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Article
Publication date: 27 February 2023

Ali A. Ali, H. Abd El-Wahab, Moustafa S. Abusaif, Ahmed Ragab, Omar A. Abdel-Jaid, E.A. Eldeeb and Yousry A. Ammar

The paper aims to the preparation of novel disperse dye based on azo salicylaldehyde derivatives TF-A [2-hydroxy-5-((3-(trifluoromethyl)phenyl)diazenyl)benzaldehyde] and full…

206

Abstract

Purpose

The paper aims to the preparation of novel disperse dye based on azo salicylaldehyde derivatives TF-A [2-hydroxy-5-((3-(trifluoromethyl)phenyl)diazenyl)benzaldehyde] and full evaluation of their use as disperse dye TF-ASC [bis 2-hydroxy-5-((3-(trifluoromethyl)phenyl)diazenyl)benzaldehyde Schiff base with 4,4'-methylenedianiline] for dyeing polyester fabric at various conditions.

Design/methodology/approach

The dispersed dye was synthesized via Schiff base condensation in the presence of ceric ammonium nitrate cerium ammonium nitrate 10 mmole% as an eco-friendly catalyst at room temperature. The chemical structure of the prepared dye was characterized via elemental analysis, Fourier-transform infrared spectroscopy, 1H- and 13 C-NMR spectroscopic analysis tools. This study thoroughly examined the dyeing of disperse dye TF-ASC on polyester at various conditions. The characteristics of dyed polyester fabric were measured by colour measurements, as well as light, washing, crock fastness and finally, colour strength. The discrete fourier transform (DFT) theoretical studies, including EHOMO, ELUMO and optimized geometrical structure, were assumed and discussed in detail.

Findings

The results showed that the synthesized organic dye TF-ASC was highly functional and appropriate for this kind of dyeing method. The dyeing fabrics obtained from disperse dye TF-ASC, properties possess high colour strength as well as good overall fastness properties. These dyes had a high affinity for polyester fabric, with just a tiny change in dye affinity when the pH was changed, even under alkaline circumstances. The dye levelness and shade depth of the colour results were good, and there were a variety of hues from light brownish yellow to deep brownish yellow. The results obtained from DFT computational studies such as EHOMO, ELUMO, optimized structure, diploe moment µ and electrophilicity index deduced that prepared organic dye TF-ASC is more applicable as a dispersed dye.

Originality/value

This research is significant because it provides a new dye for dyeing polyethylene terephthalate fibres with exceptional brightness and levelness; the method of preparation is a useful pathway due to its being known as a green chemistry method.

Details

Pigment & Resin Technology, vol. 53 no. 5
Type: Research Article
ISSN: 0369-9420

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Article
Publication date: 19 September 2024

Mohammad Azim Eirgash and Vedat Toğan

Most of the existing time-cost-quality-environmental impact trade-off (TCQET) analysis models have focused on solving a simple project representation without taking typical…

63

Abstract

Purpose

Most of the existing time-cost-quality-environmental impact trade-off (TCQET) analysis models have focused on solving a simple project representation without taking typical activity and project characteristics into account. This study aims to present a novel approach called the “hybrid opposition learning-based Aquila Optimizer” (HOLAO) for optimizing TCQET decisions in generalized construction projects.

Design/methodology/approach

In this paper, a HOLAO algorithm is designed, incorporating the quasi-opposition-based learning (QOBL) and quasi-reflection-based learning (QRBL) strategies in the initial population and generation jumping phases, respectively. The crowded distance rank (CDR) mechanism is utilized to rank the optimal Pareto-front solutions to assist decision-makers (DMs) in achieving a single compromise solution.

Findings

The efficacy of the proposed methodology is evaluated by examining TCQET problems, involving 69 and 290 activities, respectively. Results indicate that the HOLAO provides competitive solutions for TCQET problems in construction projects. It is observed that the algorithm surpasses multiple objective social group optimization (MOSGO), plain Aquila Optimization (AO), QRBL and QOBL algorithms in terms of both number of function evaluations (NFE) and hypervolume (HV) indicator.

Originality/value

This paper introduces a novel concept called hybrid opposition-based learning (HOL), which incorporates two opposition strategies: QOBL as an explorative opposition and QRBL as an exploitative opposition. Achieving an effective balance between exploration and exploitation is crucial for the success of any algorithm. To this end, QOBL and QRBL are developed to ensure a proper equilibrium between the exploration and exploitation phases of the basic AO algorithm. The third contribution is to provide TCQET resource utilizations (construction plans) to evaluate the impact of these resources on the construction project performance.

Details

Engineering Computations, vol. 41 no. 8/9
Type: Research Article
ISSN: 0264-4401

Keywords

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