Evidence map›Paper›PMID 37576194›Full record

ArticleHeliyon2023

Modeling and optimization of green-Al 6061 prepared from environmentally source materials.

Adeolu Adesoji Adediran, Abayomi Adewale Akinwande, Olanrewaju S Adesina, Victor Agbaso, Oluwatosin Abiodun Balogun, B Ravi Kumar

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 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 21% 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, 11 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 4 institutions in 2 countries.

Adeolu Adesoji AdediranDepartment of Mechanical Engineering, Landmark University, Omu-Aran, Kwara State, Nigeria.
Abayomi Adewale AkinwandeDepartment of Metallurgical and Materials Engineering, Federal University of Technology, Akure, Ondo State, Nigeria.
Olanrewaju S AdesinaDepartment of Mechanical Engineering, Redeemers University, Ede, Osun State, Nigeria.
Victor AgbasoDepartment of Mechanical Engineering, Landmark University, Omu-Aran, Kwara State, Nigeria.
Oluwatosin Abiodun BalogunDepartment of Metallurgical and Materials Engineering, Federal University of Technology, Akure, Ondo State, Nigeria.
B Ravi KumarMTE Division, CSIR-National Metallurgical Laboratory, Jamshedpur, India.
Federal University of Technology · NGLandmark University · NGNational Metallurgical Laboratory · INRedeemer's University · NG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies are evaluating the use of particulates fabricated from agro-based residues as reinforcement for enhancing the properties of aluminium alloys. This report focuses on the optimization approach and modeling of responses for future prediction, which are absent from the majority of studies involving particle reinforcement of an aluminum matrix. Herein, palm kernel shell ash (PKA) and rice husk ash (RHA) were incorporated with 4 wt% of WSD and used as fillers in the Aluminium-6061 matrix at variable proportions. The response surface approach was utilized in the experiment design, modeling, and outcome optimization. The independent variables are the proportions of PKA and RHA and stir casting temperature. Yield, ultimate tensile, impact strength, elastic modulus, and fracture toughness are examined as response parameters. The results demonstrated that the microstructural property played a significant role in the responses. Incorporating PKA and RHA into the Al-6061 matrix improved the response parameters. Temperatures in the range of 700 and 800 °C enhanced the property parameters, even though temperatures within 800 and 900 °C caused a decline in response. The dependence of the responses on the pattern between property variables was revealed by surface and contour plots. The development of models for predicting responses. Optimal conditions were reached at 4.03% PKA, 5.12% RHA, and 787 °C, with an error <5% when compared to the forecast responses, thus validating the model.

Indexed as

Al6061Casting methodsCharacterizationCompositesGrainsMechanical properties

Identifiers

PMID37576194
PMCPMC10412880
OpenAlexW4384938240

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.