The effect of various composite and operating parameters in wear properties of epoxy-based natural fiber composites

Effect of alkali treatment on tensile strength of epoxy composite reinforced with coir fiber

Natural fibers are an increasing potential alternative to synthetic fibers in recent research, due to their unique properties and weight ratio in composite materials. In this work, the banyan mat and ramie mat are used as reinforcement phase and the epoxy polymer is used as matrix material, and granite nanoparticles are used as filler for making composite laminates. The two phases of reinforcing and matrix were taken at an equal ratio of 50% in each, and the conventional hand layup process was fabricated making five different sequences of laminates. In this analysis, the dynamical mechanical properties of this hybrid composite are identified with the erratic weight ratio of banyan mat and ramie mat fabrics. The results revealed the maximum storage modulus is 1580 MPa at 93.8°C and a loss modulus of 298 MPa at 93.8°C in sample A, 12% more storage modulus, 17% more loss modulus was obtained in sample A compared to sample B, and 29% 
 
 
 
 E
 
 
 ′
 
 
 
 and 27% 
 
 
 
 E
 
 
 ″
 
 
 
 more compared to sample E and also using storage modulus, loss modulus, damping factor are the viscoelastic behavior which can reveal the glass transition temperature of hybrid composite laminates by conducting dynamic mechanical analysis, and SEM test was used to identify the failure mode of hybrid composite.

https://downloads.hindawi.com/journals/apt/2022/1560330.pdf

Dynamic Mechanical Analysis of Banyan/Ramie Fibers Reinforced with Nanoparticle Hybrid Polymer Composite

ABSTRACT Eichornia crassipes, ECs is an abundant source of natural fiber, environmentally friendly, and has a great potential to be used as filler in polymer composites. This literature review aims to provide the latest information on ECs synthesis, properties, and ECs-reinforced composites. Modification of the properties of ECs using alkaline chemicals is also discussed in detail through changes in physical, chemical, thermal, and mechanical properties, as well as fiber morphology. After being modified by alkaline chemistry, the fiber density of ECs can be reduced by around 20.69%, and the cellulose content of ECs can reach 90.24%. This literature review also discusses the physical, mechanical, and thermal properties of ECs-filled polymer composites from the results of the latest research and innovations. Polyester reinforced ECs with a length of 10 cm have modulus of elasticity and tensile strength of 11,023.33 N/m2 and 648 N/m2, respectively. Potential applications of ECs composites for product development; cost-effective and efficient replacement of inorganic fillers such as; gypsum, cooling pad, and pulp and paper. This study is expected to be a reference for the development of Eichornia crassipes fiber-filled composite technology for both industry and scientists.

https://doi.org/10.1080/15440478.2022.2162179

A Review on Cellulose Fibers from Eichornia Crassipes: Synthesis, Modification, Properties and Their Composites

The present work is an attempt to model the diameter of Poly Lactic-co-Glycolic Acid (PLGA) nanofibers by utilizing response surface methodology (RSM) and artificial neural networks (ANNs). Hence, determining the optimal electrospinning process conditions to produce a minimum fiber diameter. For modelling the average diameter of nanofibers, RSM approach based on four parameters (polymer concentration, high voltage and needle tip to collector distance and spinning angle) with five-level was compared to ANN technique. In the RSM approach, central composite design (CCD) was used to determine the individual and interaction impacts of the parameters on the average diameter of nanofibers. Several ANNs of single and double hidden layers with different number of cells for each were tried to obtain the best network structure. The experimental and predicted PLGA fiber diameters using an ANN showed a strong correlation, indicating that the network topology of 4-14-1 has good predictability for analyzing factors impacting PLGA fiber diameter. The average absolute relative error for predicting PLGA nanofibers’ diameter using ANN (2.24%) is slightly less than that obtained from RSM (2.59%). The high regression coefficient between the variables and the response (R2 = 0.9636) shows a good second-order polynomial regression model for evaluating experimental data. The R2 value was 0.945, indicating that the ANN model was good fitting with the experimental results. The optimum combinations (PLGA concentration of 26 wt.%, high voltage 22 kV, needle tip to collector distance 20 cm, and spinning angle 60o) were developed by RSM model for electrospinning PLGA nanofiber that can produce fine, consistent, and high-quality nanofibers.

Modeling electrospun PLGA nanofibers’ diameter using response surface methodology and artificial neural networks

In this experimentation hybrid composites using natural fibers and titanium oxide (TiO2) nano filler were fabricated using compression moulding technique. Pineapple (P) and Sisal (S) fibers were us...

KR Sumesh

Papers

The influence of different parameters in tribological characteristics of pineapple/sisal/TiO2 filler incorporation: