical composition content of fiber determines its mechanical properties.To study the influence of chemical composition of bast fiber to its mechanical properties,the kenaf fiber was chosen as main research object.The chemical composition cellulose,hemicellulose,lignin,pectin,wax and hydrotrope of kenaf fiber were impact factors,and the tensile strength was the result.Grey relational analysis for the chemical composition and fiber properties such as crystallinity,orientation degree,friction coefficient and specific surface area was calculated as supplementary analysis of the relevancy between chemical composition and tensile strength.Finally the Back Propagation neural network which has strong ability of adaptive pattern recognition and nonlinear fitting ability was used to predicting the kenaf fiber tensile strength based on the chemical composition content.The experimental results showed that the chemical composition content of 17 kinds of kenaf content were different,and the chemical composition test results showed good relationship with the test result of FTIR and XPS.Lignin,cellulose,wax,and pectin content showed larger relevancy degree with technical fiber tensile strength,which was 0.71?0.67?0.62?0.61 respectively.Hydrotrope,hemicellulose,lignin and pectin showed larger relevancy degree with fiber bundle tensile strength,which was 0.72?0.67?0.66?0.63 respectively.The GM(1,7)model between kenaf fiber bundle tensile strength and wax,hydrotrope,pectin,hemicellulose,lignin,cellulose was X00(k)+0.69942:(k)=-0.1745X11[(k)+ 0.6953X;(k)+ 0.0854X31(k)-0.3938X41(k)+0.2103X51(k)+ 0.3322X61((K).The BP neural network can predict the tensile strength of kenaf,jute fiber bundle strength accurately.The kenaf fiber bundle tensile strength prediction error was between 1%-5%,the kenaf fiber bundle tensile strength prediction error was between 3%-10%.