Determining Homogenization Parameters and Predicting 5182-Sc-Zr Alloy Properties by Artificial Neural Networks.

Jingxiao Li, Dongfang Du, Xiaofang Yang, Youcai Qiu, Shihua Xiang

Abstract 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. 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

The trial behind it

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3 · Its place in the literature

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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

5 authors.

Jingxiao LiDepartment of Materials Engineering, Sichuan Engineering Technical College, Deyang 618000, China.

Dongfang DuDepartment of Materials Engineering, Sichuan Engineering Technical College, Deyang 618000, China.

Xiaofang YangInternational Joint Laboratory for Light Alloys (Ministry of Education), College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China.

Youcai QiuInternational Joint Laboratory for Light Alloys (Ministry of Education), College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China.

Shihua XiangInternational Joint Laboratory for Light Alloys (Ministry of Education), College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China.

Funding

Fundamental Research Funds for the Central Universities 2020CDJDCL001National Natural Science Foundation of China 51421001National Natural Science Foundation of China 51571046Open Funding of International Joint Laboratory for Light Alloys (MOE) Chongqing UniversityThe "111" Project by the Ministry of Education and the State Administration of Foreign Experts Affairs of China B16007

6 · The paper itself

Abstract

Artificial neural networks (ANNs) were established for the homogenization and recrystallization heat treatment processes of 5182-Sc-Zr alloy. Microhardness and conductivity testing were utilized to determine the precipitation state of Al

Indexed as

5182-Sc-Zr alloyartificial neural networkhomogenization treatmentparameters selectionrecrystallization treatment

Identifiers

PMID37570019

DOI10.3390/ma16155315

PMCPMC10419564

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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.