Predicting molecular composition of primary product derived from fast pyrolysis of lignin with semi-detailed kinetic model

Predicting molecular composition of primary product derived from fast pyrolysis of lignin with... Fuel 212 (2018) 515–522 Contents lists available at ScienceDirect Fuel journal homepage: www.elsevier.com/locate/fuel Full Length Article Predicting molecular composition of primary product derived from fast pyrolysis of lignin with semi-detailed kinetic model a b b,c d, Yuki Furutani , Shinji Kudo , Jun-ichiro Hayashi , Koyo Norinaga Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, 6-1, Kasuga-koen, Kasuga, Fukuoka 816-8580, Japan Institute for Materials Chemistry and Engineering, Kyushu University, 6-1, Kasuga-koen, Kasuga, Fukuoka 816-8580, Japan Research and Education Center of Carbon Resources, Kyushu University, 6-1, Kasuga-koen, Kasuga, Fukuoka 816-8580, Japan Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan GR APHICAL A BSTRACT ARTICLE I NFO ABSTRACT Keywords: A numerical approach is presented for predicting the yields of char and volatile components obtained from fast Fast pyrolysis pyrolysis of three types of lignin (enzymatic hydrolysis lignin, EHL; organic extracted lignin, OEL; and Klason Lignin lignin, KL) in a two-stage tubular reactor (TS-TR) at 773–1223 K. The heating rate of lignin particle in the TS-TR Product yield 2 4 was estimated at 10 –10 K/s by solving the heat transfer equation. The pyrolytic behavior of lignin and the Semi-detailed kinetic model formation of products in the temperature rising http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Fuel Elsevier

Predicting molecular composition of primary product derived from fast pyrolysis of lignin with semi-detailed kinetic model

Loading next page...
 
/lp/elsevier/predicting-molecular-composition-of-primary-product-derived-from-fast-u0nxZ8YI4g
Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0016-2361
D.O.I.
10.1016/j.fuel.2017.10.079
Publisher site
See Article on Publisher Site

Abstract

Fuel 212 (2018) 515–522 Contents lists available at ScienceDirect Fuel journal homepage: www.elsevier.com/locate/fuel Full Length Article Predicting molecular composition of primary product derived from fast pyrolysis of lignin with semi-detailed kinetic model a b b,c d, Yuki Furutani , Shinji Kudo , Jun-ichiro Hayashi , Koyo Norinaga Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, 6-1, Kasuga-koen, Kasuga, Fukuoka 816-8580, Japan Institute for Materials Chemistry and Engineering, Kyushu University, 6-1, Kasuga-koen, Kasuga, Fukuoka 816-8580, Japan Research and Education Center of Carbon Resources, Kyushu University, 6-1, Kasuga-koen, Kasuga, Fukuoka 816-8580, Japan Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan GR APHICAL A BSTRACT ARTICLE I NFO ABSTRACT Keywords: A numerical approach is presented for predicting the yields of char and volatile components obtained from fast Fast pyrolysis pyrolysis of three types of lignin (enzymatic hydrolysis lignin, EHL; organic extracted lignin, OEL; and Klason Lignin lignin, KL) in a two-stage tubular reactor (TS-TR) at 773–1223 K. The heating rate of lignin particle in the TS-TR Product yield 2 4 was estimated at 10 –10 K/s by solving the heat transfer equation. The pyrolytic behavior of lignin and the Semi-detailed kinetic model formation of products in the temperature rising

Journal

FuelElsevier

Published: Jan 15, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from
Google Scholar,
PubMed
Create lists to
organize your research
Export lists, citations
Read DeepDyve articles
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off