2017
DOI: 10.1590/0104-6632.20170341s20160086
|View full text |Cite
|
Sign up to set email alerts
|

Biomass Pyrolysis Kinetics: A Review of Molecular-Scale Modeling Contributions

Abstract: -Decades of classical research on pyrolysis of lignocellulosic biomass has not yet produced a generalized formalism for design and prediction of reactor performance. Plagued by the limitations of experimental techniques such as thermogravimetric analysis (TGA) and extremely fast heating rates and low residence times to achieve high conversion to useful liquid products, researchers are now turning to molecular modeling to gain insights. This contribution briefly summarizes prior reviews along the historical pat… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
21
0

Year Published

2018
2018
2023
2023

Publication Types

Select...
6
1
1

Relationship

0
8

Authors

Journals

citations
Cited by 23 publications
(21 citation statements)
references
References 141 publications
0
21
0
Order By: Relevance
“…This increase is anticipated to increase the electrical properties of composites [23]. Both the physical and chemical properties of particle are largely reliant on the void, particle size, ratio of the amorphous, and crystalline phases as cited by Murillo et al [24] and Richard et al [25]. The patterns of XRD of all SLS-HDPE composites do not display any secondary peaks signifying that the material samples were pure samples.…”
Section: Resultsmentioning
confidence: 84%
“…This increase is anticipated to increase the electrical properties of composites [23]. Both the physical and chemical properties of particle are largely reliant on the void, particle size, ratio of the amorphous, and crystalline phases as cited by Murillo et al [24] and Richard et al [25]. The patterns of XRD of all SLS-HDPE composites do not display any secondary peaks signifying that the material samples were pure samples.…”
Section: Resultsmentioning
confidence: 84%
“…TGAs are widely applied in kinetic studies because of their ability to measure sample weight loss and temperature measurement with respect to reaction time (Bach & Chen, 2017;Cai et al, 2018;Murillo, Biernacki, Northrup, & Mohammad, 2017;Wang et al, 2016). Thermogravimetric data and differential thermogravimetric data (DTG) facilitate identification of various stages of biomass pyrolysis and temperature ranges for the decomposition of biomass components, respectively (Dollimore, Evans, Lee, & Wilburn, 1992).…”
Section: Thermogravimetric Analyzersmentioning
confidence: 99%
“…Through TGA studies the decomposition of cellulose, hemicellulose, and lignin was found to occur in reasonably distinct temperature ranges, 300-400, 200-380 and above 400 C, respectively (Yang, Yan, Chen, Lee, & Zheng, 2007). This topic has been extensively reviewed by Bach and Chen (2017), Cai et al (2018), Murillo et al (2017), and Wang et al (2016). For over several decades, TGA-based studies are being performed to gather global kinetics of biomass and its components but no intrinsic kinetics can be elucidated.…”
Section: Thermogravimetric Analyzersmentioning
confidence: 99%
“…Pyrolysis, as an environmentally friendly and cost-effective technology for biomass conversion, has several advantages over the methods of incineration and landfilling because of its low energy consumption (only approximately 10% of the energy content of biomass is consumed for the pyrolysis itself), and the harmful gas emission in biomass pyrolysis is remarkably weaker than that in incineration. Therefore, in the past few years, pyrolysis has attracted growing interest as a promising versatile platform to convert biomass into valuable resources, and the number of scientific journal papers regarding biomass pyrolysis published per year increases rapidly, and has been thoroughly reviewed (Sharma et al, 2015;Anca-Couce, 2016;Dilks et al, 2016;Hassan et al, 2016;Kan et al, 2016;Patel et al, 2016;Tripathi et al, 2016;Zhang et al, 2016;Chiaramonti et al, 2017;Dhyani & Bhaskar, 2017;Li & Jiang, 2017;Liu et al, 2017;Murillo et al, 2017;Wang et al, 2017;Zeng et al, 2017).…”
Section: Introductionmentioning
confidence: 99%