Studies on the fracture behaviour of polymer blends with special reference to PP/HDPE and PS/HIPS blends

Investigations on the fracture behaviour of polymer blends is the topic of this thesis. The blends selected are PP/HDPE and PS/HIPS. PP/HDPE blend is chosen due to its commercial importance and PS/HIPS blend is selected to study the transition from brittle fracture to ductile fracture.PP/HDPE blends were prepared at different compositions by melt blending at 180°C and fracture failure process was investigated by conducting notch sensitivity test and tensile test at different strain rates. The effects of two types of modifiers (particulate and elastomer) on the fracture behaviour and notch sensitivity of PP/HDPE blends were studied. The modifiers used are calcium carbonate, a hard particulate filler commonly used in plastics and Ethylene Propylene Diene Monomer (EPDM). They were added in 2%, 4% and 6% by weight of the blends.The study shows that the mechanical properties of PP/HDPE blends can be optimized by selecting proper blend compositions. The selected modifiers are found to alter and improve the fracture behaviour and notch sensitivity of the blends. Particulate fillers like calcium carbonate can be used for making the mechanical behaviour more stable at the various blend compositions. The resistance to notch sensitivity of the blends is found to be marginally lower in the presence of calcium carbonate. The elastomeric modifier EPDM produces a better stability of the mechanical behaviour. A low concentration of EPDM is sufficient to effect such a change. EPDM significantly improves the resistance to notch sensitivity of the blends. The study shows that judicious selection of modifiers can improve the fracture behaviour and notch sensitivity of PP/HDPE blends and help these materials to be used for critical applications.For investigating the transition in fracture behaviour and failure modes, PS/HIPS blends were selected. The blends were prepared by melt mixing followed by injection moulding to prepare the specimens for conducting tensile, impact and flexure tests. These tests were used to simulate the various conditions which promote failure.The tensile behaviour of unnotched and notched PS/HIPS blend samples were evaluated at slow speeds. Tensile strengths and moduli were found to increase at the higher testing speed for all the blend combinations whereas maximum strain at break was found to decrease. For a particular speed of testing, the tensile strength and modulus show only a very slight decrease as HIPS content is increased up to about 40%. However, there is a drastic decrease on increasing the HIPS content thereafter.The maximum strain at break shows only a very slight change up to about 40% HIPS content and thereafter shows a remarkable increase. The notched specimens also follow a comparable trend even though the notch sensitivity is seen high for PS rich blends containing up to 40% HIPS. The notch sensitivity marginally decreases with increase in HIPS content. At the same time, it is found to increase with the increase in strain rate. It is observed that blends containing more than 40% HIPS fail in ductile mode.The impact characteristics of PSIHIPS blends studied were impact strength, the energy absorbed by the test specimen and impact toughness. Remarkable increase in impact strength is observed as HIPS content in the blend exceeds 40%. The energy absorbed by the test specimens and the impact toughness also show a comparable trend.Flexural testing which helps to characterize the load bearing capacity was conducted on PS/HIPS blend samples at the two different testing speeds of 5mmlmin and 10 mm/min. The flexural strength increases with increase in testing speed for all the blend compositions. At both the speeds, remarkable reduction in flexural strength is observed as HIPS content in the blend exceeds 40%. The flexural strain and flexural energy absorbed by the specimens are found to increase with increase in HIPS content. At both the testing speeds, brittle fracture is observed for PS rich blends whereas HIPS rich blends show ductile mode of failure.Photoelastic investigations were conducted on PS/HIPS blend samples to analyze their failure modes. A plane polariscope with a broad source of light was utilized for the study. The coloured isochromatic fringes formed indicate the presence of residual stress concentration in the blend samples. The coverage made by the fringes on the test specimens varies with the blend composition and it shows a reducing trend with the increase in HIPS content. This indicates that the presence of residual stress is a contributing factor leading to brittle fracture in PS rich blends and this tendency gradually falls with increase in HIPS content and leads to their ductile mode of failure.

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.