Evidence map›Paper›PMID 41570067›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Disorder-induced stress-flow misalignment in soft glassy materials revealed using multidirectional shear.

Frédéric Blanc, Guillaume Ovarlez, Adam Trigui, Kirsten Martens, Romain Mari

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Disorder-induced stress-flow misalignment in soft glassy materials revealed using multidirectional shear.Proceedings of the National Academy of Sciences of the United States of America · 2026
    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.

Frédéric BlancInstitut de Physique de Nice, UMR7010, CNRS, Université Côte d'Azur, 17 rue Julien Lauprêtre, Nice 06200, France.ORCID 0000-0002-6121-2520
Guillaume OvarlezUniv. Bordeaux, CNRS, Syensqo, LOF, UMR 5258, Pessac F-33600, France.ORCID 0000-0003-1554-1080
Adam TriguiUniv. Grenoble-Alpes, CNRS, LIPhy, Grenoble 38000, France.ORCID 0009-0005-9981-8121
Kirsten MartensUniv. Grenoble-Alpes, CNRS, LIPhy, Grenoble 38000, France.ORCID 0000-0003-2985-7385
Romain MariUniv. Grenoble-Alpes, CNRS, LIPhy, Grenoble 38000, France.ORCID 0000-0001-7877-416X

Funding

Agence Nationale de la Recherche (ANR) ANR-24-CE06-1565
6 · The paper itself

Abstract

Controlling the mechanical response of soft glassy materials-such as emulsions, foams, and colloidal suspensions-is key for many industrial processes. While their steady-state flow behavior is reasonably well understood, their response to complex flow histories, as encountered in operations like pumping or mixing, remains poorly known. Using a custom multiaxis shear apparatus that enables arbitrary changes in flow direction, we investigate how shear history influences the mechanical behavior of a model soft glassy system. We uncover a transient shear response orthogonal to the applied shear direction, together with an anisotropic yield surface. These effects point to an underlying anisotropic distribution of internal stresses imprinted by previous deformation. To rationalize this behavior, we use a mesoscopic elastoplastic model, demonstrating that local mechanical disorder governs the emergence of macroscopic stress-flow misalignment. Our findings offer a route to experimentally probe the distribution of local yield stresses in soft glassy materials.

Indexed as

mesoscopic modelrheologysoft matterstrain hardeningyielding

Identifiers

PMID41570067
PMCPMC12846846

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.