[HTML][HTML] 3D printing of biodegradable polymers and their composites–Current state-of-the-art, properties, applications, and machine learning for potential future …

SAV Dananjaya, VS Chevali, JP Dear, P Potluri… - Progress in Materials …, 2024 - Elsevier
This review paper comprehensively examines the dynamic landscape of 3D printing and
Machine Learning utilizing biodegradable polymers and their composites, presenting a …

Applications of artificial intelligence and machine learning on critical materials used in cosmetics and personal care formulation design

H **n, AS Virk, SS Virk, F Akin-Ige, S Amin - Current opinion in colloid & …, 2024 - Elsevier
The applications of Artificial intelligence (AI) and machine learning (ML) approaches are
rising in formula optimization, ingredients selection, performance prediction, and structure …

Antifouling polymers for nanomedicine and surfaces: recent advances

YJ Eng, TM Nguyen, HK Luo, JMW Chan - Nanoscale, 2023 - pubs.rsc.org
Antifouling polymers are materials that can resist nonspecific interactions with cells, proteins,
and other biomolecules. Typically, they are hydrophilic polymers with polar or charged …

Perspective: Machine learning in design for 3D/4D printing

X Sun, K Zhou, F Demoly… - Journal of Applied …, 2024 - asmedigitalcollection.asme.org
Abstract 3D/4D printing offers significant flexibility in manufacturing complex structures with
a diverse range of mechanical responses, while also posing critical needs in tackling …

Advances in Injectable Polymeric Biomaterials and Their Contemporary Medical Practices

S Beilharz, MK Debnath, D Vinella… - ACS Applied Bio …, 2024 - ACS Publications
Injectable biomaterials have been engineered to operate within the human body, offering
versatile solutions for minimally invasive therapies and meeting several stringent …

Intelligent materials and nanomaterials improving physical properties and control oriented on electronic implementations

A Massaro - Electronics, 2023 - mdpi.com
The review highlights possible research topics matching the experimental physics of matter
with advances in electronics to improve the intelligent design and control of innovative smart …

Polymer reaction engineering meets explainable machine learning

J Fiosina, P Sievers, M Drache, S Beuermann - Computers & Chemical …, 2023 - Elsevier
Due to the complex polymerization technique and statistical composition of the polymer,
tailoring its characteristics is a challenging task. Modeling of the polymerizations can …

Machine Learning-Based High-Throughput Screening for High-Stability Polyimides

G Luo, F Huan, Y Sun, F Shi, S Deng… - Industrial & Engineering …, 2024 - ACS Publications
High-stability polyimides exhibit tremendous potential for applications in flexible electronics,
fibers, and membrane materials. However, screening polyimide structures with superior …

Advancing flame retardant prediction: A self-enforcing machine learning approach for small datasets

C Yan, X Lin, X Feng, H Yang, P Mensah… - Applied Physics Letters, 2023 - pubs.aip.org
Improving the fireproof performance of polymers is crucial for ensuring human safety and
enabling future space colonization. However, the complexity of the mechanisms for flame …

Analysis of electrochemical impedance data: use of deep neural networks

D Doonyapisut, PK Kannan, B Kim… - Advanced Intelligent …, 2023 - Wiley Online Library
Technology advancements in energy storage, photocatalysis, and sensors have generated
enormous impedimetric data. Electrochemical impedance spectroscopy (EIS) results play an …