Evidence map›Paper›PMID 42764290›Full record

ArticleNature communications2026

Rethinking concrete durability for low-carbon concretes through climate-informed corrosion modelling.

Cristhiana Albert, Thilo Schmid, Zhidong Zhang, Ueli Angst

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.

Cristhiana Albert *Institute for Building Materials, ETH Zurich, Zurich, Switzerland.
Thilo Schmid *Institute for Building Materials, ETH Zurich, Zurich, Switzerland.
Zhidong ZhangInstitute for Building Materials, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-1701-9181
Ueli AngstInstitute for Building Materials, ETH Zurich, Zurich, Switzerland. uangst@ethz.ch.ORCID http://orcid.org/0000-0002-2603-4757

Funding

CemSuisse (Betonsuisse) 202204Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) 10003479
6 · The paper itself

Abstract

Decarbonizing concrete is essential for meeting global climate targets. Many effective strategies to reduce greenhouse gas emissions result in lower concrete alkalinity, which has traditionally been viewed as a durability concern, namely promoting steel corrosion in concrete. This prevailing durability paradigm - firmly embedded in engineering mindsets and industry standards - hinders the practical implementation and thus the realization of the full potential of low-carbon concretes. To resolve this situation, we propose a conceptual framework that offers a perspective on ensuring the durability of reinforced concrete, while tolerating reduced concrete alkalinity. Our approach is inspired by empirical observations and recent scientific insights that consistently pinpointed the decisive role of moisture in concrete durability. We leverage advancements in moisture transport modeling in porous media and corrosion science to predict the time-evolution of the microclimate and corrosion kinetics at the steel-concrete interface. By drawing on time-resolved meteorological data from four examples in Europe, Asia and South America, we showcase the approach, underlining the critical role of local climate for predicting the durability performance of concrete. This work establishes the basis for developing test methods, standards, and predictive tools to promote eco-friendly concrete and evaluate how climate change impacts their durability for generations to come.

Identifiers

PMID42764290
PMCPMC13590661

What OpenQuestion holds

Textmetadata
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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.