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Mohammad Bameni Moghadam

Researcher at Allameh Tabataba'i University

Publications -  52
Citations -  1043

Mohammad Bameni Moghadam is an academic researcher from Allameh Tabataba'i University. The author has contributed to research in topics: Control chart & Control limits. The author has an hindex of 15, co-authored 47 publications receiving 941 citations.

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Photo induced silver on nano titanium dioxide as an enhanced antimicrobial agent for wool

TL;DR: The treated wool fabrics indicated an antimicrobial activity against both Staphylococcus aureus and Escherichia coli bacteria and the role of both cross-linking agent and nanocomposite concentrations was investigated using response surface methodology (RSM).
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A novel durable flame-retardant cotton fabric using sodium hypophosphite, nano TiO2 and maleic acid

TL;DR: In this article, a novel flame-retardant for woven cotton fabric using sodium hypophosphite (SHP), maleic acid (MA), triethanol amine (TEA), and nano TiO2 through conventional pad-dry-cure method was employed to investigate the thermal decomposition behavior of the treated samples.
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Influence of sericin/TiO2 nanocomposite on cotton fabric: Part 1. Enhanced antibacterial effect

TL;DR: The fabrics treated with nano-TiO2 were possessed more activity against bacteria as compared to sericin and also considerably improved with given nanocomposite, and the antibacterial activity of treated fabrics with cross-linking agents has not been considerably changed after 20 and 40 launderings.
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Nano titanium dioxide on wool keratin as UV absorber stabilized by butane tetra carboxylic acid (BTCA): A statistical prospect

TL;DR: In this article, the protection features of nano-titanium dioxide particles against UV on wool fabric were discussed and the color variations of wool samples after UV irradiation were measured and reported.
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Self-cleaning properties of bleached and cationized cotton using nanoTiO2: A statistical approach

TL;DR: In this article, the self-cleaning properties of bleached and cationized cotton treated by nanoTiO2 (NTO) were compared and optimized using a statistical model.