A universal scaling law for active diffusion in complex media.

Qun Zhang, Yuxin Tian, Xue Zhang, Xiaoting Yu, Hongwei Zhu, Ning Zheng, Luhui Ning, Ran Ni, Mingcheng Yang, Peng Liu

Abstract read

In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Qun Zhang *School of Physics, Beijing Institute of Technology, Beijing, China.

Yuxin Tian *School of Physics, Beijing Institute of Technology, Beijing, China.ORCID http://orcid.org/0009-0003-4454-793X

Xue ZhangSchool of Physics, Beijing Institute of Technology, Beijing, China.

Xiaoting YuSchool of Physics, Beijing Institute of Technology, Beijing, China.

Hongwei ZhuSchool of Physical Science and Technology, Key Laboratory of Magnetism and Magnetic Materials for Higher Education in Inner Mongolia Autonomous Region, Baotou Teachers' College, Baotou, China.

Ning ZhengSchool of Physics, Beijing Institute of Technology, Beijing, China. ningzheng@bit.edu.cn.ORCID http://orcid.org/0000-0003-2449-7202

Luhui NingBeijing Key Laboratory of Optical Detection Technology for Oil and Gas, China University of Petroleum-Beijing, Beijing, China. lhningphy@cup.edu.cn.ORCID http://orcid.org/0000-0001-5256-9205

Ran NiSchool of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, 62 Nanyang Drive, Singapore, Singapore. r.ni@ntu.edu.sg.ORCID http://orcid.org/0000-0001-9478-0674

Mingcheng YangBeijing National Laboratory for Condensed Matter Physics and Laboratory of Soft Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing, China. mcyang@iphy.ac.cn.ORCID http://orcid.org/0000-0002-8742-9277

Peng LiuSchool of Physics, Beijing Institute of Technology, Beijing, China. liupeng@bit.edu.cn.ORCID http://orcid.org/0000-0002-0898-584X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 12475031Natural Science Foundation of Shandong Province (Shandong Provincial Natural Science Foundation) ZR2024YQ017

6 · The paper itself

Abstract

Understanding how active particles transport in structurally heterogeneous environments is a fundamental and challenging problem, with relevance to biological and synthetic microswimmers in tissues and porous media. Here, using granular experiments and computer simulations, we investigate the long-time diffusion of active tracers in quasi-two-dimensional heterogeneous media. We show that diffusion-structure relations established for passive systems fail to describe active transport across different activity levels. To resolve this, we formulate a modified diffusion-structure relation by incorporating the dimensionless persistence length Q = v

Identifiers

PMID42225612

DOI10.1038/s41467-026-73626-8

PMCPMC13391495

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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.