Machine learning for property prediction and optimization of polymeric nanocomposites: a state-of-the-art

E Champa-Bujaico, P García-Díaz… - International Journal of …, 2022 - mdpi.com
Recently, the field of polymer nanocomposites has been an area of high scientific and
industrial attention due to noteworthy improvements attained in these materials, arising from …

[HTML][HTML] Advances in machine learning-aided design of reinforced polymer composite and hybrid material systems

CE Okafor, S Iweriolor, OI Ani, S Ahmad, S Mehfuz… - Hybrid Advances, 2023 - Elsevier
Reinforced composite is a preferred choice of material for the design of industrial lightweight
structures. As of late, composite materials analysis and development utilizing machine …

Advances, Synergy, and Perspectives of Machine Learning and Biobased Polymers for Energy, Fuels, and Biochemicals for a Sustainable Future

ADA Bin Abu Sofian, X Sun, VK Gupta… - Energy & …, 2024 - ACS Publications
This review illuminates the pivotal synergy between machine learning (ML) and
biopolymers, spotlighting their combined potential to reshape sustainable energy, fuels, and …

A review on computational intelligence methods for modelling of light weight composite materials

N Amor, MT Noman, M Petru, N Sebastian… - Applied Soft …, 2023 - Elsevier
Light weight composite materials (LWCM) have gained tremendous attention, thanks to their
low cost, eco-friendly nature, biodegradability, life-cycle superiority, noble mechanical …

[HTML][HTML] A perspective on the synergistic use of 3D printing and electrospinning to improve nanomaterials for biomedical applications

O Ejiohuo - Nano Trends, 2023 - Elsevier
Abstract 3D printing and electrospinning are used to fabricate complex structures with
improved properties. Combining 3D printing and electrospinning potentially creates …

Toward the design of graft-type proton exchange membranes with high proton conductivity and low water uptake: A machine learning study

S Sawada, Y Sakamoto, K Funatsu… - Journal of Membrane …, 2024 - Elsevier
Proton conductivity (σ) and hydration number (λ) are important characteristics for proton
exchange membranes (PEMs) in fuel cells and water electrolyzers. A High σ yields high …

Emerging Perspectives on Prime Editor Delivery to the Brain

E BenDavid, S Ramezanian, Y Lu, J Rousseau… - Pharmaceuticals, 2024 - mdpi.com
Prime editing shows potential as a precision genome editing technology, as well as the
potential to advance the development of next-generation nanomedicine for addressing …

Physically soft magnetic films and devices: fabrication, properties, printability, and applications

A Dhamsania, W Mah, A Sivarajan, J Ting… - Journal of Materials …, 2022 - pubs.rsc.org
Developing materials that enable fabricating multifunctional devices has been the
cornerstone of present-day materials science and engineering. Such multi-functionality …

[PDF][PDF] Nanofibers Membrane Loaded with Titanium Oxide and Rifampicin as Controlled Drug Delivery System for Wound Dressing Applications.

DM Jomaa, AK Hussien… - Journal of Composite & …, 2024 - pdfs.semanticscholar.org
Fibroblast proliferation and microbial infection control play a major role in the efficacy of
wound healing. In order to address this, we created dressing membranes by loading …

Development of machine learning regression models for the prediction of tensile strength of friction stir processed AA8090/SiC surface composites

K Adiga, MA Herbert, SS Rao… - Materials Research …, 2024 - iopscience.iop.org
Abstract Friction Stir Processing is a state-of-the-art technology for microstructure refinement,
material property enhancement, and fabrication of surface composites. Machine learning …