Strength Prediction of Cement-Stabilized Steel Slag Using Deep Learning and SHAP Analysis.

Zunqing Liu, Yifei Wang, Jian Sun, Haojie Ji, Xiaoman Shan, Fei Liu

Abstract read

In one paragraph

Article in Materials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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5 · Who and what money

Authors and funding

6 authors.

Zunqing LiuSchool of Traffic and Logistics Engineering, Xinjiang Agricultural University, Urumqi 830052, China.

Yifei WangSchool of Traffic and Logistics Engineering, Xinjiang Agricultural University, Urumqi 830052, China.

Jian SunSchool of Traffic and Logistics Engineering, Xinjiang Agricultural University, Urumqi 830052, China.

Haojie JiSchool of Traffic and Logistics Engineering, Xinjiang Agricultural University, Urumqi 830052, China.

Xiaoman ShanSchool of Traffic and Logistics Engineering, Xinjiang Agricultural University, Urumqi 830052, China.

Fei LiuXinjiang Production and Construction Corps Survey and Design Institute Group Co., Ltd., Urumqi 830002, China.

Funding

National Natural Science Foundation of China 52268072

6 · The paper itself

Abstract

This study combined experimental analysis with deep learning to investigate the effects of curing age, steel slag content, and gradation composition on the mechanical properties of cement-stabilized steel slag (CSSS). The strength evolution patterns and underlying microscopic mechanisms were systematically elucidated. Experimental results showed that CSSS strength grows nonlinearly with curing age, with optimal mechanical performance achieved at a 60% steel slag content. The microstructural evolution characterized by SEM-EDS and XRD revealed that steel slag incorporation promotes the formation of AFt and densifies the gel network. In later curing stages, natural carbonation of Ca(OH)

Indexed as

cement-stabilized steel slagdeep learningmechanical propertiesSHAP analysissteel slag

Identifiers

PMID41753513

DOI10.3390/ma19040795

PMCPMC12941763

What OpenQuestion holds

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LicenceCC BY

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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.