Evidence map›Paper›PMID 39591028›Full record

ArticleNanomaterials (Basel, Switzerland)2024

Modeling the Production Process of Lignin Nanoparticles Through Anti-Solvent Precipitation for Properties Prediction.

Victor Girard, Laurent Marchal-Heussler, Hubert Chapuis, Nicolas Brosse, Nadia Canilho, Isabelle Ziegler-Devin

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
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

6 authors.

Victor GirardLERMAB, Faculty of Science and Technology, University of Lorraine, INRAe, F-54000 Nancy, France.ORCID 0009-0007-9283-6778
Laurent Marchal-HeusslerENSIC, University of Lorraine, F-54000 Nancy, France.
Hubert ChapuisLERMAB, Faculty of Science and Technology, University of Lorraine, INRAe, F-54000 Nancy, France.ORCID 0000-0002-3745-7739
Nicolas BrosseLERMAB, Faculty of Science and Technology, University of Lorraine, INRAe, F-54000 Nancy, France.ORCID 0000-0001-8505-8401
Nadia CanilhoL2CM, Faculty of Science and Technology, University of Lorraine, CNRS, F-54000 Nancy, France.
Isabelle Ziegler-DevinLERMAB, Faculty of Science and Technology, University of Lorraine, INRAe, F-54000 Nancy, France.ORCID 0000-0001-7130-507X

Funding

ARBRE Laboratory of Excellence ANR-11-LABX-0002-01
6 · The paper itself

Abstract

Global warming has recently intensified research interest in renewable polymer chemistry, with significant attention directed towards lignin nanoparticle (LNP) synthesis. Despite progress, LNP industrial application faces challenges: (1) reliance on kraft lignin from declining raw biomass processes, (2) sulfur-rich and condensed lignin use, (3) complex lignin macroparticles to LNP conversion, using harmful and toxic solvents, and, above all, (4) lack of control over the LNP production process (i.e., anti-solvent precipitation parameters), resulting in excessive variability in properties. In this work, eco-friendly LNPs with tailored properties were produced from a semi-industrial organosolv process by studying anti-solvent precipitation variables. Using first a parametric and then a Fractional Factorial Design, predictions of LNP sizes and size distribution, as well as zeta-potential, were derived from a model over beech by-products organosolv lignin, depending on initial lignin concentration (x

Indexed as

anti-solvent precipitationligninnanoparticlesorganosolv processprediction model

Identifiers

PMID39591028
PMCPMC11597156

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.