Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.6
5.0
Journals
Polymers
Special Issues
Smart Polymeric Fibrous Materials
share announcement

Smart Polymeric Fibrous Materials

A special issue of Polymers (ISSN 2073-4360). This special issue belongs to the section "Smart and Functional Polymers".

Deadline for manuscript submissions: closed (10 October 2022) | Viewed by 6611

Special Issue Editors

Dr. Nesrine Amor

E-Mail Website
Guest Editor
Department of Machinery Construction, Institute for Nanomaterials, Advanced Technologies and Innovation (CXI), Studentská 1402/2, 461 17 Liberec 1, Technical University of Liberec, Liberec, Czech Republic
Interests: textile-based composites; signal processing; sequential monte carlo methods; machine learning; blind source separation; optimization; modeling; data analytics and control systems
Dr. Michal Petrů

E-Mail Website
Guest Editor
Department of Machinery Construction, Institute for Nanomaterials, Advanced Technologies and Innovation (CXI), Technical University of Liberec, Studentská 1402/2, 46117 Liberec 1, Czech Republic
Interests: materials characterization; modeling; optimization; composites; machine design; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Muhammad Tayyab Noman

E-Mail Website
Guest Editor
Department of Machinery Construction, Institute for Nanomaterials, Advanced Technologies and Innovation (CXI), Studentská 1402/2, 461 17 Liberec 1, Technical University of Liberec, Liberec, Czech Republic
Interests: photocatalysis; nanocoating; textile-based composites; polymer composites; materials characterization; surface science; nanofabrication; wastewater treatment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nowadays, smart polymer-based composite materials have gained popularity in different fields, especially textile engineering, thanks to the unique properties and high-performance of composite materials in the development and promotion of smart materials to resolve complex issues in various applications including biosensors, hydrogels, nanocomposites, functional materials, phase change materials, smart coating, self-cleaning, moisture- and thermal-responsive polymer, etc. The nonlinear response of smart polymers is what makes them so unique and effective. Therefore, multifunctional properties including comfort, smart wetting properties, wound monitoring, self-control, self-cleaning or ease of recycling can be delivered to textiles by integrating smart polymers into them, which are critical for the sophisticated modern way of life.

Therefore, this Special Issue will cover recent trends in advanced intelligent polymer composite materials for potential textile topics including, but not limited to: structure, multiple functionalities nanomaterials, smart nanocoating textiles methodologies, mathematical modelling, implementing artificial intelligence methodologies, reinforced textile materials (in composites and polymer composites), synthesis, characterization, and promising smart applications of textile-based polymer composite materials in the textile field.

We invite authors to submit their research results in the form of full-length research articles, review articles, as well as communications and letters on the above-mentioned topics.

Dr. Nesrine Amor
Dr. Michal Petrů
Dr. Muhammad Tayyab Noman
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Polymers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • polymers
  • smart textiles
  • functional textile composites
  • stimuli-responsive polymers
  • cotton
  • polyester
  • nanocoating
  • geopolymer
  • modelling and simulation
  • artificial intelligence

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

19 pages, 50549 KiB  
Article
Chemical Cleaning Process of Polymeric Nanofibrous Membranes
by Aysegul Gul, Jakub Hruza, Lukas Dvorak and Fatma Yalcinkaya
Polymers 2022, 14(6), 1102; https://0-doi-org.brum.beds.ac.uk/10.3390/polym14061102 - 09 Mar 2022
Cited by 5 | Viewed by 3787
Abstract
Membrane fouling is one of the most significant issues to overcome in membrane-based technologies as it causes a decrease in the membrane flux and increases operational costs. This study investigates the effect of common chemical cleaning agents on polymeric nanofibrous membranes (PNM) prepared [...] Read more.
Membrane fouling is one of the most significant issues to overcome in membrane-based technologies as it causes a decrease in the membrane flux and increases operational costs. This study investigates the effect of common chemical cleaning agents on polymeric nanofibrous membranes (PNM) prepared by polyvinylidene fluoride (PVDF), polyacrylonitrile (PAN), and polyamide 6 (PA6) nanofibers. Common alkaline and acid membrane cleaners were selected as the chemical cleaning agents. Membrane surface morphology was investigated. The PAN PNM were selected and fouled by engine oil and then cleaned by the different chemical cleaning agents at various ratios. The SEM results indicated that the use of chemical agents had some effects on the surface of the nanofibrous membranes. Moreover, alkaline cleaning of the fouled membrane using the Triton X 100 surfactant showed a two to five times higher flux recovery than without using a surfactant. Among the tested chemical agents, the highest flux recovery rate was obtained by a binary solution of 5% sodium hydroxide + Triton for alkaline cleaning, and an individual solution of 1% citric acid for acidic cleaning. The results presented here provide one of the first investigations into the chemical cleaning of nanofiber membranes. Full article
(This article belongs to the Special Issue Smart Polymeric Fibrous Materials)
►▼ Show Figures

Graphical abstract

11 pages, 840 KiB  
Article
Use of an Artificial Neural Network for Tensile Strength Prediction of Nano Titanium Dioxide Coated Cotton
by Nesrine Amor, Muhammad Tayyab Noman, Adla Ismail, Michal Petru and Neethu Sebastian
Polymers 2022, 14(5), 937; https://0-doi-org.brum.beds.ac.uk/10.3390/polym14050937 - 26 Feb 2022
Cited by 8 | Viewed by 1856
Abstract
In this study, an artificial neural network (ANN) is used for the prediction of tensile strength of nano titanium dioxide (TiO2) coated cotton. The coating process was performed by ultraviolet (UV) radiations. Later on, a backpropagation ANN algorithm trained with Bayesian [...] Read more.
In this study, an artificial neural network (ANN) is used for the prediction of tensile strength of nano titanium dioxide (TiO2) coated cotton. The coating process was performed by ultraviolet (UV) radiations. Later on, a backpropagation ANN algorithm trained with Bayesian regularization was applied to predict the tensile strength. For a comparative study, ANN results were compared with traditional methods including multiple linear regression (MLR) and polynomial regression analysis (PRA). The input conditions for the experiment were dosage of TiO2, UV irradiation time and temperature of the system. Simulation results elucidated that ANN model provides high performance accuracy than MLR and PRA. In addition, statistical analysis was also performed to check the significance of this study. The results show a strong correlation between predicted and measured tensile strength of nano TiO2-coated cotton with small error values. Full article
(This article belongs to the Special Issue Smart Polymeric Fibrous Materials)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop