Author ORCID Identifier

https://orcid.org/0009-0006-5943-0832

Date Available

9-12-2025

Year of Publication

2024

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Engineering

Department/School/Program

Mining Engineering

First Advisor

Dr. Joshua M. Werner

Second Advisor

Dr. John G. Groppo

Abstract

Electronic waste (e-waste) encompasses waste originating from electronic and electrical equipment. In 2022, 59.4 million metric tons of e-waste were generated, projected to increase to 74.7 million metric tons by 2030. Among the most valuable components within E-Waste are the printed circuit boards (PCBs), primarily composed of metals including copper (Cu), gold (Au), silver (Ag), cobalt (Co), nickel (Ni), bismuth (Bi), and various other base and precious metals. Notably, copper is the predominant element in PCBs, with concentrations exceeding those in their respective ores. The high demand for copper driven by the ongoing push towards greener technologies and its abundant presence in PCBs has prompted substantial interest in recycling e-waste products. The benefits of recycling are twofold; it not only provides an alternate avenue to meet the copper demand but also mitigates the environmental impact posed by e-waste disposal in landfills.

E-waste recycling technologies have undergone significant advancements in recent years, particularly in the development of various hydrometallurgical processes. The extraction process of copper from PCBs starts from crushing, grinding and beneficiation which separates the desirable components from the waste. Subsequently, the sequential application of leaching, solvent extraction, and electrowinning facilitates the efficient extraction of copper from PCBs, resulting in high-purity products. Initially, the solution containing Cu(II) species is employed to leach metallic copper from the e-waste, generating a monovalent copper-ammonia complex along with other leached impurities. Subsequently, this electrolyte undergoes multiple stages of solvent extraction to eliminate impurities and undesired divalent copper-ammonia complexes. The purified electrolyte is then directed to the electrowinning cell to produce high-grade copper through electrodeposition.

Previously, most researchers focused on Cu(II) based systems, and a few studied the Cu(I) enriched system to understand the kinetics using different ammonia-based electrolytes. This study delves into the optimization of parameters for leaching, solvent extraction, and electrowinning to achieve the highest possible Cu(I):Cu(II) ratio electrolyte with minimum impurities, which can produce pure copper cathode efficiently. These methods encompass the utilization of both acidic and alkaline electrolytes for. Recent investigations have underscored the increasing preference for alkaline electrolytes over acidic counterparts due to several advantages, including minimal equipment corrosion and the absence of acidic waste handling issues. Among alkaline electrolytes, ammonia-based copper solutions have garnered considerable attention owing to their myriad benefits. These advantages include enhanced selectivity for copper metal, reduced power consumption and equipment corrosion, and a more environmentally sustainable approach compared to conventional techniques. Considering the fact that copper extraction from E waste is still a developing technology, this study was focused on the development of a processing flowsheet by focus on unit operations involved in copper recycling.

A fundamental investigation was carried out to understand the solution chemistry of the Cu-NH3-SO4-2 system focusing on the effect of pH on copper solubility and optimization of parameters to achieve the higher Cu(I):Cu(II) in the electrolyte. As higher Cu(I):Cu(II) ratio is desired for the higher current efficiency during the electrowinning of copper. Moreover, a pourbaix diagram for the Cu-N-S system was also developed using the HSC Chemistry software for a wide range of Cu-NH3 species, unlike most other studies that were only focused on Cu(NH3)42+ (Cu(II)) as the dominant species. It was found that the Cu(NH3)2+ (Cu(I)) is the only species that exists for Cu(I) while the Cu(II) species dominate as Cu(NH3)42+ and Cu(NH3)52+ depending upon the pH of the solution. Copper precipitation was observed in the electrolyte at pH values less than 8.0 and the precipitation behavior increased as the pH became acidic. The highest Cu(I):Cu(II) ratio of 15.01 was observed at 10.05 pH and 4.0 M NH4OH and 0.25 M (NH4)2SO4 concentration.

