Evidence map›Paper›PMID 37537247›Full record

ArticleScientific reports2023

On the reaction-diffusion type modelling of the self-propelled object motion.

Masaharu Nagayama, Harunori Monobe, Koya Sakakibara, Ken-Ichi Nakamura, Yasuaki Kobayashi, Hiroyuki Kitahata

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Masaharu Nagayama *Research Center of Mathematics for Social Creativity, Research Institute for Electronic Science, Hokkaido University, Hokkaido, 060-0812, Japan. nagayama@es.hokudai.ac.jp.
Harunori Monobe *Department of Mathematics, Graduate School of Science, Osaka Metropolitan University, Osaka, 599-8531, Japan.
Koya Sakakibara *Institute of Science and Engineering, Kanazawa University, Ishikawa, 920-1192, Japan.
Ken-Ichi NakamuraMeiji Institute for Advanced Study of Mathematical Sciences, Meiji University, Tokyo, 164-8525, Japan.
Yasuaki KobayashiResearch Center of Mathematics for Social Creativity, Research Institute for Electronic Science, Hokkaido University, Hokkaido, 060-0812, Japan.
Hiroyuki KitahataDepartment of Physics, Chiba University, Chiba, 263-8522, Japan.

Funding

Cooperative Research Program of "Network Joint Research Centre for Materials and Devices" 20221162Cooperative Research Program of "Network Joint Research Centre for Materials and Devices" 20224003Japan Society for the Promotion of Science JP21H00996JP18K13455Japan Society for the Promotion of Science JP21H01004Japan Society for the Promotion of Science JP22K03425Japan Society for the Promotion of Science JP22K03428Japan Society for the Promotion of Science JP22K18677
6 · The paper itself

Abstract

In this study, we propose a mathematical model of self-propelled objects based on the Allen-Cahn type phase-field equation. We combine it with the equation for the concentration of surfactant used in previous studies to construct a model that can handle self-propelled object motion with shape change. A distinctive feature of our mathematical model is that it can represent both deformable self-propelled objects, such as droplets, and solid objects, such as camphor disks, by controlling a single parameter. Furthermore, we demonstrate that, by taking the singular limit, this phase-field based model can be reduced to a free boundary model, which is equivalent to the [Formula: see text]-gradient flow model of self-propelled objects derived by the variational principle from the interfacial energy, which gives a physical interpretation to the phase-field model.

Identifiers

PMID37537247
PMCPMC10400585

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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.