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Optimization of the Electrochemical Extraction and Recovery of Metals from Electronic Waste Using Response Surface Methodology Luis Alejandro Diaz, Gemma G. Clark, and Tedd Edward Lister Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.7b01009 • Publication Date (Web): 08 Jun 2017 Downloaded from http://pubs.acs.org on June 14, 2017

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Optimization of the Electrochemical Extraction and Recovery of Metals from Electronic Waste Using Response Surface Methodology Luis A. Diaz*, Gemma G. Clark, and Tedd E. Lister

Biological and Chemical Processing Department Idaho National Laboratory P.O Box 1625 Idaho Falls, ID 38415-3731, USA Phone: (1) 208-526-7411 Fax: (1) 208-526-5086 e-mail: [email protected]

A research paper submitted to Industrial & Engineering Chemistry Research for consideration for publication

* Corresponding Author. Tel.: +1 208 526 7411. Fax: +1 208 526 5086. E-mail address: [email protected] (L.A Diaz).

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Abstract

The rapid growth of electronic waste can be viewed as an environmental threat, and as an attractive source of minerals that can reduce the mining of natural resources. In this paper response surface methodology was used to optimize an electrochemical process for the extraction and recovery of base metals from electronic waste using a mild oxidant (Fe3+). Through this process an effective extraction of base metals can be achieved enriching the concentration of precious metals and significantly reducing environmental impacts and operational costs associated with the waste generation and chemical consumption. The optimization was performed using a bench-scale system specifically designed for this process. Operational parameters such as flow rate, applied current density and iron concentration were optimized to reduce the specific energy consumption of the electrochemical recovery process to 1.94 kWh per kg of metal recovered.

Key words: Electronic waste, Electrochemical recovery, Metal recycling, Process optimization

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1. Introduction The global need for proper disposal and treatment of electronic waste (e-waste) is buoyed by rapid technology developments, decreasing lifetime of electronic devices, and declining mineral resources.1 Along with the direct environmental impacts associated to the landfill disposal of increasing amounts of electronic waste,2, 3 there are side environmental effects that come with the mining and exploitation of natural resources to supply the demand of raw materials required for the manufacturing of new electronic devices.4 Base metals (metals that are not considered precious, such as Cu, Sn, Ni, Zn, and Pb) and value metals (Ag, Au, and Pd) contained within e-waste compose approximately 20 wt%, mainly present in printed circuit boards (PCBs) as part of the circuitry, solders, capacitors, and connectors.5, 6 Hence, the high content of base and value metals in electronic waste provide a valuable source for the recovery and recycle of metals, which can be re-used in new electronic devices or different applications. Some of the environmental and economic advantages of obtaining metals from e-waste include energy savings, reduction of landfill disposal, reduction of mining dependence, and market stabilization.2, 4, 7, 8 Moreover, a sustainable electronics industry of the near future will need to recoup materials from end-of-life (EOL) devices using processes that are clean and efficient. Nevertheless, technological challenges have also been recognized for the processing of ewaste and the comprehensive recovery of metals .9 The complex e-waste matrix, where the metals are integrated inside polymeric materials, complicates the efficient extraction of metals by means of the current pyro-metallurgical, hydrometallurgical, and combination of these processes.2, 6, 10 In terms of energy consumption and environmental impact, hydrometallurgical processes are claimed as more energy efficient and greener than pyro-metallurgical extraction.11 However, the extensive use of reagents and the generation of effluents (high liquid to solid ratios

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L/S) play against the overall cost and a neat environmental advantage of the process 12, 13. While over 80% of the total recoverable value of metals falls on the precious metals (Ag, Au, and Pd),14-16 more than 95% of the total metals present on PCBs (Cu>>Sn> Fe, Zn, Ni, and Pb) are base metals.17 Therefore, a complete recovery of the value metals without the extraction of the base metals is not possible, as the base metals are less noble in the galvanic series than the precious metals. In a conventional hydrometallurgical process this situation is turned into an extensive consumption of chemicals and additional waste generation. Electrochemically mediated processes have been proposed for the regeneration of the oxidants required for the metals extraction.5, 18-21 This approach allows the re-use of the leaching solution, significantly reducing the addition of new chemicals and the amount of waste generated. In previous work, an electrochemical recovery (ER) process was proposed as the core of a comprehensive process for the recovery of value metals and critical materials from electronic waste.5, 15 In this process a mild oxidant (Fe3+) generated in the anode of an electrochemical cell is circulated through a packed column loaded with milled electronic waste. The selective oxidation of base metals can be achieved without attacking Au and Pd, allowing their enrichment in the remaining electronic waste solid matrix. The leaching solution is recirculated back to the electrochemical cell where the base metals are electrowon on the cathode. Process times can be significantly reduced as metals extraction and recovery are performed simultaneously. Whereas Ag can also been oxidized during the base metals extraction, the galvanic reactions taking place within the packed column allows an extraction sequence in which the metals are extracted following the galvanic series. In this scenario Ag, the most noble metal oxidized by Fe3+, is the last metal leaving the packed column.15 The use of a chloride environment during the ER process takes advantage of the formation and low solubility 4 ACS Paragon Plus Environment