From the leached sopper solution, the co-leached impurities and unwanted Cu(II) needs to be removed for higher purity of copper cathode and higher current efficiency. To do so, solvent extraction (SX) was used to remove metallic impurities, such as Al+3, Co+2, Pb+2, Sn+2, and Zn+2, and unwanted Cu(II) from the electrolyte solution. For the removal of impurities, there were three stages: loading, scrubbing, and stripping. During the loading stage, LIX-84I and ORFOM-SX-11 were used as organic diluents, respectively. pH, organic-to-aqueous ratio (O:A), and organic concentration were variables. The response surface analysis presented the optimum conditions for each variable for maximum removal of each metal were at pH 11, O:A 10:1, and organic concentration of 15%. At these optimized conditions 76% Al, 64% Co, 67% Cu(II) and Sn, 79% Pb, and 58% Zn were removed. Using these results from the loading experimentation, the metals were loaded onto the organic phase and scrubbed for ammonia removal using DI water to avoid excessive acid consumption. For ammonia scrubbing time and water to organic ratio (W:O) were variables and again the response surface analysis was used to find the optimum time of 34 minutes and W:O ratio of 0.9:1 for 99.65% ammonia scrubbing. At the last stage, final results from metallic loading and ammonia scrubbing were used to load and scrub the organic phase for acid stripping. At the stripping stage, sulfuric acid was used at acid to organic ratio of 1:1 to strip metals from the organic phase for organic recycling. Time and acid-to-organic ratio were kept as variables, and the optimization analysis showed that contact time of 15 minutes and 2M H2SO4 can remove 76% Cu(II). The recovery of other metallic impurities was not a success. The statistical analysis provided the equilibrium models for the loading, ammonia scrubbing and acid stripping which can be used to design the circuit and flowsheet for the solvent extraction process to eliminate impurities and unwanted Cu(II) from the leached electrolyte. A model was derived using the mass balance equation incorporating the distribution coefficient, which is based on the statistical equilibrium models to calculate the concentration of impurities and Cu(II) in aqueous and organic phases. Using the statistical models an Excel model was developed for the solvent extraction to achieve the 99% pure electrolyte which can be sent to electrowinning cell to get pure copper cathode efficiently. The model was designed to treat 1 ton/hr. of Cu(I) solution. The model provided that five loading and two stripping stages were needed to achieve the 99% purity leached solution.

For the final stage to achieve the pure copper cathode efficiently from the purified electrolyte diffusion coefficient was studied for Cu(I) and Cu(II) species. Diffusion coefficients for Cu(NH3)42+ and Cu(NH3)2+ were investigated using the linear sweep voltammetry (LSV) technique from the alkaline copper-ammonia-sulfate solution. The LSVs were performed at 25 0C, 35 0C and 45 0C for 20 g/L, 30 g/L and 40 g/L Cu(II) solution. The electrolyte was composed of varying concentrations of copper sulfate, 1.0M ammonium sulfate, 4.0M ammonium hydroxide, and 20ppm ammonium chloride. The LSVs were run at 50 RPM, 75 RPM, and 100 RPM over a range of temperatures and given copper concentrations. The diffusion coefficient was determined using limiting current values obtained from LSVs. It was noticed that the diffusion coefficient increased with an increase in the temperature and a slight decrease with an increase in the copper concentration in the electrolyte. Furthermore, a higher diffusion rate was observed for the cuprous ammonia complex compared to the cupric ammonia complex which proves that having higher Cu(I):Cu(II) ratio in the electrolyte favors the higher current efficiency of the system. The diffusion coefficient ranges for Cu(NH3)42+ and Cu(NH3)2+ are 5.09x10-06 to 8.11x10-06 and 5.61x10-06 to 9.24x10-06, respectively.

A COMSOL model was developed for rotating disk electrode (RDE) using all the statistical models obtained from fundamental solution chemistry and diffusion coefficients study. These predictive models were obtained using real-time experimental data and were expected to provide results close to reality. The COMSOL model recreated some aspects of the linear sweep voltammograms which we obtained experimentally for the diffusion coefficient calculations. This will enhance virtual experimentation saving the cost of extensive experimentation and equipment development.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2024.390

Funding Information

This study was supported by the National Science Foundation (NSF) under the grand number 2044719.

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