Harmless extraction process of electronic waste metal resources based on green chemical method

Abstract

The invention provides an electronic waste metal resource harmless extraction process based on a green chemical method, and aims to realize efficient recovery and harmless treatment of precious metals and common metals in electronic wastes. According to the process, low-toxicity organic acid (such as citric acid and oxalic acid) is adopted as a solvent, and metal dissolution and selective complexation are carried out under the condition of normal temperature or low temperature. By regulating and controlling the pH value of the solution and the concentration of the complexing agent, efficient separation and extraction of metal are achieved. The system integrates an automatic monitoring module, the dissolving, electrolyzing and precipitating processes are adjusted in real time, meanwhile, a cyclic waste liquid treatment system is adopted, and water resource consumption and waste liquid discharge are effectively reduced. Compared with a traditional high-temperature smelting and acid leaching process, the method has the advantages that energy consumption and environmental pollution are greatly reduced, and the metal recovery rate and economic benefits are improved. The process is suitable for treating various electronic wastes, conforms to the green and environment-friendly concept, and has a wide market application prospect.

Description

Technical Field

[0001] The present invention relates to the technical field of waste treatment, and more particularly to a harmless extraction process of metal resources from electronic waste based on a green chemical method. Background Art

[0002] With the development of science and technology and the rapid replacement of electronic products, the amount of electronic waste in the world continues to grow, becoming an important environmental and resource issue facing modern society. Electronic waste not only contains a large amount of precious metals and common metal resources, such as gold, silver, copper, aluminum and palladium, but also contains toxic and hazardous substances, such as lead, mercury and hexavalent chromium. If these wastes are not handled properly, they will not only cause environmental pollution, but also waste precious metal resources.

[0003] Traditional electronic waste treatment processes usually rely on physical separation, high-temperature incineration or acid leaching metallurgical processes. However, these methods have obvious defects:

[0004] 1. High energy consumption and pollution:

[0005] High-temperature smelting requires a lot of energy and releases greenhouse gases and toxic gases such as sulfur dioxide and dioxins, causing air pollution.

[0006] The acid leaching method uses highly corrosive chemicals such as concentrated sulfuric acid and nitric acid, which generates a large amount of acidic waste liquid, posing a serious threat to the environment.

[0007] 2. Waste of resources:

[0008] Traditional processes are usually unable to completely recover precious metals, resulting in some high-value metal resources being lost with the waste slag.

[0009] 3. Complex operation and potential safety hazards:

[0010] The high temperature and high pressure environment increases the difficulty and risk of workers' operations and makes safety accidents more likely to occur.

[0011] 4. Low economic benefits:

[0012] High energy consumption and complex process flow lead to a decline in the economic benefits of enterprises.

[0013] Therefore, developing a green and efficient process for harmless extraction of metal resources from electronic waste has important social and economic value. Summary of the invention

[0014] In order to solve the above problems, the present invention provides a harmless extraction process of metal resources from electronic waste based on green chemistry, which realizes efficient recovery of precious metals and other metals by using green solvents, coordination complex reactions and efficient separation technologies, and solves the high pollution and high energy consumption problems existing in traditional processes to achieve the above purpose;

[0015] The present invention provides the following technical solution, which mainly includes:

[0016] The harmless extraction process of metal resources from electronic waste based on green chemistry includes the following steps:

[0017] (1) Pretreatment of electronic waste: crushing and screening the electronic waste, and separating the ferromagnetic materials from other materials through magnetic material separation;

[0018] (2) Green solvent extraction: using green solvents and complex reactions to extract target metal resources through a diffusion-reaction model;

[0019] (3) Precipitation and selective separation of metals: Selective separation and recovery of metals are achieved through the solubility equilibrium formula and the phase distribution of multi-component systems;

[0020] (4) Treatment and recycling of waste liquid: Use membrane separation and nanofiltration technology to treat waste liquid and recover residual resources in the waste liquid;

[0021] (5) Electrolytic refining of metals: High purity metals are obtained by electrolytic refining process, and the current and charge distribution are controlled by modified Faraday's law;

[0022] (6) Intelligent control and optimization: The particle swarm optimization algorithm is introduced to optimize the process parameters such as temperature, solution ratio and metal extraction time in real time.

[0023] Preferably, the pretreatment process of electronic waste adopts the screening efficiency model

[0024]

[0025] Where S f is the screening efficiency, d is the particle diameter, d0 is the sieve hole diameter, and k is the screening coefficient.

[0026] Preferably, the separation of magnetic materials adopts a dynamic magnetic field model

[0027] B(t)=B0sin(ωt)

[0028] Where B(t) is the magnetic induction intensity at time t, B0 is the initial magnetic induction intensity, and ω is the magnetic field frequency.

