Machine learning for revealing the relationship between the process–structure–properties of polypropylene in-reactor alloys DOI Creative Commons
Zheng Shaojie, Xu Huang, Jijiang Hu

et al.

Reaction Chemistry & Engineering, Journal Year: 2024, Volume and Issue: 9(6), P. 1354 - 1363

Published: Jan. 1, 2024

Polypropylene reactor alloys with distinct structures were synthesized, and machine learning models developed to reveal the relationship between process–structure–properties optimize process conditions.

Language: Английский

ANN model-based estimation of ash agglomeration temperature in fluidised bed gasification using ash composition DOI

Vinayak S. Jayapal,

P. Suraj,

Melbin Benny

et al.

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
A novel waste-to-energy conversion plant based on catalytic pyrolytic conditions: Modeling and Optimization Using Supervised Machine Learning and Desirability-Driven Methodologies DOI
Aqueel Ahmad, Ashok Kumar Yadav,

Shifa Hasan

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134648 - 134648

Published: Jan. 1, 2025

Language: Английский

Citations

0
Enhancing plastic pyrolysis for carbon nanotubes synthesis through machine learning integration: A review DOI

K. Loke,

Xuan Han Lim,

M.A. Osman

et al.

Journal of Analytical and Applied Pyrolysis, Journal Year: 2025, Volume and Issue: unknown, P. 106989 - 106989

Published: Jan. 1, 2025

Language: Английский

Citations

0
Investigation of the characteristics of microwave-assisted co-pyrolysis of biomass and waste plastics based on orthogonal experimental methods: Thermal degradation, kinetics and product distribution DOI

Teng Wen,

Zhaosheng Yu, Shen Gao

et al.

Journal of Analytical and Applied Pyrolysis, Journal Year: 2025, Volume and Issue: unknown, P. 107083 - 107083

Published: March 1, 2025

Language: Английский

Citations

0
Valorizing disposable face masks into non-condensable hydrocarbon gases via optimal reactor configurations in thermal pyrolysis DOI Open Access

Kai Qi Tan,

Wen‐Da Oh, Mohd Azmier Ahmad

et al.

Journal of Analytical and Applied Pyrolysis, Journal Year: 2023, Volume and Issue: 175, P. 106164 - 106164

Published: Sept. 9, 2023

Language: Английский

Citations

5
Microwaves assisted deconstruction of HDPE waste into structured carbon and hydrogen fuel using Al2O3-(Ni, Zn, Mg)Fe2O4 composite catalysts DOI

Bilal Shoukat,

Hammad Hussain,

Muhammad Yasin Naz

et al.

Thermal Science and Engineering Progress, Journal Year: 2023, Volume and Issue: 47, P. 102368 - 102368

Published: Dec. 28, 2023

Language: Английский

Citations

5
Interaction of Mustard Husk with microwave radiation: A study on dielectric properties and its variation with frequency DOI Open Access
Akanksha Verma, Manoj Tripathi

Journal of Analytical and Applied Pyrolysis, Journal Year: 2023, Volume and Issue: 173, P. 106090 - 106090

Published: July 22, 2023

Language: Английский

Citations

4
Synergistic valorization of wheat husk-derived HZSM-5 catalyst in pyrolysis of polystyrene and polypropylene: sustainable waste-to-energy conversion enhanced by machine learning models DOI
Prathiba Rex, M. Kalil Rahiman

Journal of Material Cycles and Waste Management, Journal Year: 2024, Volume and Issue: 26(6), P. 3433 - 3445

Published: Aug. 13, 2024

Language: Английский

Citations

1
Machine learning for revealing the relationship between the process–structure–properties of polypropylene in-reactor alloys DOI Creative Commons
Zheng Shaojie, Xu Huang, Jijiang Hu

et al.

Reaction Chemistry & Engineering, Journal Year: 2024, Volume and Issue: 9(6), P. 1354 - 1363

Published: Jan. 1, 2024

Polypropylene reactor alloys with distinct structures were synthesized, and machine learning models developed to reveal the relationship between process–structure–properties optimize process conditions.

Language: Английский

Citations

0