Evidence map›Paper›PMID 36233965›Full record

ArticleMaterials (Basel, Switzerland)2022

Optimized Alkali-Activated Slag-Based Concrete Reinforced with Recycled Tire Steel Fiber.

Milad Eskandarinia, Mina Esmailzade, Ata Hojatkashani, Aida Rahmani, Soheil Jahandari

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2022. 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
–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

1 citing paper in PubMed.

  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

5 authors.

Milad EskandariniaDepartment of Civil Engineering, South Tehran Branch, Islamic Azad University, Tehran 15847-43311, Iran.ORCID 0000-0003-4834-8199
Mina EsmailzadeDepartment of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran 16788-15811, Iran.ORCID 0000-0001-8813-1176
Ata HojatkashaniDepartment of Civil Engineering, South Tehran Branch, Islamic Azad University, Tehran 15847-43311, Iran.ORCID 0000-0003-4244-1552
Aida RahmaniCentre for Infrastructure Engineering, Western Sydney University, Penrith, NSW 2751, Australia.
Soheil JahandariCentre for Infrastructure Engineering, Western Sydney University, Penrith, NSW 2751, Australia.ORCID 0000-0001-9449-1848

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study employed Taguchi-Grey relational analysis to optimize the influences of binder content, the molarity of sodium hydroxide (SH) solution, alkaline solution to binder content (Al/Bi) ratio, water to alkali-activated solids (W/S) ratio, and sodium silicate to sodium hydroxide solution (SS/SH) ratio on the workability, setting time, and compressive strength of alkali-activated slag-based concrete (AASC). Then, the recycled tire steel fibers (RTSF) were introduced into the optimized mixture in different dosages, and the physical and mechanical properties of fiber-reinforced AASC (FR-AASC) were evaluated. RTSF inclusion negatively affected the workability and increased the density while slightly reducing the water absorption. Additionally, the compressive strength and flexural behavior of FR-AASC improved by increasing the RTSF content. The analysis of images taken from flexural specimens through the Digital Image Correlation technique (DIC) revealed that higher RTSF dosage caused a curved macro crack with several branches alongside, leading to a better post-cracking performance in terms of strength and toughness.

Indexed as

alkali-activated slag-based concretefiber-reinforced concreteimage processing techniquerecycled tire steel fiberTaguchi-Grey relational analysis method

Identifiers

PMID36233965
PMCPMC9572460

What OpenQuestion holds

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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.