Evidence map›Paper›PMID 41802135›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Sub-Unit-Cell Logic Governs Transport in TPMS Architectures.

Haozhang Zhong, Yipei He, Jiaxuan Wang, Chenyi Qian, Gerd E Schröder-Turk, Raj Das, Junye Shi, Qi Tang, Zheda Ning, Wenjue Yi and 7 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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

17 authors.

Haozhang ZhongInstitute of Materials Modification and Modeling, Shanghai Jiao Tong University, Shanghai, China.
Yipei HeInstitute of Materials Modification and Modeling, Shanghai Jiao Tong University, Shanghai, China.
Jiaxuan WangInstitute of Refrigeration and Cryogenics, Shanghai Jiao Tong University, Shanghai, China.
Chenyi QianInstitute of Refrigeration and Cryogenics, Shanghai Jiao Tong University, Shanghai, China.
Gerd E Schröder-TurkSchool of Mathematics, Statistics, Chemistry and Physics, Murdoch University, Perth, Western Australia, Australia.
Raj DasCentre for Additive Manufacturing, School of Engineering, RMIT University, Melbourne, Victoria, Australia.
Junye ShiInstitute of Refrigeration and Cryogenics, Shanghai Jiao Tong University, Shanghai, China.
Qi TangInstitute of Materials Modification and Modeling, Shanghai Jiao Tong University, Shanghai, China.
Zheda NingInstitute of Materials Modification and Modeling, Shanghai Jiao Tong University, Shanghai, China.
Wenjue YiInstitute of Materials Modification and Modeling, Shanghai Jiao Tong University, Shanghai, China.
Chuanwei LiInstitute of Materials Modification and Modeling, Shanghai Jiao Tong University, Shanghai, China.
Jiangping ChenInstitute of Refrigeration and Cryogenics, Shanghai Jiao Tong University, Shanghai, China.
Zeyao ChenSchool of Electro-Mechanical Engineering, Guangdong University of Technology, Guangzhou, China.
Binbin YuInstitute of Refrigeration and Cryogenics, Shanghai Jiao Tong University, Shanghai, China.
Jian LuDepartment of Mechanical Engineering, City University of Hong Kong, Hong Kong, China.
Jianfeng GuInstitute of Materials Modification and Modeling, Shanghai Jiao Tong University, Shanghai, China.
Ma QianCentre for Additive Manufacturing, School of Engineering, RMIT University, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0001-9705-6913

Funding

Australian Research Council DP250103847Gu Jianfeng Expert Workstation of Yunnan Province 202405AF140041Key Research and Development Project of the Yunnan Laboratory for Precious Metals YPML-20240502080National Natural Science Foundation of China 52305270
6 · The paper itself

Abstract

Next-generation energy, thermal, and chemical systems require architectures capable of highly efficient transport across multiple length scales. Triply periodic minimal surfaces (TPMS), first conceptualized in 1865, offer inherently scalable geometries with exceptional transport potential, yet mechanistic links between topology and performance have remained elusive. Here we introduce a sub-unit-cell conduit framework that governs transport in TPMS architectures. By integrating crystallographic symmetry analysis with Voronoi tessellation, we show that each TPMS can be resolved into a network of identical intrinsic conduits oriented in different directions, with geometry and connectivity uniquely determined by topology. This framework reveals that transport efficiency is determined primarily by two conduit-scale descriptors-conduit uniformity and conduit spatial density-while conduit surface area and connectivity play secondary roles. Building on these insights, we derive predictive descriptors and a performance quotient that link local conduit geometry to TPMS transport behavior independent of scale and operating conditions. The model identifies Fischer-Koch as a leading topology, which we validate using additively manufactured copper Fischer-Koch TPMS heat exchangers fabricated via green-laser powder bed fusion. Experiments reveal up to a 156-fold improvement in heat-exchange efficiency (quantified by the j/f ratio) for the copper Fischer-Koch TPMS, compared with a conventional baseline, aligning closely with model predictions. This sub-unit-cell conduit approach provides a generalizable mechanistic basis for the rational design of high-performance TPMS-architected materials across diverse transport applications.

Indexed as

3D printingsub‐unit cellsTPMS metamaterialstransport function

Identifiers

PMID41802135
PMCPMC13205735

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.