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of AgCl to keep most of the Ag inside the packed column and selectively recover it in a separate step. A diagram of the ER process is shown in Fig. 1. Precious metal extraction assessments using acid thiourea leaching on the ER treated material and untreated material, showed an increase over twenty times the extraction efficiency for Ag, Au, and Pd for ER treated material.15 Notwithstanding the promising results of the electrochemical mediated processes, further studies and optimization are required prior to scale-up.2 Parameters, such as oxidant concentration, leachate flow rate, and applied current have a direct effect in the extraction kinetics, mass transfer of metal extraction and deposition, and in the polarization of the electrodes leading to higher cell voltages and energy consumption. In a previous work published by this group,15 it was reported that 93% of the base metals were extracted after processing 70 g of milled electronic waste for 35 hours with the ER process. For this test 0.2 M Fe(2+/3+) in 0.5 M HCl solution at 3 mL min-1 and an applied current of 13.89 mA cm-2, were used. Under these conditions specific energy consumption in the electrochemical cell of 3.45 kWhr per kg of base metal recovered was obtained. Specific energy consumption was found to be affected by several factors: deposition of less noble metals, such as Sn, Ni, and Pb, where evolution of hydrogen (reduction of hydrogen protons to form hydrogen gas) occurs as a side reaction, oxidation of unreduced metals to higher valence states (eg. Sn2+ to Sn4+), and the reduction at the cathode of unreacted oxidant passed through the column (Fe3+ to Fe2+). Based on similar chemistry but using a different extraction configuration, Fogarasi et.al 18 studied the effect of iron concentration and current density in the performance of the process. After 12 h of processing 500 g of PCBs with 4 L of a 0.37 M Fe(2+/3+) in 0.3 M HCl solution at 4 mA cm-2, a specific energy consumption of 1.75 kWh per kg of base metal recovered was observed. However, the reported experiment did not achieve the complete extraction of base metals and the optimization study did 5 ACS Paragon Plus Environment

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not account for the effect of the leachate flow rate in the mass transfer of the extraction and deposition processes. In this paper, response surface methodology (RSM) was applied in order to study the relationship and significance of three process control factors (mediator concentration, leachate flow rate, and applied current density) in the performance of the ER process. The RSM uses statistical and mathematical techniques for the development of empirical multivariable models based on an experimental design for the optimization of one or more response variables. 22 Although RSM is not intended to substitute a complete phenomenological understanding of the processes involved in the electrolyzer and extraction columns, RSM has been widely used for the optimization of different chemical processes and in metal extraction to optimize the extraction efficiency.23, 24 The use of RSM and an adequate experimental design allow identifying the significance of controllable parameters and overall effects with an optimum number of experiments. Moreover, there is limited work in the process optimization as a whole (extraction and recovery). In this work, extraction and recovery of base metals are simultaneously optimized by evaluation of three response variables (specific energy consumption, cathodic Faraday efficiency, and metal recovery rate) in the ER process. The optimization results were verified by several processing cycles through a series of packed columns which allowed a complete removal of base metals in a semi-continuous process. 2. Materials and methods 2.1 Chemicals and Materials The milled non-ferromagnetic fractions of waste cell phone materials (0.31 mm median particle size), obtained after magnetic separation of shredded cell phone material, were provided

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by Advanced Recovery Inc. Before shredding, batteries were manually removed. The metal composition of the electronic waste in wt% (Cu 19.38%, Sn 1.95%, Zn 1.4%, Pb 0.17%, Ni 0.82%, and Ag 0.3%), used for the base metals extraction, was reported in a previous work.15 Leaching solutions were prepared in deionized water (18 MΩ-cm) using American Chemical Society (ACS) grade chemicals: FeCl2.4H2O (Fisher scientific, 99 to 102%), CuCl2.2H2O (Fisher scientific), and HCl (Fisher scientific, certified ACS plus). 2.2 Experimental equipment A scheme of the experimental equipment used for the electrochemical recovery of metals from electronic waste is shown in Fig. 1. An in-house designed and constructed trough-flow electrochemical cell configuration was employed. For the first part of the experimentation (experimental design), solution drawn from the anode side was pumped through a 10 cm long x 2.54 cm (1” OD) clear Tygon column packed with 20 g of milled cellphone material obtained after the separation of the batteries and ferromagnetic fragments. After leaving the column the leaching solution was returned to the cathode section of the electrochemical cell. The cathode, which consisted of a 7.5 cm by 6 cm 316 stainless (1/4” thick) steel medium grade wool, was attached to a 304SS bus bar so that the wool cathode was suspended in the bulk of the solution for easy removal/replacement. The submerged area was 36 cm2 and new clean wool cathodes were used for each experiment (for experimental consistency). At the other end of the cell, the anode was composed of two 6 cm x 6 cm pieces of carbon felt woven together with a Pt wire which also served as the current collector. The distance between the anode and the cathode was 3.5 cm and no separator (membrane) was positioned between the cathode and the anode.

