Evidence map›Paper›PMID 35615315›Full record

ReviewFrontiers in chemistry2022

Recent Advances in the Catalytic Conversion of Biomass to Furfural in Deep Eutectic Solvents.

Xu Zhang, Peng Zhu, Qinfang Li, Haian Xia

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 41 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Xu ZhangJiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Chemical Engineering, Nanjing Forestry University, Nanjing, China.
Peng ZhuJiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Chemical Engineering, Nanjing Forestry University, Nanjing, China.
Qinfang LiJiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Chemical Engineering, Nanjing Forestry University, Nanjing, China.
Haian XiaJiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Chemical Engineering, Nanjing Forestry University, Nanjing, China.
Nanjing Forestry University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lignocellulose is recognized as an ideal raw material for biorefinery as it may be converted into biofuels and value-added products through a series of chemical routes. Furfural, a bio-based platform chemical generated from lignocellulosic biomass, has been identified as a very versatile alternative to fossil fuels. Deep eutectic solvents (DES) are new "green" solvents, which have been employed as green and cheap alternatives to traditional organic solvents and ionic liquids (ILs), with the advantages of low cost, low toxicity, and biodegradability, and also have been proven to be effective media for the synthesis of biomass-derived chemicals. This review summarizes the recent advances in the conversion of carbohydrates to furfural in DES solvent systems, which mainly focus on the effect of adding different catalysts to the DES system, including metal halides, water, solid acid catalyst, and certain oxides, on the production of furfural. Moreover, the challenges and perspectives of DES-assisted furfural synthesis in biorefinery systems are also discussed in this review.

Indexed as

biomasscatalysisdeep eutectic solventsfurfuralsolid acid

Identifiers

PMID35615315
PMCPMC9124943
OpenAlexW4229371257

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.