Enzyme mimics based on self-assembled peptide functionalized with graphene oxide for polyethylene terephthalate degradation DOI
Xia Li,

Yaoling Zhou,

Jingchao Yue

et al.

Colloids and Surfaces B Biointerfaces, Journal Year: 2025, Volume and Issue: 251, P. 114588 - 114588

Published: Feb. 22, 2025

Language: Английский

Construction of Yarrowia lipolytica for degradation of low-density polyethylene DOI
Fei Liu, Ni Zhang, Yutong Shang

et al.

Process Safety and Environmental Protection, Journal Year: 2025, Volume and Issue: unknown, P. 106818 - 106818

Published: Jan. 1, 2025

Language: Английский

Citations

0

Optimizing Hydrogen Production in the Co-Gasification Process: Comparison of Explainable Regression Models Using Shapley Additive Explanations DOI Creative Commons
Thavavel Vaiyapuri

Entropy, Journal Year: 2025, Volume and Issue: 27(1), P. 83 - 83

Published: Jan. 17, 2025

The co-gasification of biomass and plastic waste offers a promising solution for producing hydrogen-rich syngas, addressing the rising demand cleaner energy. However, optimizing this complex process to maximize hydrogen yield remains challenging, particularly when balancing diverse feedstocks improving efficiency. While machine learning (ML) has shown significant potential in simulating such processes, there is no clear consensus on most effective regression models co-gasification, especially with limited experimental data. Additionally, interpretability these key concern. This study aims bridge gaps through two primary objectives: (1) modeling using seven different ML algorithms, (2) developing framework evaluating model interpretability, ultimately identifying suitable optimization. A comprehensive set experiments was conducted across three dimensions, generalization ability, predictive accuracy, thoroughly assess models. Support Vector Regression (SVR) exhibited superior performance, achieving highest coefficient determination (R2) 0.86. SVR outperformed other capturing non-linear dependencies demonstrated overfitting mitigation. further highlights limitations models, emphasizing importance regularization hyperparameter tuning stability. By integrating Shapley Additive Explanations (SHAP) into evaluation, work first provide detailed insights feature demonstrate operational feasibility industrial-scale production process. findings contribute development robust supporting advancement sustainable energy technologies reduction greenhouse gas (GHG) emissions.

Language: Английский

Citations

0

Advanced Biotechnological Approaches for the Management of Plastic Waste DOI
Lubna Yaqoob, Tayyaba Nооr, Naseem Iqbal

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0

Reliable methodology to determine biotransformation of PBAT in anaerobic conditions DOI Creative Commons
Alba Trueba-Santiso, Reinhard Wimmer,

Mathias Helmer Eskildsen

et al.

Bioresource Technology, Journal Year: 2025, Volume and Issue: unknown, P. 132242 - 132242

Published: Feb. 1, 2025

Language: Английский

Citations

0

Enzyme mimics based on self-assembled peptide functionalized with graphene oxide for polyethylene terephthalate degradation DOI
Xia Li,

Yaoling Zhou,

Jingchao Yue

et al.

Colloids and Surfaces B Biointerfaces, Journal Year: 2025, Volume and Issue: 251, P. 114588 - 114588

Published: Feb. 22, 2025

Language: Английский

Citations

0