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To start each experiment, 310 mL of the Fe leaching solution in 0.5 M HCl was freshly prepared at the desired concentration for Fe ions from FeCl2.4H2O. A small amount of Cu (0.025 M CuCl2 equivalent to 0.49 g of Cu) was added, to all the leaching solution, to be reduced at the cathode while the leachate starts coming out of the packed column. Cu addition was necessary to avoid the evolution of hydrogen on the cathode at the beginning of the experiment in the absence of any leached metal. Having the same concentration of Cu for all the starting solutions will have the same effect in the response variables for all the optimization experiments. After loading the solution into the electrochemical cell a Cole Parmer MasterFlex C/L peristaltic pump was used to deliver the desired flow rate of solution through one packed bed and back to the electrochemical reactor. The desired current density was applied to the electrochemical cell using a Princeton Applied Research Model 273A galvanostat/potentiostat. Leaching solution aliquots were taken from the three way valves V-1 and V-5 in Fig. 1 every 30 minutes to measure the concentration of Fe3+ at the inlet and outlet of the packed column. 20-30 µL were sampled from the aliquot for Fe3+analysis and the rest was returned to the system. Fe3+ concentration was measured by spectrometric determination at 500 nm after complexation with 5-sulfosalicilic acid using a Barnstead Turner SP-830 spectrophotometer. 25 The experiments were stopped when the Fe3+ conversion (reduction to Fe2+) through the column decreased to 50%, or after completing 8 hours of operation. At the beginning of the experiments Fe3+ conversions were ca. 100 %. Based on the results reported in a previous work,15 it was expected that once Fe3+ conversion decreased to 50%, over 80% of the base metals had been extracted while most of the Ag still remained on the packed column. Weight of recovered metal was obtained after separation of the metal from the cathode through sonication in deionized water and the weight of the powder deposit and the cathode before and after deposition. Elemental analysis of recovered metal samples, digested in

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50% HNO3, was performed using an inductive coupled plasma mass spectrometer Agilent 7900 ICP-MS. Verification of the optimal conditions and complete base metals extraction was performed using two columns in series (Fig. 1). In this configuration the first column, which reaches complete extraction first, can be substituted for a new column that will take the second position in the series. This configuration aims to maintain the mass transfer zone inside the packed beds, and increase utilization of the electro-generated oxidant. 2.3 Experimental design A three factors, three levels Box-Behnken experimental design with three repetitions in the central point was used to analyze the statistical significance and effects of the current density (X1), leachate flow rate (X2), and total Fe concentration (X3) in the specific energy consumption (Y1), Cathodic Faraday efficiency (Y2), fraction of the current used in the deposition of metals, and metals recovery rate (Y3) by means of RSM. The value of the response variables were calculated using Equations 1 to 3:  =

 (1)



 =   =

∗2 (2)  ∗  ∗ 

 (3)  ∗ 60

where MDeposit is the weight of the electrowon metal, I is the current in A, t is the process time in seconds, F is the Faraday constant (96485 C mol-1), and Mw is the molecular weight of

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the deposit. To simplify calculations of the Faraday efficiency (Equation 2), the molecular weight of the deposited material was assumed as that of Cu, which represent ca. 90% in weight of the recovered deposit.15 The experimental design factors and levels are presented in Table 1. Among the main considerations to choose the Box-Behnken experimental design are that this design has the lowest number of experiments required for three factors, three levels analysis (15), with equally spaced intervals between the levels26, and that the Box-Behnken design does not include factor combinations at the vertex of the process space, which avoid the testing of extreme conditions (e.g. high current density, low Fe concentration, and low flow rates, in coded units X1=1, X2=-1, X3=-1) that could lead to high electrode polarization and the appearance of undesired reactions such as oxygen and chlorine gas evolution. The experimental design is shown in Table 2. Experimental data analysis was performed using the trial version of Minitab 17. Analysis of variance (ANOVA) was used to establish statistical significance of the individual factors and interactions in the variability of the response variables with a 95% confidence level (pvalue