Green Composites and Their Properties: A Brief Introduction

Green composites are important class of biocomposites widely explored due to their enhanced properties. The biodegradable polymeric material is reinforced with natural fibers to form a composite that is eco-friendly and environment sustainable. The green composites have potential to attract the traditional petroleum-based composites which are toxic and nonbiodegradable. The green composites eliminate the traditional materials such as steel and wood with biodegradable polymer composites. The degradable and environment-friendly green composites were prepared by various fabrication techniques. The various properties of different fiber composite were studied as reinforcement for fully biodegradable and environmental-friendly green composites.

Banana and abaca fiber-reinforced plastic composites obtained by rotational molding process

Natural fibers can be used in rotational molding process to obtain parts with improved mechanical properties. Different approaches have been followed in order to produce formulations containing banana or abaca fiber at 5% weight, in two- and three-layer constructions. Chemically treated abaca fiber has also been studied, causing some problems in processability. Fibers used have been characterized by Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), optical microscopy, and single-fiber mechanical tests. Rotomolded parts have been tested for tensile, flexural, and impact properties, demonstrating that important increases in elastic modulus are achieved with these fibers, although impact properties are reduced. © 2013 Copyright Taylor and Francis Group, LLC.

Glass fibre-reinforced polyethylene composites in rotational moulding

Fibre-reinforced mouldings are of growing interest to the rotational moulding industry due to their outstanding price performance ratio. However, a particular problem that arises when using reinforcements in this process is that the process is low shear and good mixing of resin and reinforcement is not optimum under those conditions. There is also a problem of the larger/heavier reinforcing agents segregating out of the powder to lay up on the inner part surface. In this paper we report on studies to incorporate, short glass fibres into rotationally moulded parts. Four different approaches were investigated; direct addition of fibre in between two powder shots, addition of a layer of pre-compounded polyethylene-glass fibre pellets between two powder shots, addition of a layer of pre-compounded polyethylene-glass fibre powder between two powder shots and a single layer of glass-reinforced, pre-compounded powder. Results indicate that pre-compounding is necessary to gain performance enhancement and the single layer part made from glass-reinforced, pre-compounded powder exhibited the highest tensile and flexural modulus.

Projected equations of motion approach to hybrid quantum/classical dynamics in dielectric-metal composites

We introduce a hybrid method for dielectric-metal composites that describes the dynamics of the metallic system classically whilst retaining a quantum description of the dielectric. The time-dependent dipole moment of the classical system is mimicked by the introduction of projected equations of motion (PEOM) and the coupling between the two systems is achieved through an effective dipole-dipole interaction. To benchmark this method, we model a test system (semiconducting quantum dot-metal nanoparticle hybrid). We begin by examining the energy absorption rate, showing agreement between the PEOM method and the analytical rotating wave approximation (RWA) solution. We then investigate population inversion and show that the PEOM method provides an accurate model for the interaction under ultrashort pulse excitation where the traditional RWA breaks down.

Natural Fibers for the Production of Green Composites

Development of green composite from natural fibers has gained increasing interests due to the environmental and sustainable benefits when compared with petroleum based non-degradable materials. However, a big challenge of green composites is the diversity of fiber sources, because of the large variation in the properties and characteristics of the lignocellulosic renewable resource. The lignocellulosic fibers/natural fibers used to reinforce green composites are reviewed in this chapter. A classification of fiber types and sources, the properties of various natural fibers, including structure, composition, physical and chemical properties are focused; followed by the impacts of natural fibers on composite properties, with identification of the main pathways from the natural fibers to the green composite. Furthermore, the main challenges and future trend of natural fibers are highlighted.

Techno-Economic and Life Cycle Assessment for the Production of Green Composites

Botanically, green composites belong to an economically important seed plant family that includes maize, wheat, rice, and sorghum known as Saccharum offi cinarum. There are so many natural fibers available in the environment such as rice husk, hemp fibers, flax fibers, bamboo fibers, coconut fiber, coconut coir, grawia optiva and many others also. Life Cycle Assessment (LCA) is a process to estimate the environmental feature and potential impacts related to a product, by organizing a directory of pertinent inputs and outputs of a product system, assessing the potential environmental impacts related with the said inputs and outputs, explaining the results of the inventory analysis and impact evaluation phases in connection to the objectives of the study. Particularly Bagasse, an agricultural residue not only becomes a problem from the environmental point of view, but also affects the profitability of the sugarcane industries. This chapter discusses the properties, processing methods and various other aspects including economic and environmental aspects related to green composites.

