Evidence map›Paper›PMID 30815031›Full record

ArticleBiotechnology for biofuels2019

Microfluidic techniques for enhancing biofuel and biorefinery industry based on microalgae.

Pierre Bodénès, Hsiang-Yu Wang, Tsung-Hua Lee, Hung-Yu Chen, Chun-Yen Wang

Abstract read
In one paragraph

Article in Biotechnology for biofuels, 2019. 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
–field-weighted citation impact
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.

  1. Review
  2. Article
  3. Review
  4. Microfluidic Microalgae System: A Review.Molecules (Basel, Switzerland) · 2022
    Review
  5. Review
  6. Article
  7. Review
  8. High-Throughput Screening ofBiomolecules · 2019
    Article
  9. Article
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

5 authors.

Pierre Bodénès1Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan.
Hsiang-Yu Wang2Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan.ORCID 0000-0002-4798-0670
Tsung-Hua Lee4Department of Chemical Engineering, National Cheng Kung University, Tainan, Taiwan.
Hung-Yu Chen *2Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan.
Chun-Yen Wang *2Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review presents a critical assessment of emerging microfluidic technologies for the application on biological productions of biofuels and other chemicals from microalgae. Comparisons of cell culture designs for the screening of microalgae strains and growth conditions are provided with three categories: mechanical traps, droplets, or microchambers. Emerging technologies for the in situ characterization of microalgae features and metabolites are also presented and evaluated. Biomass and secondary metabolite productivities obtained at microscale are compared with the values obtained at bulk scale to assess the feasibility of optimizing large-scale operations using microfluidic platforms. The recent studies in microsystems for microalgae pretreatment, fractionation and extraction of metabolites are also reviewed. Finally, comments toward future developments (high-pressure/-temperature process; solvent-resistant devices; omics analysis, including genome/epigenome, proteome, and metabolome; biofilm reactors) of microfluidic techniques for microalgae applications are provided.

Indexed as

Downstream treatmentsMetabolites productionMicroalgaeMicrofluidicsScreening

Identifiers

PMID30815031
PMCPMC6376642

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.