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Review
Polymer Science
Abdulhamid Al-Abduljabbar et al.
Summary: This article provides an overall review of electrospun polymer nanofibers (EPNF) and discusses their attractive features, production techniques, polymers used, and properties. The mechanical properties of EPNF are explored, along with other properties such as electrical and chemical properties. The article also highlights the important applications of EPNF in areas such as biomedical engineering, sensors, air filtration, defense, and energy devices. The conclusion summarizes the key findings and suggests directions for future research.
Article
Engineering, Environmental
Mojtaba Malayeri et al.
Summary: Photocatalytic oxidation (PCO) is a promising method for removing volatile organic compounds (VOCs) from indoor environments, but the generation of toxic by-products hinders its widespread use. This study focuses on modeling and optimizing PCO using artificial neural networks and genetic algorithms. The concentrations of target VOCs and by-products are estimated using the ANN model, which considers seven input parameters. The proposed ANN model accurately predicts the concentration of various VOCs and by-products, and multi-objective optimization suggests the optimal conditions for PCO.
CHEMICAL ENGINEERING JOURNAL
(2023)
Review
Chemistry, Multidisciplinary
Shuo Shi et al.
Summary: This research reviewed the progress and applications of multifunctional protective membranes fabricated via electrospinning. It identified gaps in current research and proposed solutions for technological development.
ADVANCED MATERIALS
(2022)
Review
Materials Science, Biomaterials
Fanjin Wang et al.
Summary: Electrohydrodynamic (EHD) processes show promise in healthcare fabrication, and the incorporation of machine learning (ML) is expected to enhance EHD workflows and improve production efficiency.
MATERIALS SCIENCE AND ENGINEERING C-MATERIALS FOR BIOLOGICAL APPLICATIONS
(2022)
Article
Polymer Science
Mingxin Zhang et al.
Summary: The search for higher-quality nanomaterials for medicinal applications is ongoing. Electrospun fibers, which have similarities with natural tissues, have made significant progress in medical applications. Combining nanoparticles and nanofibers in composite materials allows for additional functions, such as photothermal, magnetic response, biosensing, antibacterial, drug delivery, and biosensing. There are two primary ways to prepare nanofiber and nanoparticle hybrids (NNHs): through single-step electrospinning or through the self-assembly technique. This paper focuses on the application of NNHs in drug release, antibacterial effects, and tissue engineering, utilizing biocompatible polymer composites.
Article
Materials Science, Multidisciplinary
Sooyoun Yu et al.
Summary: This study systematically investigated the size- and conformation-dependent piezoelectric properties of polyacrylonitrile (PAN) nanofibers. It was found that the electrospinning process and post-thermal treatment could increase the proportion of the electroactive phase in the nanofibers, leading to a higher piezoelectric charge constant.
ACS APPLIED POLYMER MATERIALS
(2022)
Article
Materials Science, Paper & Wood
Alexandre F. Santos et al.
Summary: In this study, a neural network model was built to predict the aspect ratio of micro/nanofiber products. The model, calibrated based on a limited number of samples, demonstrated high accuracy and robustness in predicting the aspect ratio of materials from different cellulose sources.
Article
Engineering, Chemical
Xizi Xu et al.
Summary: A functionalized porous nanofibrous membrane loaded with MgO nanoparticles was prepared by coaxial electrospinning and post-processing method, and showed high efficiency in removing copper ions from aqueous solutions. The membrane had a larger specific surface area, a more uniform diameter distribution, and surface pores, as well as good mechanical properties and hydrophilicity. The adsorption of copper ions reached equilibrium within 3 hours, with an optimal adsorption pH of 5 and a maximum adsorption capacity of 354 mg/g. The membrane also demonstrated good recycling performance.
SEPARATION AND PURIFICATION TECHNOLOGY
(2022)
Article
Polymer Science
Haoran Liu et al.
Summary: One of the most important trends in electrospinning is to combine itself with traditional materials production and transformation methods to take advantage of the unique properties of nanofibers. In this research, a medicated double-layer hybrid was successfully fabricated using the single-fluid blending electrospinning process combined with the casting film method, providing a dual-phase drug controlled release profile. The hybrid film showed promising potential in developing novel functional materials.
Article
Materials Science, Textiles
Saleh S. Abdelhady et al.
Summary: This study attempted to model the diameter of Poly Lactic-co-Glycolic Acid (PLGA) nanofibers using response surface methodology (RSM) and artificial neural networks (ANNs), aiming to determine the optimal electrospinning process conditions for producing the smallest fiber diameter. The results showed that ANN performed better in predicting nanofiber diameter compared to RSM, and the optimal network structure was determined. The experimental and predicted results demonstrated a strong correlation, indicating the good predictability of the ANN model. The RSM model yielded the optimum combinations for electrospinning PLGA nanofibers that can achieve fine, consistent, and high-quality results.
