Dual-responsive shape memory and self-healing ability of a novel copolymer from epoxy/cashew nut shell liquid and polycaprolactone

2020 ◽  
Vol 81 ◽  
pp. 106159 ◽  
Author(s):  
Narubeth Lorwanishpaisarn ◽  
Pornnapa Kasemsiri ◽  
Kaewta Jetsrisuparb ◽  
Jesper T.N. Knijnenburg ◽  
Salim Hiziroglu ◽  
...  
Keyword(s):  
Shape Memory ◽  
Self Healing ◽  
Cashew Nut Shell Liquid ◽  
Dual Responsive ◽  
Cashew Nut ◽  
Cashew Nut Shell

scholarly journals Self-Healing Ability of Epoxy Vitrimer Nanocomposites Containing Bio-Based Curing Agents and Carbon Nanotubes for Corrosion Protection

2021 ◽  
Author(s):  
Narubeth Lorwanishpaisarn ◽  
Natwat Srik ◽  
Kaewta Jetsrisuparb ◽  
Jesper T.N. Knijnenburg ◽  
Somnuk Theerakulpisut ◽  
...  
Keyword(s):  
Near Infrared ◽  
Thermomechanical Properties ◽  
Self Healing ◽  
Coated Steel ◽  
Cashew Nut Shell Liquid ◽  
Corrosion Properties ◽  
Cashew Nut ◽  
Healing Efficiency ◽  
Curing Agents ◽  
Cashew Nut Shell

Abstract Epoxy is extensively used for anti-corrosion coatings on metallic materials. Conventional epoxy coatings have a permanent crosslink network that is unable to repair itself when cracks and damages occur on the coating layer. This study aims to develop self-healing epoxy vitrimer/carbon nanotube (CNTs) nanocomposite for coating. Two bio-based curing agents viz., cashew nut shell liquid (CNSL) and citric acid (CA) were employed to create covalent adaptable networks. The 0-0.5 wt% CNTs were also incorporated into epoxy/CNSL/CA matrix (V-CNT0-0.5). Based on the results of our study, thermomechanical properties of V-CNT nanocomposites increased with increasing CNTs content. The bond exchange reaction of esterification was thermally activated by near infrared (NIR) light. The V-CNT0.5 showed the highest self-healing efficiency in Shore D hardness of 97.37%. The corrosion resistance of coated steel with V-CNT0 and V-CNT0.5 were observed after immersing the samples in 3.5 wt% NaCl for 7 days. The corrosion rate of coated steel with V-CNT0.5 decreased from 9.53 x 102 MPY to 3.12 x 10-5 MPY whereas an increase in protection efficiency of 99.99% was observed. By taking advantages of the superior self-healing and anti-corrosion properties, V-CNT0.5 could prove to be a desirable organic anti-corrosion coating material.

Particleboard from Cashew Nut Shell Liquid

2007 ◽  
Vol 15 (1) ◽  
pp. 75-82 ◽  
Author(s):  
Lubi C. Mary ◽  
Eby Thomas Thachil
Keyword(s):  
Cashew Nut Shell Liquid ◽  
Cashew Nut ◽  
Cashew Nut Shell

Rheological studies of SBS/EVA blends modified with bio-based cashew nut shell liquid

2021 ◽  
pp. 009524432199040
Author(s):  
Isabela Pinto Ferreira ◽  
Alex da Silva Sirqueira ◽  
Taiane Andre dos Santos ◽  
Monica Feijo Naccache ◽  
Bluma Guenther Soares
Keyword(s):  
Ethylene Vinyl Acetate ◽  
Rheological Parameters ◽  
Creep Recovery ◽  
Cashew Nut Shell Liquid ◽  
Cashew Nut ◽  
Curve Fit ◽  
Significant Difference ◽  
Cashew Nut Shell ◽  
S Model ◽  
Styrene Butadiene

Research on bio-plasticizers is a topic of strategic interest in polymer blends. A bio-plasticizer, cashew nut shell liquid (CNSL), was studied in blends of ethylene-vinyl acetate copolymer (EVA) and styrene-butadiene-styrene copolymer (SBS). In the literature does not report the addition of plasticizers to SBS/EVA blend. Statistical analyses showed that there was a significant difference in mechanical properties (tension at break, hardness and elongation at break) vs. the unplasticized blend. The minimum CNSL concentration required for a statistical difference was 10 phr. The Carreau-Yasuda rheological model was used to obtain rheological parameters in these blends. The plasticizing influence of CNSL was confirmed by rheology. The effects of CNSL on creep and recovery were evaluated for the SBS/EBA blends. Burger´s model explained well SBS/EVA creep compliance. Moreover, its parameters (Newtonian dashpots and Hookean springs) were evaluated as a function of the CNSL concentrations. The bio-plasticizer concentration influenced significant correlations among the rheological creep-recovery tests, thus enabling a considerable increase in the elastic phase. Experimental creep-recovery data and curve fit were in good agreement.

Explorative Investigation on Cashew Nut Shell Liquid Biodiesel blended with Ethanol and Hydrogen in Direct Injection (DI) Diesel Engine and prediction through Artificial Neural Network

2021 ◽  
Author(s):  
Thanigaivelan V ◽  
Lavanya R
Keyword(s):  
Diesel Engine ◽  
Diesel Fuel ◽  
Direct Injection ◽  
Cashew Nut Shell Liquid ◽  
Single Cylinder ◽  
Direct Injection Diesel Engine ◽  
Cashew Nut ◽  
Di Diesel Engine ◽  
Artificial Neural ◽  
Cashew Nut Shell

Abstract Emission from the DI diesel engine is series setback for environment viewpoint. Intended for that investigates for alternative biofuel is persuaded. The important hitches with the utilization of biofuels and their blends in DI diesel engines are higher emanations and inferior brake-thermal efficiency as associated to sole diesel fuel. In this effort, Cashew nut shell liquid (CNSL) biodiesel, hydrogen and ethanol (BHE) mixtures remained verified in a direct-injection diesel engine with single cylinder to examine the performance and discharge features of the engine. The ethanol remained supplemented 5%, 10% and 15% correspondingly through enhanced CNSL as well as hydrogen functioned twin fuel engine. The experiments done in a direct injection diesel engine with single-cylinder at steadystate conditions above the persistent RPM (1500RPM). Throughout the experiment, emissions of pollutants such as fuel consumption rate (SFC), hydrocarbons (HC), carbon monoxide (CO), nitrogen oxides (NOx) and pressure of the fuel were also measured. cylinders. The experimental results show that, compared to diesel fuel, the braking heat of the biodiesel mixture is reduced by 26.79-24% and the BSFC diminutions with growing addition of ethanol from the CNSL hydrogen mixture. The BTE upsurges thru a rise in ethanol proportion with CNSL hydrogen mixtures. Finally, the optimum combination of ethanol with CNSL hydrogen blends led to the reduced levels of HC and CO emissions with trivial upsurge in exhaust gas temperature and NOx emissions. This paper reconnoiters the routine of artificial neural networks (ANN) to envisage recital, ignition and discharges effect.

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