Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 364

The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.

A mechanistic model of fast pyrolysis of glucose-based carbohydrates to predict bio-oil composition

Vinu, R., Broadbelt, Linda J.·2012·Energy & Environmental Science
DOI 10.1039/c2ee22784c
Open this paper in CoChat — free account

Abstract

Bio-oil obtained from fast pyrolysis of biomass has the potential to be upgraded to renewable, drop-in fuel intermediates. The quality of bio-oil produced is critical to downstream process development and is determined by a number of factors like reaction timescale, extent of primary and secondary reactions, and the presence of minerals. In this work, we provide a mechanistic understanding of the various competing reactions in fast pyrolysis of cellulose and other glucose-based carbohydrates through a unified microkinetic model. The model incorporates the reactions of the cellulose chain and of the glucose intermediate to form a variety of bio-oil components, which are confirmed by either experiments or theoretical calculations reported in the literature. The majority of the Arrhenius rate parameters were based on existing studies, while a small number were fitted to match the experimental product distribution over a wide range of temperatures. The model yields of all the major primary fast pyrolysis products, viz., levoglucosan, formic acid, glycolaldehyde, 5-hydroxymethyl furfural, furfural and char, match reasonably well with the experimental data over the temperature range of 400–550 °C. The model predicted that the time required for complete conversion corresponds to 2.5–3 s. Net rate analysis identified key pathways to levoglucosan via either mid-chain initiation, or depropagation and end-chain initiation that were dominant over the timescales of 0–100 ms and 100–1000 ms, respectively, at 500 °C. Unlike the existing lumped kinetic models, our model provides a detailed picture of levoglucosan formation that involves mid-chain glycosidic bond cleavage followed by unzipping of levoglucosan from the chain ends. The model, utilizing the same set of rate coefficients, was able to predict the dominant products of fast pyrolysis of maltohexaose, cellobiose and glucose that also are in good agreement with experimental data. The initial chain length of cellulose was found to have a profound effect on the product yields for chain lengths shorter than 50, while it had no effect on the total reaction time.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1039/c2ee22784c

Cites

60 of 60 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 364

Metadata

Authors
Vinu, R., & Broadbelt, L. J.
Venue
Energy & Environmental Science
Publisher
Royal Society of Chemistry (RSC)
Published
2012
Volume
5
Issue
12
Pages
9808
ISSN
  • 1754-5692 (ISSN-L)
  • 1754-5706
DOI
10.1039/c2ee22784c
OpenAlex
W2025770802
Cited by
364
References
60
FWCI
11.34
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.