JOURNAL OF INDUSTRIAL TEXTILES
(2022)
Article
Computer Science, Artificial Intelligence
Danial Jahed Armaghani et al.
Summary: This study investigates the use of artificial intelligence techniques to predict the compressive strength of cement-based mortars. Both ANN and ANFIS models were found to reliably approximate the strength of mortars, with ANFIS outperforming ANN but showing signs of overfitting during verification. The developed ANN model was introduced as the best predictive technique for solving the problem of mortar compressive strength.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Polymer Science
Mookala Premasudha et al.
Summary: This study developed an artificial neural network (ANN) model to predict the diameter and quality classification of polysaccharide-based biopolymer nanofibers, successfully establishing a relationship between process parameters and fiber quality and diameter. Lower feed rate, lower polymer concentration, and higher applied voltage favored the production of smaller diameter fibers with good quality.
JOURNAL OF APPLIED POLYMER SCIENCE
(2021)
Review
Computer Science, Artificial Intelligence
F. Sherwani et al.
Summary: Machine-based classification involves the use of algorithms to accelerate the automated process, which is crucial given the exponential growth in data complexity. This review paper focuses on analyzing deterministic optimization techniques used for machine learning applications, with a particular emphasis on neural networks like BPNN, RNNs, and LM. The study highlights the importance of optimized computational algorithms for efficient classification processes.
EGYPTIAN INFORMATICS JOURNAL
(2021)
Review
Engineering, Environmental
Fan Zhu et al.
Summary: ENFMs, as excellent adsorbents, have high adsorption capacity for heavy metals, with more focus needed on improving stability and mechanical strength for practical applications.
JOURNAL OF HAZARDOUS MATERIALS
(2021)
Article
Materials Science, Multidisciplinary
B. S. Reddy et al.
Summary: Electrospun polycaprolactone (PCL) scaffolds are widely used in tissue engineering applications for their superior biomechanical properties and cell matrix compatibility, with properties depending on electrospinning parameters. This study successfully estimated the properties of PCL scaffolds using artificial neural networks (ANN) technique with high learning precision. The precise predictions demonstrated the model's ability to adequately estimate the relationships between electrospinning parameters and properties of PCL scaffolds.
MATERIALS TODAY COMMUNICATIONS
(2021)
Article
Polymer Science
Pasupuleti Lakshmi Narayana et al.
Summary: An artificial neural networks (ANN) model was developed in this study to predict and analyze polycaprolactone fiber diameter as a function of 3D melt electrospinning process parameters. The developed model showed reasonable accuracy in predicting fiber diameter and revealed the significance of process variables on the fiber diameter. The study established a quantitative relationship between fiber diameter and process variables in a virtual melt spinning system.
JOURNAL OF APPLIED POLYMER SCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Jose de Jesus Rubio
Summary: The article introduces a modified Levenberg-Marquardt algorithm based on Levenberg-Marquardt and Newton algorithms, ensuring error stability and weights boundedness through Lyapunov technique. Comparative studies were conducted with other algorithms for learning electric and brain signal datasets.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Materials Science, Characterization & Testing
Daniela S. de Almeida et al.
Review
Construction & Building Technology
Tanveer Ahmad et al.
SUSTAINABLE CITIES AND SOCIETY
(2020)
Review
Chemistry, Multidisciplinary
Dimitry Papkov et al.
Article
Materials Science, Textiles
Hadi Samadian et al.
JOURNAL OF THE TEXTILE INSTITUTE
(2019)
Article
Chemistry, Multidisciplinary
Seo Yeon Choi et al.
MOLECULAR CRYSTALS AND LIQUID CRYSTALS
(2019)
Article
Materials Science, Textiles
Tahere Khatti et al.
FIBERS AND POLYMERS
(2017)
Article
Chemistry, Multidisciplinary
Nguyen Duy Vinh et al.
APPLIED SCIENCES-BASEL
(2016)
Article
Engineering, Environmental
Wei-Min Chang et al.
CHEMICAL ENGINEERING JOURNAL
(2014)
Article
Polymer Science
Jinmei Du et al.
JOURNAL OF POLYMER SCIENCE PART B-POLYMER PHYSICS
(2008)
Article
Biochemistry & Molecular Biology
Hongliang Jiang et al.
MACROMOLECULAR BIOSCIENCE
(2007)
Article
Polymer Science
Tong Wang et al.
JOURNAL OF APPLIED POLYMER SCIENCE
(2006)
Article
Polymer Science
CS Ki et al.
Article
Polymer Science
SL Zhao et al.
JOURNAL OF APPLIED POLYMER SCIENCE
(2004)
Article
Polymer Science
MM Demir et al.
