2016
DOI: 10.1016/j.enconman.2016.05.007
|View full text |Cite
|
Sign up to set email alerts
|

Thermal degradation of beech wood with thermogravimetry/Fourier transform infrared analysis

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

2
22
0

Year Published

2018
2018
2024
2024

Publication Types

Select...
7

Relationship

2
5

Authors

Journals

citations
Cited by 159 publications
(27 citation statements)
references
References 40 publications
2
22
0
Order By: Relevance
“…However, the above researches are not enough to reveal the pyrolysis dynamics of engineering plastic waste CPVC, so the aim of current paper is to explore its pyrolysis behaviors and obtained appropriate kinetic parameters.Knowledge of pyrolysis kinetics can help provide better understanding and planning of important industrial processes [24], such as their application in pyrolysis model [25] and direct combustion [26].Model-fitting and model-fitting methods are the common ways to explore the kinetic parameters. Model-fitting method consists of fitting different models to the experimental data for the best statistical fit but with the inability to determine the reaction model [27]. However, model-free method can come over this problem without prior knowledge of the reaction model and estimate the kinetic parameters at specific extent of conversion to provide appropriate search ranges for model-fitting method [28].…”
mentioning
confidence: 99%
See 1 more Smart Citation
“…However, the above researches are not enough to reveal the pyrolysis dynamics of engineering plastic waste CPVC, so the aim of current paper is to explore its pyrolysis behaviors and obtained appropriate kinetic parameters.Knowledge of pyrolysis kinetics can help provide better understanding and planning of important industrial processes [24], such as their application in pyrolysis model [25] and direct combustion [26].Model-fitting and model-fitting methods are the common ways to explore the kinetic parameters. Model-fitting method consists of fitting different models to the experimental data for the best statistical fit but with the inability to determine the reaction model [27]. However, model-free method can come over this problem without prior knowledge of the reaction model and estimate the kinetic parameters at specific extent of conversion to provide appropriate search ranges for model-fitting method [28].…”
mentioning
confidence: 99%
“…Model-fitting and model-fitting methods are the common ways to explore the kinetic parameters. Model-fitting method consists of fitting different models to the experimental data for the best statistical fit but with the inability to determine the reaction model [27]. However, model-free method can come over this problem without prior knowledge of the reaction model and estimate the kinetic parameters at specific extent of conversion to provide appropriate search ranges for model-fitting method [28].…”
mentioning
confidence: 99%
“…Ash (Fraxinus) wood sawdust, Ea (198 kJ/mol -202 kJ/mol) is similar to waste tea pyrolysis (Ea: 208kJ/mol -223 kJ/mol) (Tian et al 2016). The results still show that Ash sawdust was not so easy to pyrolyse compared to beech wood (Ea: 147-174kJ/mol) (Ding et al 2016), moso bamboo (Ea: 96-113kJ/mol) (Chen, Zhou, and Zhang 2014), and other biomass with lower activation energy , , (Slopiecka, Bartocci, and Fantozzi 2012), (Sonobe and Worasuwannarak 2008).…”
Section: Activation Energymentioning
confidence: 88%
“…However, investigation of the material properties has to be made to ensure suitability for any probable bioenergy production like bio-char. Several researchers have analyzed and characterized a number of biomass resources including beech wood (Ding et al 2016), pine wood (Mishra, Kumar, and Bhaskar 2015), bamboo (Chen, Liu, et al 2015) among others for their energy Published by Taylor and Francis. This is the Author Accepted Manuscript issued with: Creative Commons Attribution Non-Commercial License (CC:BY:NC 4.0).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation