Artificial neural network approach for microhardness prediction of eight component FeCoNiCrMnVAlNb eutectic high entropy alloys

被引：32

作者：

Jain, Reliance ^{[1
]}

Dewangan, Sheetal Kumar ^{[1
]}

Kumar, Vinod ^{[2
]}

Samal, Sumanta ^{[1
]}

机构：

[1] Indian Inst Technol, Discipline Met Engn & Mat Sci, Indore, Madhya Pradesh, India

[2] Indian Inst Technol Indore, Ctr Adv Elect CAE, Indore, Madhya Pradesh, India

来源：

MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING | 2020年 / 797卷

关键词：

Eutectic high entropy alloys (EHEAs); Thermodynamic simulation; Microhardness; ANN; Solidification; MECHANICAL-PROPERTIES; MICROSTRUCTURE; TEXTURE; TEMPERATURE; COMPOSITES; STABILITY; EVOLUTION; HARDNESS; GROWTH;

D O I：

10.1016/j.msea.2020.140059

中图分类号：

TB3 [工程材料学];

学科分类号：

0805 ; 080502 ;

摘要：

For the first time, we report here that higher-order eight component Fe32.5-xCo10Ni25Cr15Mn5V10Al2.5Nbx = 5, 7.5, 10, and 12.5 at. %) eutectic high entropy alloys (EHEAs) are designed and developed by integrating thermodynamic simulation approach and non-equilibrium solidification processing technique. The developed EHEAs consist of FeCoNiCr-rich FCC solid solution phase and eutectics mixture between FCC solid solution phase and the Co2Nb-type Laves phase. The predicted microhardness of EHEAs for x = 7.5% and x = 10% by using artificial neural networks (ANNs) modeling is 501 H V, and 618 H V, respectively, which is in good agreement with experimentally measured values having less than 5% error.

引用

页数：8

共 38 条

[1] Use of artificial neural network for prediction of mechanical properties of α-Al2O3 particulate-reinforced Al-Si10Mg alloy composites prepared by using stir casting process [J].

Altinkok, Necat .

JOURNAL OF COMPOSITE MATERIALS, 2006, 40 (09) :779-796

[2] Effect of temperature on microstructure and texture evolutions during uniaxial compression of commercially pure titanium [J].

Bishoyi, B. D. ;

Sabat, R. K. ;

Sahoo, S. K. .

MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING, 2018, 718 :398-411

[3] Effect of temperature on microstructure and texture evolution during uniaxial tension of commercially pure titanium [J].

Bishoyi, B. D. ;

Sabat, R. K. ;

Sahu, J. ;

Sahoo, S. K. .

MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING, 2017, 703 :399-412

[4] Microstructural development in equiatomic multicomponent alloys [J].

Cantor, B ;

Chang, ITH ;

Knight, P ;

Vincent, AJB .

MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING, 2004, 375 :213-218

[5] Prediction of the Composition and Hardness of High-Entropy Alloys by Machine Learning [J].

Chang, Yao-Jen ;

Jui, Chia-Yung ;

Lee, Wen-Jay ;

Yeh, An-Chou .

JOM, 2019, 71 (10) :3433-3442

[6]

Chen S., 2018, ENTROPY, V20

[7] Microstructure exploration and an artificial neural network approach for hardness prediction in AlCrFeMnNiWx High-Entropy Alloys [J].

Dewangan, Sheetal Kumar ;

Samal, Sumanta ;

Kumar, Vinod .

JOURNAL OF ALLOYS AND COMPOUNDS, 2020, 823

[8]

Glicksman ME, 2011, PRINCIPLES OF SOLIDIFICATION: AN INTRODUCTION TO MODERN CASTING AND CRYSTAL GROWTH CONCEPTS, P1, DOI 10.1007/978-1-4419-7344-3

[9] A fracture-resistant high-entropy alloy for cryogenic applications [J].

Gludovatz, Bernd ;

Hohenwarter, Anton ;

Catoor, Dhiraj ;

Chang, Edwin H. ;

George, Easo P. ;

Ritchie, Robert O. .

SCIENCE, 2014, 345 (6201) :1153-1158

[10] Database on the mechanical properties of high entropy alloys and complex concentrated alloys [J].

Gorsse, S. ;

Nguyen, M. H. ;

Senkov, O. N. ;

Miracle, D. B. .

DATA IN BRIEF, 2018, 21 :2664-2678

← 1 2 3 4 →