Browsing by Author "Siddiqa, Fahmida"

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Adsorption Kinetics of Curcumin on Cotton Fabric
(Tekstilec, 2018-05) Haque, Abu Naser Md. Ahsanul; Hussain, Manwar; Siddiqa, Fahmida; Haque, Md. Mahbubul; Islam, G M Nazmul
The adsorption kinetics study of curcumin on a cotton fabric was investigated at three different temperatures at neutral pH with 1:20 material liquid ratio and 1 g/L initial dye concentration. Pseudo first-order and pseudo second-order kinetics were approached to experimental data and the adsorption kinetics of curcumin on cotton fitted well with the pseudo second-order kinetic model. The activation energy was 71.96 kJ/ mol, whereas enthalpy and entropy were 68.99 kJ/mol and –59.7 J/mol K, respectively. Dye adsorption declined with increasing temperature, which suggests that the process is exothermic and the negative value of entropy indicates the presence of interaction between the adsorbent and adsorbate.
Effect of Elastane and Thread Density on Mechanical Attributes of Stretch Woven Fabric
(AATCC Journal of Research, 2020-01-01) Siddiqa, Fahmida; Haque, Md; Smriti, Mahbubul; Akter, Shamima; Farzana, Nawshin; Haque, Ahsanul; Naser, Md Abu
Stretch woven fabrics continue to grow in popularity, offering superior elastic properties and comfort. However, there are a number of factors (e.g., elongation, recovery, growth, tensile strength, tearing strength, and shrinkage) that can affect the attributes and performance of stretch woven fabric. These were investigated in the present study in relation to different elastane content and thread density. Blended cotton woven fabrics containing an increased elastane content gave enhanced elongation and recovery, despite a decrease in thread density. The tensile strength, tearing strength, shrinkage, and fabric growth decreased when the elastane ratio increased, regardless of the decline in warp thread density.
Fuzzy Modelling for Prediction of Bursting Strength of Knitted Cotton Fabric Using Bleaching Process Variables
(AATCC Journal of Research, 2019-01-01) Haque, Abu Naser Md. Ahsanul; Smriti, Shamima Akter; Farzana, Nawshin; Siddiqa, Fahmida; Islam, Md. Azharul
A fuzzy prediction model has been built based on hydrogen peroxide concentration, bleaching temperature, and time of bleaching as the input variables and knitted cotton fabric bursting strength as the output variable. Fuzzy expert systems can map efficiently in nonlinear domains with minimal experimental data. The model developed in the present study has been validated by new experimental data. The root means square, mean absolute error percentage, and coefficient of determination (R 2) between the predicted and experimental values were found to be 4.89, 0.707, and 0.965 respectively. The results confirm that the model can be applied successfully for the prediction of fabric bursting strength in textile dye houses.
Kinetic Study of Curcumin on Modal Fabric.
(EBSCO Industries, 2018-03) Akter, Smriti Shamima; Haque, Abu Naser Md. Ahsanul; Hussain, Manwar; Smriti, Shamima akter; Siddiqa, Fahmida; Farzana, Nawshin
A kinetic study of curcumin on modal fabric was carried out using an initial dye concentration of 1 g/L at three different temperatures, 70 °C, 85 °C and 100 °C, at pH 7 and an material to liquor ratio of 1:20. Pseudo first-order and pseudo second-order kinetics were applied, and it was found that the adsorption kinetics of curcumin on modal fabric matched the pseudo second-order kinetic model. The activation energy was found to be equal to 71.14 kJ/mol, while the enthalpy and entropy of activation were 68.16 kJ/mol and -66.02 J/molK respectively.
Prediction of whiteness index of cotton using bleaching process variables by fuzzy inference system
(2018-02-28) Naser, Abu; Haque, Md. Ahsanul; Smriti, Shamima Akter; Hussain, Manwar; Farzana, Nawshin; Siddiqa, Fahmida; Islam, Md. Azharul
A fuzzy prediction model has been built based on hydrogen peroxide concentration, temperature and time of bleaching as the input variables and knitted fabric whiteness index as the output variable. The process parameters affecting the whiteness index of cotton knitted fabrics are very non-linear. Fuzzy inference system is a prospective modeling tool as it can map effectively in nonlinear domain with minimum investigational data. Triangular-shaped membership functions were considered for the variables and total 48 rules were created in this study. It was found that the sole effect of the concentration of hydrogen peroxide on whiteness is pretty low, but is affected by temperature noticeably even in a fixed concentration of hydrogen peroxide. The model proposed in the present study has been verified by additional experimental data set. The root mean square, mean absolute error percentage and coefficient of determination (R 2 ) between the predicted and experimental values were found to be 0.536, 0.798 and 0.959 respectively. The results validate that the model can be applied suitably for the prediction of fabric whiteness index in textile industries.