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Authors = Manik Chandra Biswas ORCID = 0000-0003-3786-2774

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14 pages, 5308 KiB  
Article
Using Sodium Polyacrylate to Gel-Spin Lignin/Poly(Vinyl Alcohol) Fiber at High Lignin Content
by Manik Chandra Biswas and Ericka Ford
Polymers 2022, 14(13), 2736; https://doi.org/10.3390/polym14132736 - 4 Jul 2022
Cited by 4 | Viewed by 3552
Abstract
Lignin is the world’s most naturally abundant aromatic polymer, which makes it a sustainable raw material for engineered polymers and fiber manufacturing. Dry-jet gel-spinning was used to fabricate poly(vinyl alcohol) (PVA) fibers having 30% or more of the lignin biopolymer. To achieve this [...] Read more.
Lignin is the world’s most naturally abundant aromatic polymer, which makes it a sustainable raw material for engineered polymers and fiber manufacturing. Dry-jet gel-spinning was used to fabricate poly(vinyl alcohol) (PVA) fibers having 30% or more of the lignin biopolymer. To achieve this goal, 0.45 wt.% of aqueous sodium polyacrylate (SPA, at 0.55 wt.% solids) was added to spinning dopes of PVA dissolved in dimethylsulfoxide (DMSO). SPA served to enable the spinning of fibers having high lignin content (i.e., above 30%) while eliminating the aging of as-spun gel fiber prior to elevated temperature drawing. SPA impedes the migration of acetone soluble lignin from the skin of as-spun gel fibers, because SPA is insoluble in acetone, which is also a nonsolvent coagulant for PVA. PVA fibers having 30% lignin exhibited the highest tenacity of 1.3 cN/dtex (centinewton/decitex) and specific modulus 35.7 cN/dtex. The drawn fiber of 70% lignin to PVA, showed tenacity and specific modulus values of 0.94 cN/dtex and 35.3 cN/dtex, respectively. Fourier Transform Infrared (FTIR) spectroscopy showed evidence of hydrogen bonding between lignin and PVA among the drawn fibers. The modification of PVA/lignin dopes with SPA, therefore, allowed for the fabrication of gel-spun biobased fibers without the previously required step of gel aging. Full article
(This article belongs to the Special Issue Renewable and Sustainable Polymers)
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34 pages, 2798 KiB  
Review
Fashion Recommendation Systems, Models and Methods: A Review
by Samit Chakraborty, Md. Saiful Hoque, Naimur Rahman Jeem, Manik Chandra Biswas, Deepayan Bardhan and Edgar Lobaton
Informatics 2021, 8(3), 49; https://doi.org/10.3390/informatics8030049 - 26 Jul 2021
Cited by 54 | Viewed by 42544
Abstract
In recent years, the textile and fashion industries have witnessed an enormous amount of growth in fast fashion. On e-commerce platforms, where numerous choices are available, an efficient recommendation system is required to sort, order, and efficiently convey relevant product content or information [...] Read more.
In recent years, the textile and fashion industries have witnessed an enormous amount of growth in fast fashion. On e-commerce platforms, where numerous choices are available, an efficient recommendation system is required to sort, order, and efficiently convey relevant product content or information to users. Image-based fashion recommendation systems (FRSs) have attracted a huge amount of attention from fast fashion retailers as they provide a personalized shopping experience to consumers. With the technological advancements, this branch of artificial intelligence exhibits a tremendous amount of potential in image processing, parsing, classification, and segmentation. Despite its huge potential, the number of academic articles on this topic is limited. The available studies do not provide a rigorous review of fashion recommendation systems and the corresponding filtering techniques. To the best of the authors’ knowledge, this is the first scholarly article to review the state-of-the-art fashion recommendation systems and the corresponding filtering techniques. In addition, this review also explores various potential models that could be implemented to develop fashion recommendation systems in the future. This paper will help researchers, academics, and practitioners who are interested in machine learning, computer vision, and fashion retailing to understand the characteristics of the different fashion recommendation systems. Full article
(This article belongs to the Special Issue Big Data Analytics, AI and Machine Learning in Marketing)
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16 pages, 4657 KiB  
Article
Strengthening Regenerated Cellulose Fibers Sourced from Recycled Cotton T-Shirt Using Glucaric Acid for Antiplasticization
by Manik Chandra Biswas, Ryan Dwyer, Javier Jimenez, Hsun-Cheng Su and Ericka Ford
Polysaccharides 2021, 2(1), 138-153; https://doi.org/10.3390/polysaccharides2010010 - 4 Mar 2021
Cited by 10 | Viewed by 7356
Abstract
The recycling of cellulose from cotton textiles would minimize the use of virgin crop fibers, but recycled polymers are generally inferior in mechanical performance to those made from virgin resins. This challenge prompted the investigation of biobased additives that were capable of improving [...] Read more.
The recycling of cellulose from cotton textiles would minimize the use of virgin crop fibers, but recycled polymers are generally inferior in mechanical performance to those made from virgin resins. This challenge prompted the investigation of biobased additives that were capable of improving the mechanical properties of fibers by means of antiplasticizing additives. In this study, regenerated cellulose (RC) fibers were spun from cellulose found in cotton T-shirts, and fibers were mechanically strengthened with glucaric acid (GA), a nontoxic product of fermentation. The recycled pulp was activated using aqueous sodium hydroxide and then followed by acid neutralization, prior to the direct dissolution in lithium chloride/N,N-dimethylacetamide (LiCl/DMAc) at 3 wt.% cellulose. At 10% (w/w) GA, the tensile modulus and strength of regenerated cellulose from recycled cotton fibers increased five-fold in contrast to neat fibers without GA. The highest modulus and tenacity values of 664 cN/dtex and of 9.7 cN/dtex were reported for RC fibers containing GA. Full article
(This article belongs to the Special Issue (Nano)cellulose: Extraction, Characterizations, Application)
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