Process parameter optimization in Czochralski growth of silicon ingots: a Monte Carlo-finite element coupled model

被引:0
|
作者
Dezfoli, Amir Reza Ansari [1 ,2 ]
Maurya, Swami Nath [1 ]
Adabavazeh, Zary [2 ]
Huang, Yi-Jen [3 ]
机构
[1] Natl Chin Yi Univ Technol, Dept Intelligent Automat Engn, Taichung 41170, Taiwan
[2] Natl Chin Yi Univ Technol, PhD Program Grad Inst Precis Mfg, Taichung 41170, Taiwan
[3] Natl Chin Yi Univ Technol, Dept Chem & Mat Engn, Taichung 41170, Taiwan
关键词
Czochralski process optimization; Monte Carlo optimization; Finite element modeling; Defect minimization; Thermal management; GAS-FLOW; FURNACE; DESIGN; OXYGEN;
D O I
10.1007/s00170-025-15323-2
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Czochralski (Cz) process is a crucial method for producing high-quality single-crystal silicon for semiconductor applications. This study introduces a Monte Carlo-finite element (MC-FE) optimization model to enhance Cz puller performance by refining five key parameters: crystal rotation speed, crucible rotation speed, insulation thermal conductivity, melt level, and thermal gap. A finite element model has been developed to incorporate conduction, convection, and radiation heat transfer, with a segregated solver employed to simulate silicon ingot growth. The MC-FE optimization reduced the objective function from 1.0 to 0.13 with an 87% improvement, achieving a flatter crystal front with maximum deflection decreasing from - 36.0 to - 10.4 mm. The optimized process increased the melt temperature from 1442 to 1517 degrees C at a 10 mm crystal length, enhancing thermal gradient stability. The V/G ratio, important for defect minimization, was flattened from a steep drop of 0.205 to 0.098 mm/min<middle dot>K to a more uniform 0.185 to 0.158 mm/min<middle dot>K range. Optimized parameters, including an increased crystal rotation speed of 9 RPM and a reduced thermal gap of 10 mm, contributed to a well-defined hot-cold thermal zone separation that supports stable crystal growth. These findings demonstrate the effectiveness of MC-FE optimization in improving the efficiency and quality of large-scale silicon crystal growth in semiconductor manufacturing.
引用
收藏
页码:2935 / 2946
页数:12
相关论文
共 50 条
  • [1] A coupled kinetic Monte Carlo-finite element mesoscale model for thermoelastic martensitic phase transformations in shape memory alloys
    Chen, Ying
    Schuh, Christopher A.
    ACTA MATERIALIA, 2015, 83 : 431 - 447
  • [2] Finite element numerical simulation and control parameter of czochralski silicon monocrystal during shoulder growth process
    Zhang, J. (weeine@gmail.com), 1600, Chinese Ceramic Society, Baiwanzhuang, Beijing, 100831, China (42):
  • [3] Geometric optimization of a solar cubic-cavity multi-tubular thermochemical reactor using a Monte Carlo-finite element radiative transfer model
    Valades-Pelayo, P. J.
    Romero-Paredes, H.
    Arancibia-Bulnes, C. A.
    Villafan-Vidales, H. I.
    APPLIED THERMAL ENGINEERING, 2016, 98 : 575 - 581
  • [4] Robust nonlinear feedback-feedforward control of a coupled kinetic Monte Carlo-finite difference simulation
    Rusli, E
    Drews, TO
    Ma, DL
    Alkire, RC
    Braatz, RD
    ACC: PROCEEDINGS OF THE 2005 AMERICAN CONTROL CONFERENCE, VOLS 1-7, 2005, : 2548 - 2553
  • [5] Robust nonlinear feedback-feedforward control of a coupled kinetic Monte Carlo-finite difference simulation
    Rusli, E
    Drews, TO
    Ma, DL
    Alkire, RC
    Braatz, RD
    JOURNAL OF PROCESS CONTROL, 2006, 16 (04) : 409 - 417
  • [6] A FULLY PARALLEL COUPLED MONTE CARLO-FINITE VOLUME METHOD FOR COUPLED CONDUCTION-RADIATION HEAT TRANSFER IN MULTIDIMENSIONAL GEOMETRIES
    Sit, Abhishek
    Talukdar, Prabal
    COMPUTATIONAL THERMAL SCIENCES, 2020, 12 (06): : 509 - 527
  • [7] Kinetic Monte Carlo simulation for the void defects formation in Czochralski silicon growth
    Lee, Sang Hun
    Cho, Hyun Jong
    Oh, Hyun Jung
    Kim, Do Hyun
    MOLECULAR SIMULATION, 2010, 36 (03) : 240 - 245
  • [8] Diameter Prediction of Silicon Ingots in the Czochralski Process Based on a Hybrid Deep Learning Model
    Zhao, Xiaoguo
    Liu, Ding
    Yan, Xiaomei
    CRYSTALS, 2023, 13 (01)
  • [9] Kinetic Monte Carlo simulation for the striation distribution of void defects in Czochralski silicon growth
    Lee, Sang Hun
    Oh, Hyun Jung
    Kim, Do Hyun
    MOLECULAR SIMULATION, 2010, 36 (09) : 663 - 669
  • [10] Finite element modeling of rolling process and optimization of process parameter
    Datta, A. K.
    Das, G.
    De, P. K.
    Ramachandrarao, P.
    Mukhopadhyaya, M.
    MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING, 2006, 426 (1-2): : 11 - 20