The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Dynamic Clustering and Chemotactic Collapse of Self-Phoretic Active Particles
Open accessAbstract
Recent experiments with self-phoretic particles at low concentrations show a pronounced dynamic clustering [I. Theurkauff et al., Phys. Rev. Lett. 108, 268303 (2012)]. We model this situation by taking into account the translational and rotational diffusiophoretic motion, which the active particles perform in their self-generated chemical field. Our Brownian dynamics simulations show pronounced dynamic clustering only when these two phoretic contributions give rise to competing attractive and repulsive interactions, respectively. We identify two dynamic clustering states and characterize them by power-law-exponential distributions. In case of mere attraction a chemotactic collapse occurs directly from the gaslike into the collapsed state, which we also predict by mapping our Langevin dynamics on the Keller-Segel model for bacterial chemotaxis.
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.
Integrity signals
Registry
Cites
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.
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
Vicsek, T., & Zafeiris, A. (2012) · Physics Reports · doi:10.1016/j.physrep.2012.03.004 · Cited by 2,923
Inferring the structure and dynamics of interactions in schooling fish
Katz, Y., Tunstrøm, K., Ioannou, C. C., Huepe, C., & Couzin, I. D. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1107583108 · Cited by 927
Cited by
Emergent behavior in active colloids
Zöttl, A., & Stark, H. (2016) · Journal of Physics: Condensed Matter · doi:10.1088/0953-8984/28/25/253001 · Cited by 426
Self-citationOsmosis, from molecular insights to large-scale applications
Marbach, S., & Bocquet, L. (2019) · Chemical Society Reviews · doi:10.1039/c8cs00420j · Cited by 316
Metadata
- Authors
- Pohl, O., & Stark, H.
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 2014-06-10
- Volume
- 112
- Issue
- 23
- Pages
- 238303-238303
- ISSN
- 0031-9007 (ISSN-L)
- 1079-7114
- OpenAlex
- W1975247487
- Cited by
- 221
- References
- 2
- FWCI
- 9.65
- Type
- journal article
- Language
- en
- Open access
- green
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Dynamic Clustering and Chemotactic Collapse of Self-Phoretic Active Particles. https://app.cochat.ai/papers/10.1103/physrevlett.112.238303
- The paper
- Pohl, O., & Stark, H. (2014). Dynamic Clustering and Chemotactic Collapse of Self-Phoretic Active Particles. Physical Review Letters. https://doi.org/10.1103/physrevlett.112.238303
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.