Shape characterization of copper metallic particles recovered from jig separation of e-wastes

Since copper (Cu) plays a vital role in the transition toward carbon neutrality due to its excellent electrical conductivity, environmental and economic advantages can be achieved by utilizing e-waste, which contains much more Cu metal than Cu ores. Therefore, the recovery of Cu from e-waste is crucial for ensuring sustainability and preventing the rapid depletion of natural resources. Due to the significant density difference between metals and plastics, gravity separation methods, such as jigging and shaking tables, can be efficiently applied at large scales. These methods are particularly attractive for e-waste recycling due to their low capital and operating costs. Besides, understanding e-waste materials at the particle-scale level can help improve the separation process by examining the behavior of each particle during separation. However, no literature currently examines particle shapes in the jig separation process for recovering Cu from e-waste. To fill this gap, this study explores the behavior of Cu particles in jig separation from e-waste through shape characterization of Cu particles. The fact that approximately 60% of the Cu in the feed material of the jig-heavy product consists of heavy, large, and round Cu particles shows that not only density and size are effective in stratification.

Authors

Institutions

Publication Details

Journal
Academia Engineering
Published
2024-10-07
DOI
https://doi.org/10.20935/acadeng7368
Primary Topic
Recycling and Waste Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Shape characterization of copper metallic particles recovered from jig separation of e-wastes

Zeynep Üçerler, Uğur Ulusoy, Fırat Burat, Halide Nur Dursun et al.
Academia Engineering
Recycling and Waste Management Techniques
article

Shape characterization of copper metallic particles recovered from jig separation of e-wastes

Zeynep Üçerler, Uğur Ulusoy, Fırat Burat, Halide Nur Dursun, Nazlım İlkyaz Dinç
article en

Abstract

Since copper (Cu) plays a vital role in the transition toward carbon neutrality due to its excellent electrical conductivity, environmental and economic advantages can be achieved by utilizing e-waste, which contains much more Cu metal than Cu ores. Therefore, the recovery of Cu from e-waste is crucial for ensuring sustainability and preventing the rapid depletion of natural resources. Due to the significant density difference between metals and plastics, gravity separation methods, such as jigging and shaking tables, can be efficiently applied at large scales. These methods are particularly attractive for e-waste recycling due to their low capital and operating costs. Besides, understanding e-waste materials at the particle-scale level can help improve the separation process by examining the behavior of each particle during separation. However, no literature currently examines particle shapes in the jig separation process for recovering Cu from e-waste. To fill this gap, this study explores the behavior of Cu particles in jig separation from e-waste through shape characterization of Cu particles. The fact that approximately 60% of the Cu in the feed material of the jig-heavy product consists of heavy, large, and round Cu particles shows that not only density and size are effective in stratification.

Academia EngineeringVol. 1(4)
Sivas Cumhuriyet Üniversitesi (TR), Istanbul Technical University (TR)
Openalex Percentile: Top 79%
Recycling and Waste Management Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.