Evidence map›Paper›PMID 40805443›Full record

ArticleMaterials (Basel, Switzerland)2025

Predicting the Uniaxial Compressive Strength of Cement Paste: A Theoretical and Experimental Study.

Chunming Lian, Xiong Zhang, Lu Han, Weijun Wen, Lifang Han, Lizhen Wang

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2025. 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.

Chunming LianKey Laboratory of Advanced Civil Engineering Materials of Education Ministry, School of Material Science and Technology, Tongji University, 4800 Cao'an Road, Shanghai 201804, China.
Xiong ZhangKey Laboratory of Advanced Civil Engineering Materials of Education Ministry, School of Material Science and Technology, Tongji University, 4800 Cao'an Road, Shanghai 201804, China.
Lu HanChina Construction Eighth Bureau Science and Technology Construction Co., Ltd., 899 Gaoke West Road, Shanghai 201804, China.
Weijun WenChina Construction Eighth Bureau Science and Technology Construction Co., Ltd., 899 Gaoke West Road, Shanghai 201804, China.
Lifang HanChina Construction Eighth Bureau Science and Technology Construction Co., Ltd., 899 Gaoke West Road, Shanghai 201804, China.
Lizhen WangChina Construction Eighth Bureau Science and Technology Construction Co., Ltd., 899 Gaoke West Road, Shanghai 201804, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents a progressive strength prediction model for cement paste based on the hypothesis that compressive strength is governed by the microstructural compactness of hydration products. A three-stage modeling framework was developed: (1) a semi-empirical model for pure cement paste incorporating water-to-cement ratio and paste density; (2) a density-corrected effective water-cement ratio w/ceff that accounts for the physical effects of mineral additives including fly ash, slag, and limestone powder; and (3) a hydration-informed strength model incorporating curing age and temperature through an equivalent hydration degree αte. Experimental validation using over 60 cement paste mixes demonstrated high predictive accuracy, with coefficients of determination up to 0.97. The proposed model unifies the influence of binder composition, packing density, and curing conditions into a physically interpretable and practically applicable formulation. It enables early-age strength prediction of blended cementitious systems using only routine mix and density parameters, supporting performance-based mix design and optimization. The methodology provides a robust foundation for extending compactness-based modeling to more complex cementitious materials and structural applications.

Indexed as

cement pastecompressive strengthdensity correctionmineral admixturesstrength prediction model

Identifiers

PMID40805443
PMCPMC12348791

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.