Chemical Industry and Engineering Progress ›› 2025, Vol. 44 ›› Issue (2): 706-716.DOI: 10.16085/j.issn.1000-6613.2024-0296

• Chemical processes and equipment • Previous Articles     Next Articles

Numerical simulation of chemical vapor deposition in polycrystalline silicon reduction furnace

WANG Siyi1(), XU Jianliang1, DAI Zhenghua1,2(), WU Guoyi3, WANG Fuchen1   

  1. 1.Shanghai Coal Gasification Engineering Technology Research Center, East China University of Science and Technology, Shanghai 200237, China
    2.College of Chemical Engineering, Xinjiang University, Urumqi 830046, Xinjiang, China
    3.Lanzhou Lanshi Heavy Equipment Co. , Ltd. , Lanzhou 730300, Gansu, China
  • Received:2024-02-20 Revised:2024-03-29 Online:2025-03-10 Published:2025-02-25
  • Contact: DAI Zhenghua

多晶硅还原炉气相沉积反应数值模拟

王思懿1(), 许建良1, 代正华1,2(), 武国义3, 王辅臣1   

  1. 1.华东理工大学上海煤气化工程技术研究中心,上海 200237
    2.新疆大学化工学院,新疆 乌鲁木齐 830046
    3.兰州兰石重型装备股份有限公司,甘肃 兰州 730300
  • 通讯作者: 代正华
  • 作者简介:王思懿(1999—),女,硕士研究生,研究方向为多晶硅反应过程模拟优化。E-mail:1072474707@qq.com
  • 基金资助:
    国家重点研发计划(2022YFB4101500);新疆维吾尔自治区自然科学基金重点项目(2023D01D02);中央高校基本科研业务费专项资金(2022ZFJH04)

Abstract:

Polysilicon is a key material for solar panels in the field of photovoltaics, and the modified Siemens method is a common method for preparing polysilicon, with the core equipment being a reduction furnace. The structure of the reduction furnace is complex, and the furnace contains complex physicochemical phenomena. In order to study the polycrystalline silicon vapor deposition characteristics, a reactor model with 12 pairs of rods was established, coupling the vapor phase reaction and surface reaction mechanisms, and the velocity, temperature, and silicon deposition rate distributions under different conditions were discussed in detail. Response surface methodology coupled with two variables, inlet velocity and temperature, was used to explore the combined effects on the average silicon deposition rate and the feedstock conversion rate. The results showed that higher inlet velocity and temperature were favorable to increase the heat and mass transfer rate and the average silicon deposition rate. Temperature was the main factor influencing the process and the effect was significant in the low temperature region. Due to the increase of inlet velocity and the decrease of feedstock conversion, the optimal process conditions were predicted to be 1460—1500K and 25—36m/s, taking into account the effects of average deposition rate (≥10μm/min) and feedstock conversion (≥10%).

Key words: polysilicon, chemical vapor deposition, heat transfer, computational fluid dynamics, optimization

摘要:

多晶硅是光伏领域太阳能电池板的关键材料,改良西门子法是制备多晶硅的常用方法,其核心设备为还原炉。还原炉结构复杂,炉内包含复杂的物理化学现象。为了研究多晶硅气相沉积特性,本文建立了一个12对棒的反应器模型,耦合气相反应及表面反应机理,详细讨论了不同条件下的速度、温度、硅沉积速率分布。采用响应面法耦合入口速度和温度两个变量探究其对硅平均沉积速率以及原料转化率的综合影响。结果表明,较高的入口速度和温度有利于提高传热传质速率,提高硅平均沉积速率。温度为该过程的主要影响因素且在低温区域影响显著。由于入口速度提高,原料转化率降低,兼顾平均沉积速率(≥10μm/min)和原料转化率(≥10%)的影响,预测最佳工艺条件温度为1460~1500K、入口速度为25~36m/s。

关键词: 多晶硅, 化学气相沉积, 传热, 计算流体力学, 优化

CLC Number: 

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