Efficient Al Recovery from Aluminum Dross with Simultaneous AlN Separation by a Mechanical Method

Yujie Xue, Mingqi Zhang, Jizhi Zhou () and Yufeng Zhang ()
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Yujie Xue: School of Environmental Science and Technology, Nanjing Tech University, No. 30 Puzhunan Road, Nanjing 211816, China
Mingqi Zhang: School of Environmental and Chemical Engineering, Shanghai University, No. 99 Shangda Road, Baoshan District, Shanghai 200444, China
Jizhi Zhou: School of Environmental Science and Technology, Nanjing Tech University, No. 30 Puzhunan Road, Nanjing 211816, China
Yufeng Zhang: School of Environmental Science and Technology, Nanjing Tech University, No. 30 Puzhunan Road, Nanjing 211816, China

Waste, 2022, vol. 1, issue 1, 1-12

Abstract: Aluminum dross (AD) is a hazardous waste that contains valuable metallic Al and reactive aluminum nitride (AlN). The intergrowth of Al and AlN presents a challenge to Al recovery and AlN removal. In the current work, a mechanical milling method was developed to separate Al and AlN. Steel bars and balls were used as grinding media. The AD particle size decreased after milling and was distributed in the ranges 0.425–2 mm, 0.15–0.425 mm, 0.08–0.15 mm, and <0.08 mm. The particle size distribution was affected by the ball milling media and grinding time. Steel ball media had a better grinding effect on particles > 2 mm. After ball milling, the Dp0.08–2 mm size fraction accounted for approximately 90%. With changes in particle size, the element content of AD varied: the fraction of metallic Al decreased, while the fraction of Si increased. Metallic Al mainly existed in particles with size > 0.425 mm, accounting for 48.5%. AlN mainly existed in Dp0.15–0.425 mm, accounting for 64.9%. The optimal milling conditions achieved a 65% Al recovery rate and a 90% AlN separation efficiency. This work provides a promising approach for highly efficient pretreatment for AD recovery and AlN elimination in industrial applications.

Keywords: Al recovery; AlN seperation; ball milling (search for similar items in EconPapers)
JEL-codes: Q1 Q16 Q18 Q2 Q20 Q23 Q24 Q25 Q28 Q3 Q31 Q38 Q5 (search for similar items in EconPapers)
Date: 2022
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