Solid-liquid equilibrium of the Ga-In-Ga-Sb system and artificial neural network prediction

被引:0
|
作者
Wei, Wu [1 ]
Luming, Yan [1 ]
Ruiwu, Peng [1 ]
Nianyi, Chen [1 ]
Jinwei, Zhang [1 ]
机构
[1] Chinese Acad of Sciences, Shanghai, China
关键词
Composition - Computer simulation - Differential thermal analysis - Gallium alloys - Liquid phase epitaxy - Microanalysis - Neural networks - Phase equilibria;
D O I
暂无
中图分类号
学科分类号
摘要
The Ga-In-As-Sb solid-liquid equilibrium was studied by experimental measurement and by computer prediction. The liquidus and solidus data are determined by differential thermal analysis and by liquid-phase epitaxial growth respectively. Artificial neural networks, trained by use of the experimental data, have been used to predict liquidus and solidus data. The cross-validation method is also employed to get rid of overfitting.
引用
收藏
页码:305 / 308
相关论文
共 50 条
  • [31] Solid-Liquid Equilibrium in Co-Amorphous Systems: Experiment and Prediction
    Zemankova, Alzbeta
    Hassouna, Fatima
    Klajmon, Martin
    Fulem, Michal
    MOLECULES, 2023, 28 (06):
  • [32] Prediction of the thermodynamic properties for the Ga-Sb-Pb ternary system
    Manasijevic, D
    Zivkovic, D
    Zivkovic, Z
    CALPHAD-COMPUTER COUPLING OF PHASE DIAGRAMS AND THERMOCHEMISTRY, 2003, 27 (04): : 361 - 366
  • [33] SOLID-LIQUID EQUILIBRIUM IN THE LITHIUM-LITHIUM HYDRIDE SYSTEM
    MESSER, CE
    DAMON, EB
    MAYBURY, PC
    MELLOR, J
    SEALES, RA
    JOURNAL OF PHYSICAL CHEMISTRY, 1958, 62 (02): : 220 - 222
  • [34] Solid-liquid equilibrium in the system propanoic acid-formamide
    Sedlakova, Zuzana
    Malijevska, Ivona
    Bures, Michal
    COLLECTION OF CZECHOSLOVAK CHEMICAL COMMUNICATIONS, 2007, 72 (07) : 899 - 907
  • [35] SOLID-LIQUID EQUILIBRIUM DIAGRAM FOR ARGON-METHANE SYSTEM
    VANTZELFDE, P
    OMAR, MH
    LEPAIRSC.HG
    DOKOUPIL, Z
    PHYSICA, 1968, 38 (02): : 241 - +
  • [36] Development of NOx reduction system utilizing artificial neural network (ANN) and genetic algorithm (GA)
    Shin, Yeonju
    Kim, Ziehyun
    Yu, Jihye
    Kim, Geonjung
    Hwang, Sungwon
    JOURNAL OF CLEANER PRODUCTION, 2019, 232 : 1418 - 1429
  • [37] Prediction of degree of particle misplacement in liquid solid fluidization using artificial neural network
    Tripathy, Alok
    Bagchi, Subhankar
    Biswal, S. K.
    Meikap, B. C.
    SEPARATION SCIENCE AND TECHNOLOGY, 2020, 55 (01) : 68 - 80
  • [38] Performance prediction of solid desiccant rotary system using artificial neural network
    Mishra, V. K.
    Singh, R. P.
    Das, R. K.
    1ST INTERNATIONAL CONFERENCE ON CONTEMPORARY RESEARCH IN MECHANICAL ENGINEERING WITH FOCUS ON MATERIALS AND MANUFACTURING (ICCRME-2018), 2018, 404
  • [39] On the application of artificial neural network for modeling liquid-liquid equilibrium
    Moghadam, M.
    Asgharzadeh, S.
    JOURNAL OF MOLECULAR LIQUIDS, 2016, 220 : 339 - 345
  • [40] Prediction of Effluent Temperature of Coolant in Cogeneration System Based on GA-BP Neural Network
    Cao, Ling
    Wang, Chaofan
    Qin, Yunjing
    ADVANCES IN MATERIALS, MACHINERY, ELECTRONICS III, 2019, 2073