Preparation of Low-alloy Steel Powders for Additive Manufacturing by VIGA and EIGA Gas Atomization

Lv Weiyan, Yang Fan, Han Guofeng, Wang Xiaoming, Yang Baijun

China Surface Engineering ›› 2020, Vol. 33 ›› Issue (5) : 115-122.

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China Surface Engineering ›› 2020, Vol. 33 ›› Issue (5) : 115-122. DOI: 10.11933/j.issn.1007-9289.20200819001

Preparation of Low-alloy Steel Powders for Additive Manufacturing by VIGA and EIGA Gas Atomization

  • Lv Weiyan, Yang Fan, Han Guofeng, Wang Xiaoming, Yang Baijun
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Abstract

Vacuum induction gas atomization (VIGA) and electrode induction gas atomization (EIGA) methods were used to prepare low alloy steel powder 12CrNi2 for additive manufacturing. The particle size distribution, sphericity, cross-sectional mor- phology and oxygen content of the powders were compared. The results show that the two powders present an approximate sphe- ricity within an trace satellite powder accompanied in the VIGA powders. The median particle size d50 of VIGA and EIGA powder in the range of 0~ 53 μm according to the particle size distribution curve shows that the values are as 40. 7 and 34. 8 μm respec- tively, and the values are as 126. 3 and 127 μm in the range of 53~ 180 μm respectively. The combination state of Fe 2p and ox- ygen element was analyzed by XPS, and the results show that the relative content of metallic Fe0 in surface oxide film of EIGA powder is higher than that of VIGA powder, and the relative content of Fe2+ and Fe3+ in oxidation state is lower. In addition, comparison of the oxidation peaks of Fe 2p at different sputtering times indicating that oxygen element penetrates deeper in VIGA powder and may have formed oxide compounds and is confirmed by the subsequent phase structure analysis of XRD.

Key words

additive manufacturing; gas atomization; metal powder; particle size distribution; oxidation

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Lv Weiyan, Yang Fan, Han Guofeng, Wang Xiaoming, Yang Baijun. Preparation of Low-alloy Steel Powders for Additive Manufacturing by VIGA and EIGA Gas Atomization[J]. China Surface Engineering, 2020, 33(5): 115-122 https://doi.org/10.11933/j.issn.1007-9289.20200819001

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Funding

Supported by National Key Research and Development Program of China (2016YFB1100204)
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