Evidence map›Paper›PMID 42754560›Full record

ArticleNature communications2026

Constructing and decoding tree-ring-like surface patterns on self-assembled polymer platelets.

Laihui Xiao, Tianlai Xia, Andrew P Dove, Rachel K O'Reilly

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

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

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

4 authors.

Laihui Xiao *School of Chemistry, University of Birmingham, Birmingham, UK.ORCID http://orcid.org/0000-0002-3412-0954
Tianlai Xia *School of Chemistry, University of Birmingham, Birmingham, UK.ORCID http://orcid.org/0000-0002-4391-0296
Andrew P DoveSchool of Chemistry, University of Birmingham, Birmingham, UK. a.dove@bham.ac.uk.ORCID http://orcid.org/0000-0001-8208-9309
Rachel K O'ReillySchool of Chemistry, University of Birmingham, Birmingham, UK. r.oreilly@bham.ac.uk.ORCID http://orcid.org/0000-0002-1043-7172

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precise control of surface patterns in assembled nanostructures remains a significant challenge in materials science. Here, we introduce a scalable bottom-up strategy utilizing living crystallization-driven self-assembly (CDSA) to fabricate tunable 3D surface patterns on polymer platelets. Inspired by biological growth increments, our approach leverages temperature-regulated, time-dependent crystallization to direct nanoscale organization, mimicking how nature constructs layered architectures. By exploiting polymer systems with temperature-dependent crystallization kinetics, we achieved diverse morphologies-including layered, concave, and convex features through controlled co-assembly and kinetic self-sorting. Temporal-thermal modulation was implemented in a continuous flow reactor, where precisely programmed residence times and temperature profiles enabled spatially resolved material deposition and growth history encoded in tree-ring-like patterns - control that is challenging or impossible to achieve using conventional batch methods. These features achieved lateral and vertical resolutions of ~73 nm and ~2 nm, respectively, allowing quantitative determination of directional crystallization rates (22.8 nm/s along the long axis and 13.4 nm/s along the short axis). Furthermore, modulating the number of layers provided a practical means to tune surface wettability. Our bioinspired design framework bridges synthetic self-assembly and natural structural logic, expanding opportunities for programmable materials in nanotechnology and functional systems.

Identifiers

PMID42754560
PMCPMC13586395

What OpenQuestion holds

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Registered trials

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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.