[HTML][HTML] A review of computational approaches used in the modelling, design, and manufacturing of biodegradable and biobased polymers

BG Laycock, CM Chan, PJ Halley - Progress in Polymer Science, 2024 - Elsevier
The design and manufacture of new biodegradable and bioderived polymeric materials has
traditionally taken place through experimentation and material characterisation. However …

An overview on wound dressings and sutures fabricated by electrospinning

R Mohamadinooripoor, S Kashanian… - Biotechnology and …, 2023 - Springer
Electrospinning is simple and cost-effective technique for micro/nano-fibers production that
have emerged recently. Electrospun fibers have a wide variety of applications. They can …

Modeling the relationship between forward osmosis process parameters and permeate flux

BS Reddy, AK Maurya, PL Narayana, SA Kori… - Separation and …, 2022 - Elsevier
Artificial neural networks (ANN) models are becoming more popular than mathematical and
transport-based models due to their high performance and accuracy. Previous literature …

Machine learning applications for electrospun nanofibers: a review

B Subeshan, A Atayo, E Asmatulu - Journal of Materials Science, 2024 - Springer
Electrospun nanofibers have gained prominence as a versatile material, with applications
spanning tissue engineering, drug delivery, energy storage, filtration, sensors, and textiles …

The effects of electrospinning structure on the ion conductivity of PEO-based polymer solid-state electrolytes

Q Sun, Z Liu, P Zhu, J Liu, S Shang - Energies, 2023 - mdpi.com
To overcome the safety hazard of the liquid electrolytes used in traditional lithium batteries,
solid electrolytes have drawn more attention because of their advantages such as non …

Application of artificial neural network and full factorial method to predict the Poisson's ratio of double core helical auxetic yarn

M Razbin, MJ Avanaki, AAA Jeddi - The Journal of the Textile …, 2023 - Taylor & Francis
In this work, an experiment according to the full factorial method (FFM) to investigate the
effect of initial helical angle of wrap component, diameter ratio of components and modulus …

Analysis and prediction of electrospun nanofiber diameter based on artificial neural network

M Ma, H Zhou, S Gao, N Li, W Guo, Z Dai - Polymers, 2023 - mdpi.com
Electrospinning technology enables the fabrication of electrospun nanofibers with
exceptional properties, which are highly influenced by their diameter. This work focuses on …

Machine learning to empower electrohydrodynamic processing

F Wang, M Elbadawi, SL Tsilova, S Gaisford… - Materials Science and …, 2022 - Elsevier
Electrohydrodynamic (EHD) processes are promising healthcare fabrication technologies,
as evidenced by the number of commercialised and food-and-drug administration (FDA) …

Development of artificial neural networks software for arsenic adsorption from an aqueous environment

AK Maurya, M Nagamani, SW Kang, JT Yeom… - Environmental …, 2022 - Elsevier
Arsenic contamination is a global problem, as it affects the health of millions of people. For
this study, data-driven artificial neural network (ANN) software was developed to predict and …

Correlating the 3D melt electrospun polycaprolactone fiber diameter and process parameters using neural networks

P Lakshmi Narayana, XS Wang… - Journal of Applied …, 2021 - Wiley Online Library
In the present work, we developed an artificial neural networks (ANN) model to predict and
analyze the polycaprolactone fiber diameter as a function of 3D melt electrospinning …