Modelling the crush behaviour of thermoplastic composites

Thermoplastic composites are likely to emerge as the preferred solution for meeting the high-volume production demands of passenger road vehicles. Substantial effort is currently being directed towards the development of new modelling techniques to reduce the extent of costly and time consuming physical testing. Developing a high-fidelity numerical model to predict the crush behaviour of composite laminates is dependent on the accurate measurement of material properties as well as a thorough understanding of damage mechanisms associated with crush events. This paper details the manufacture, testing and modelling of self-supporting corrugated-shaped thermoplastic composite specimens for crashworthiness assessment. These specimens demonstrated a 57.3% higher specific energy absorption compared to identical specimen made from thermoset composites. The corresponding damage mechanisms were investigated in-situ using digital microscopy and post analysed using Scanning Electron Microscopy (SEM). Splaying and fragmentation modes were the 2 primary failure modes involving fibre breakage, matrix cracking and delamination. A mesoscale composite damage model, with new non-linear shear constitutive laws, which combines a range of novel techniques to accurately capture the material response under crushing, is presented. The force-displacement curves, damage parameter maps and dissipated energy, obtained from the numerical analysis, are shown to be in a good qualitative and quantitative agreement with experimental results. The proposed approach could significantly reduce the extent of physical testing required in the development of crashworthy structures.  

Basalt Fibre Reinforced Polymer Strengthening of Normal Strength Reinforced Concrete Floor Slabs Subject to Arching Effects

With ever increasing demands to strengthen existing reinforced concrete structures to facilitate higher loading due to change of use and to extend service lifetime, the use of fibre reinforced polymers (FRPs) in structural retrofitting offers an opportunity to achieve these aims. To date, most research in this area has focussed on the use of glass fibre reinforced polymer (GFRP) and carbon fibre reinforced polymer (CFRP), with relatively little on the use of basalt fibre reinforced polymer (BFRP) as a suitable strengthening material. In addition, most previous research has been carried out using simply supported elements, which have not considered the beneficial influence of in-plane lateral restraint, as experienced within a framed building structure. Furthermore, by installing FRPs using the near surface mounted (NSM) technique, disturbance to the existing structure can be minimised.
This paper outlines BFRP NSM strengthening of one third scale laterally restrained floor slabs which reflect the inherent insitu compressive membrane action (CMA) in such slabs. The span-to-depth ratios of the test slabs were 20 and 15 and all were constructed with normal strength concrete (~40N/mm2) and 0.15% steel reinforcement. 0.10% BFRP was used in the retrofitted samples, which were compared with unretrofitted control samples. In addition, the bond strength of BFRP bars bonded into concrete was investigated over a range of bond lengths with two different adhesive thicknesses. This involved using an articulated beam arrangement in order to establish optimum bond characteristics for use in strengthening slab samples.

Directed Selection using Reinforcement Learning for the Examination Timetabling Problem

Traditional heuristic approaches to the Examination Timetabling Problem normally utilize a stochastic method during Optimization for the selection of the next examination to be considered for timetabling within the neighbourhood search process. This paper presents a technique whereby the stochastic method has been augmented with information from a weighted list gathered during the initial adaptive construction phase, with the purpose of intelligently directing examination selection. In addition, a Reinforcement Learning technique has been adapted to identify the most effective portions of the weighted list in terms of facilitating the greatest potential for overall solution improvement. The technique is tested against the 2007 International Timetabling Competition datasets with solutions generated within a time frame specified by the competition organizers. The results generated are better than those of the competition winner in seven of the twelve examinations, while being competitive for the remaining five examinations. This paper also shows experimentally how using reinforcement learning has improved upon our previous technique.

Effect of two types of graphene nanoplatelets on the physico–mechanical properties of linear low–density polyethylene composites

The influence of two types of graphene nanoplatelets (GNPs) on the physico-mechanical properties of linear low-density polyethylene (LLDPE) was investigated. The addition of these two types of GNPs – designated as grades C and M – enhanced the thermal conductivity of the LLDPE, with a more pronounced improvement resulting from the M-GNPs compared to C-GNPs. Improvement in electrical conductivity and decomposition temperature was also noticed with the addition of GNPs. In contrast to the thermal conductivity, C-GNPs resulted in greater improvements in the electrical conductivity and thermal decomposition temperature. These differences can be attributed to differences in the surface area and dispersion of the two types of GNPs.