[0029] Preferably, the metal complexation reaction uses the coordination field energy model

[0030]

[0031] Where \ΔE is the coordination field energy, D q is the field strength parameter, e g and They represent the number of electron energy level occupancy.

[0032] Preferably, the metal precipitation process is governed by the solubility equilibrium equation:

[0033]

[0034] Where K sp is the solubility product constant, ΔH° and ΔS° are the standard enthalpy change and standard entropy change, respectively.

[0035] Preferably, in the wastewater treatment process, membrane separation uses a nanofiltration model

[0036] J=L p (ΔP-σΔπ)

[0037] Where J is the permeate flow rate, L p is the permeability of the membrane, ΔP is the pressure difference, σ is the reflection coefficient, and Δπ is the osmotic pressure difference.

[0038] Preferably, electrorefining uses the modified Faraday's law:

[0039]

[0040] Where M is the metal mass, Z is the electrochemical equivalent, F is the Faraday constant, I is the current, t is the time, n is the number of electrons, η c is the current efficiency.

[0041] Preferably, a particle swarm optimization algorithm is used to optimize the process parameters:

[0042] v i (t+1)=wv i (t)+c1r1(p i -x i (t))+c2r2(gx i (t))

[0043] where v i (t+1) is the velocity of particle i, w is the inertia weight, c1 and c2 are acceleration coefficients, and r1 and r2 are random numbers.

[0044] Preferably, a dynamic ratio strategy is adopted in the green solvent selection process so that the complexing degree of the solution is optimized as the temperature and concentration change.

[0045] Preferably, the system is able to perform real-time model retraining during the monitoring process and automatically update separation and extraction strategies based on the type of material detected.

[0046] It can be seen from the above technical solution that compared with the prior art, the present invention has the following beneficial effects:

[0047] (1) Green and environmentally friendly:

[0048] This process uses low-toxic solvents (such as citric acid and acetic acid), reduces the use of traditional strong acids and strong bases, reduces the risk of environmental pollution, and achieves harmless treatment.

[0049] The waste liquid can be recycled after neutralization treatment, reducing water consumption and emissions.

[0050] (2) High metal recovery rate and purity:

[0051] By optimizing dissolution conditions and selective complexation reactions, high recovery rates and high purity of metals such as gold, silver, and copper can be achieved, ensuring effective utilization of resources.

[0052] (3) Low energy consumption and efficient process:

[0053] Compared with traditional metallurgical extraction processes, this process performs dissolution and separation at lower temperatures, reducing energy consumption and improving overall operating efficiency.

[0054] (4) Simple process and stable operation:

[0055] The automated electrolysis and precipitation separation process is used to reduce manual intervention, operational complexity and the risk of errors.

[0056] (5) Strong adaptability:

[0057] It is suitable for processing a variety of electronic waste (such as circuit boards, waste chips), and the extraction process and solution parameters can be adjusted according to the waste composition to enhance the adaptability of the process.

[0058] (6) Reduce the consumption of chemical reagents:

[0059] By precisely controlling solution concentration and electrolysis parameters, the amount of chemical reagents used can be reduced, and resource waste can be further reduced through waste liquid recycling.

[0060] (7) Improve the economic benefits of enterprises:

[0061] The extracted precious metals and common metals can be used for reprocessing, which increases the economic value of electronic waste and creates additional profits for enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0063] Figure 1 It is a process flow chart of the present invention. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] The present invention proposes a harmless extraction process of metal resources from electronic waste based on green chemical method. Through this process, valuable metals in electronic waste can be efficiently recovered under mild conditions while reducing negative impact on the environment. The implementation method of this process is described in detail below in combination with specific steps.

[0066] Embodiment 1:

[0067] Extraction technology of metal resources from electronic waste

[0068] 1. Pretreatment of electronic waste

[0069] Electronic waste (such as discarded circuit boards, mobile phone parts, etc.) is placed in a crusher for preliminary crushing to reduce the material into smaller particles. The crushed waste is graded through a screening system to screen the particles according to different diameters to ensure the uniformity of the material entering the subsequent steps.

[0070] Screening models are used to optimize screening efficiency:

[0071]

[0072] Where S f is the screening efficiency, d is the particle diameter, d0 is the sieve hole diameter, and k is the screening coefficient. 2. Separation of magnetic materials

[0073] In the pre-treated material, the ferromagnetic material is removed by the dynamic magnetic separation equipment. The magnetic field in the equipment adopts a sinusoidal function to improve the separation effect of different magnetic materials.

[0074] -The magnetic field model is as follows:

[0075] B(t)=B0 sin(ωt)

[0076] Where B(t) is the magnetic induction intensity at time t, B0 is the initial magnetic induction intensity, and ω is the magnetic field frequency.

