Evidence map›Paper›PMID 37629849›Full record

ArticleMaterials (Basel, Switzerland)2023

Research and Development of Self-Waterproofing Concrete for Tunnel Lining Structure and Its Impermeability and Crack Resistance Characteristics.

Huayun Li, Anxiang Zhou, Yangfan Wu, Lai Deng, Kaicheng Zhu, Feng Lu

Open access · goldAbstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.4field-weighted citation impact, top 22% of its field
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

1 citing paper in PubMed, 9 citations in OpenAlex.

  1. 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 at 1 institution in 1 country.

Huayun LiSchool of Architecture and Civil Engineering, Xihua University, Chengdu 610039, China.
Anxiang ZhouSchool of Architecture and Civil Engineering, Xihua University, Chengdu 610039, China.
Yangfan WuSchool of Architecture and Civil Engineering, Xihua University, Chengdu 610039, China.ORCID 0009-0001-8894-1248
Lai DengSchool of Architecture and Civil Engineering, Xihua University, Chengdu 610039, China.
Kaicheng ZhuSchool of Architecture and Civil Engineering, Xihua University, Chengdu 610039, China.
Feng LuSchool of Emergency Management, Xihua University, Chengdu 610039, China.
Xihua University · CN

Funding

Natural Science Foundation of Sichuan Province (No. 2022NSFSC1025)
6 · The paper itself

Abstract

This research paper systematically investigates the combined influence of fly ash, cementitious capillary crystalline waterproofing (CCCW) materials, and polypropylene fibers on the mechanical properties and impermeability of concrete through comprehensive orthogonal tests. Microscopic morphological changes in the concrete induced by different composite materials are examined via scanning electron microscopy (SEM) and X-ray diffraction (XRD) testing. The objective is to facilitate a beneficial synergetic interaction among these materials to develop highly permeable, crack-resistant concrete. Key findings of this study are: (1) The study unveils the impact of the concentration of three additive materials on the concrete's compressive strength, tensile strength, and penetration height, thereby outlining their significant influence on the mechanical properties and impermeability of the concrete; (2) An integrated scoring method determined the optimal composite dosage of three materials: 15% fly ash, 2% CCCW, and polypropylene fibers at 1.5 kg/m

Indexed as

mechanical propertiesmicroscopic testingmix designorthogonal designwaterproof concrete

Identifiers

PMID37629849
PMCPMC10456606
OpenAlexW4385737441

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.