Corrosion Inhibition with Green Polymer Systems and Natural Compounds DOI
Andrey Ivankin,

G. L. Oliferenko

Polymer Science Series D, Journal Year: 2024, Volume and Issue: 17(4), P. 982 - 989

Published: Dec. 1, 2024

Language: Английский

Machine Learning-Based Process Optimization in Biopolymer Manufacturing: A Review DOI Open Access
Ivan Malashin,

D. A. Martysyuk,

В С Тынченко

et al.

Polymers, Journal Year: 2024, Volume and Issue: 16(23), P. 3368 - 3368

Published: Nov. 29, 2024

The integration of machine learning (ML) into material manufacturing has driven advancements in optimizing biopolymer production processes. ML techniques, applied across various stages production, enable the analysis complex data generated throughout identifying patterns and insights not easily observed through traditional methods. As sustainable alternatives to petrochemical-based plastics, biopolymers present unique challenges due their reliance on variable bio-based feedstocks processing conditions. This review systematically summarizes current applications techniques aiming provide a comprehensive reference for future research while highlighting potential enhance efficiency, reduce costs, improve product quality. also shows role algorithms, including supervised, unsupervised, deep

Language: Английский

Citations

4

Corrosion Inhibition with Green Polymer Systems and Natural Compounds DOI
Andrey Ivankin,

G. L. Oliferenko

Polymer Science Series D, Journal Year: 2024, Volume and Issue: 17(4), P. 982 - 989

Published: Dec. 1, 2024

Language: Английский

Citations

0