[0077] 3. Green solvent extraction of metals

[0078] The non-ferromagnetic material is added to a green solvent, such as a citric acid-oxalic acid mixture. This solvent can selectively dissolve the precious metals (such as gold, silver, and palladium) in it. During the extraction process, the complexation reaction of the metal uses the following coordination field energy model:

[0079]

[0080] Where \ΔE is the coordination field energy, D q is the field strength parameter, e g and They represent the number of electron energy level occupancy.

[0081] 4. Precipitation and selective separation of metals

[0082] The metal ions recovered from the solution are separated by precipitation reaction. The selective precipitation of different metals is achieved by adjusting the pH value and temperature of the solution.

[0083] -The metal precipitation process is governed by the following dissolution equilibrium equation:

[0084]

[0085] Where K sp is the solubility product constant, ΔH° and ΔS° are the standard enthalpy change and standard entropy change, respectively.

[0086] 5. Waste liquid treatment and recycling

[0087] The waste liquid after extraction is treated by a nanofiltration membrane system to remove residual metal ions and impurities. The recycling treatment of the waste liquid follows the following membrane filtration model:

[0088] J=L p (ΔP-σΔπ)

[0089] Where J is the permeate flow rate, L p is the permeability of the membrane, ΔP is the pressure difference, σ is the reflection coefficient, and Δπ is the osmotic pressure difference.

[0090] 6. Electrolytic refining of metals

[0091] After the metal is precipitated, the crude metal is placed in an electrolytic cell where it is further purified by electrolytic refining. The electrolytic process is based on a modified Faraday's law:

[0092]

[0093] Where M is the metal mass, Z is the electrochemical equivalent, F is the Faraday constant, I is the current, t is the time, n is the number of electrons, η c is the current efficiency.

[0094] 7. Optimization of intelligent control system

[0095] The entire process is monitored by an intelligent control system, and the parameters are adjusted in real time through the particle swarm optimization algorithm to ensure the efficient operation of the system.

[0096] -The particle swarm optimization algorithm is as follows:

[0097] v i (t+1)=wv i (t)+c1r1(p i -x i (t))+c2r2(gx i (t))

[0098] where v i (t+1) is the velocity of particle i, w is the inertia weight, c1 and c2 are acceleration coefficients, and r1 and r2 are random numbers.

[0099] 8. Optimization and feedback control

[0100] The system continuously analyzes data from each step of the process and dynamically optimizes the process through an online learning mechanism. During operation, when new types of e-waste are detected or material characteristics change, the system automatically adjusts the crushing, extraction, filtration and electrolysis parameters.

[0101] In summary, the process flow of the present invention achieves efficient extraction of metals from electronic waste. Through the introduction of multiple innovative models and the optimization of intelligent control systems, the resource recovery efficiency is significantly improved and the environmental impact is reduced. The process is suitable for resource recovery of various complex electronic wastes and provides technical support for achieving a balance between green environmental protection and economic benefits.

[0102] Embodiment 2:

[0103] Detailed process flow of extraction and separation of different metals

[0104] When treating electronic waste containing precious metals such as gold, silver, and copper, the green chemical extraction process of the present invention can efficiently achieve resource recovery and harmless treatment. The following is a detailed description of the treatment scheme for such electronic waste in combination with specific process steps.

[0105] 1. Pretreatment and magnetic separation

[0106] - Crushing and grading:

[0107] Electronic waste such as discarded circuit boards and electronic components are put into the crusher for preliminary crushing, turning them into particles of about 2-5 mm, which is convenient for subsequent processing. The crushed particles are classified by screening equipment to remove dust and fine particles to ensure the uniformity of the material.

[0108] -Magnetic separation process:

[0109] Magnetic separation equipment is used to remove ferromagnetic materials (such as iron and nickel) from the crushed waste.

[0110] -Magnetic field strength optimization:

[0111] The magnetic field strength of the magnetic disk is between 3000-5000 Gauss, and the sinusoidal magnetic field changes ensure the effective separation of different ferromagnetic materials.

[0112] B(t)=B0 sin(ωt)

[0113] Where B(t) is the magnetic induction intensity at time t, B0 is the initial magnetic induction intensity, and ω is the magnetic field frequency.

[0114] -The separated ferromagnetic material is collected by the first collecting mechanism, and the non-ferromagnetic material enters the next extraction process.

[0115] 2. Metal Extraction with Green Solvents

[0116] -Solvent selection:

[0117] A green chemical solvent system, such as a citric acid-oxalic acid mixed solution, is used to selectively extract gold from non-ferromagnetic materials.

