Accelerated First-Principles Calculations Based on Machine Learning for Interfacial Modification Element Screening of SiCp/Al Composites.

Xiaoshuang Du, Nan Qu, Xuexi Zhang, Jiaying Chen, Puchang Cui, Jingtao Huang, Yong Liu, Jingchuan Zhu

Abstract read

In one paragraph

Article in Materials (Basel, Switzerland), 2024. 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

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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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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.

Effect of Fe/Ni Microalloying on Interface Regulation of SiC/Al Composites: Molecular Dynamics Simulation and Experiments.Materials (Basel, Switzerland) · 2026
Article

4 · The record

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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

8 authors.

Xiaoshuang DuSchool of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China.

Nan QuSchool of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China.

Xuexi ZhangSchool of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China.ORCID 0000-0002-7939-7025

Jiaying ChenSchool of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China.

Puchang CuiSchool of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China.

Jingtao HuangSchool of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China.

Yong LiuSchool of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China.

Jingchuan ZhuSchool of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China.ORCID 0000-0002-6075-2373

Funding

National Key R&D program of China 2022YFB3705701

6 · The paper itself

Abstract

SiCp/Al composites offer the advantages of lightweight construction, high strength, and corrosion resistance, rendering them extensively applicable across various domains such as aerospace and precision instrumentation. Nonetheless, the interfacial reaction between SiC and Al under high temperatures leads to degradation in material properties. In this study, the interface segregation energy and interface binding energy subsequent to the inclusion of alloying elements were computed through a first-principle methodology, serving as a dataset for machine learning. Feature descriptors for machine learning undergo refinement via feature engineering. Leveraging the theory of machine-learning-accelerated first-principle computation, six machine learning models-RBF, SVM, BPNN, ENS, ANN, and RF-were developed to train the dataset, with the ANN model selected based on R

Indexed as

first principleinterface modification elementmachine learningSiCp/Al matrix composites

Identifiers

PMID38541476

DOI10.3390/ma17061322

PMCPMC10972090

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LicenceCC BY

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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.