[0118] -Chemical reaction equation:

[0119] Au+4C6H8O7→[Au(C6H8O7)2] - +H +

[0120] -Temperature and solution control:

[0121] The solution temperature is controlled within the range of 60-80°C, and the complexation reaction between gold and green solvent is promoted by heating. The whole process is carried out between pH 2-4 to enhance the dissolution efficiency of gold.

[0122] 3. Selective precipitation of silver and copper

[0123] -Precipitant addition:

[0124] Sodium chloride (NaCl) is added to the extracted solution to precipitate silver, followed by the addition of sodium hydroxide (NaOH) to precipitate copper ions.

[0125] -Silver precipitation reaction:

[0126] Ag + +Cl - →AgCl(s)

[0127] -Copper precipitation reaction:

[0128] Cu 2+ +2OH - →Cu(OH)2(s)

[0129] -Solubility Control:

[0130] By adjusting the pH of the solution and controlling the temperature, efficient precipitation of silver and copper can be achieved respectively. The following equilibrium equations apply in this process:

[0131] K sp =[Ag + ][Cl - ]

[0132] K sp =[Cu 2+ ][OH - ] 2

[0133] 4. Electrolytic refining

[0134] -Electrolyzer configuration:

[0135] The precipitated silver and copper are placed as anode materials in separate electrolytic cells, the anode plates are composed of crude silver or crude copper, and the cathode plates are stainless steel.

[0136] -Electrolysis reaction:

[0137] Ag(s)→Ag + +e - (Anode reaction)

[0138] Ag + +e - →Ag(s) (cathode reaction)

[0139] -Control parameters:

[0140] -Electrolysis voltage: 2-4V

[0141] -Current density: 200-300A / m 2

[0142] -Electrolysis time: 4-6 hours

[0143] Silver and copper are continuously precipitated during the electrolysis process, achieving the extraction of pure metals.

[0144] 5. Waste liquid treatment and recycling

[0145] -Nanofiltration membrane system filtration:

[0146] The waste liquid after extraction is treated by nanofiltration membrane to remove impurities and residual heavy metal ions, and the treated solution is recycled.

[0147] J=L p (ΔP-σΔπ)

[0148] Where J is the permeate flow rate, L p is the permeability of the membrane, ΔP is the pressure difference, σ is the reflection coefficient, and Δπ is the osmotic pressure difference.

[0149] -Harmless treatment of waste liquid:

[0150] Use alkaline reagents to neutralize the treated wastewater to ensure that its pH value meets the discharge standards and is eventually discharged into the sewage treatment system.

[0151] 6. System optimization and feedback control

[0152] -Intelligent control system:

[0153] The entire process is monitored in real time by the PLC control system, and the parameters of each link are dynamically adjusted through the particle swarm optimization algorithm to ensure that the entire system operates in the best condition.

[0154] -Optimized algorithms:

[0155] v i (t+1)=wv i (t)+c1r1(p i -x i (t))+c2r2(gx i (t))

[0156] where v i (t+1) is the velocity of particle i, w is the inertia weight, c1 and c2 are acceleration coefficients, and r1 and r2 are random numbers.

[0157] Effects and advantages of Example 2 (as shown in Table 1)

[0158]

[0159] Table 1

[0160] (1) High resource recovery rate: The recovery rate of gold, silver, copper and other metals in this process exceeds 95%, which significantly improves the resource utilization efficiency of electronic waste.

[0161] (2) Green and environmentally friendly: The use of green chemical solvents and harmless treatment processes avoids the environmental pollution caused by traditional chemical methods.

[0162] (3) Intelligent management: The system realizes fully automatic operation and parameter optimization through intelligent control, ensuring efficient and safe processing results.

[0163] In summary, this example demonstrates how to efficiently extract and separate metals such as gold, silver, and copper from electronic waste through a process based on green chemistry. This process combines multiple process technologies such as pretreatment, magnetic separation, solvent extraction, precipitation separation, electrolytic refining, and waste liquid treatment, and uses an intelligent control system to optimize the management of the entire process, providing an innovative solution for the harmless treatment of electronic waste and the efficient recovery of metal resources.

[0164] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0165] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A harmless extraction process of metal resources from electronic waste based on green chemistry, characterized in that: The following steps are involved: (1) Pretreatment of electronic waste: crushing and screening the electronic waste, and separating the ferromagnetic materials from other materials through magnetic material separation; (2) Green solvent extraction: using green solvents and complex reactions to extract target metal resources through a diffusion-reaction model; (3) Precipitation and selective separation of metals: Selective separation and recovery of metals are achieved through the solubility equilibrium formula and the phase distribution of multi-component systems; (4) Treatment and recycling of waste liquid: Use membrane separation and nanofiltration technology to treat waste liquid and recover residual resources in the waste liquid; (5) Electrolytic refining of metals: High purity metals are obtained by electrolytic refining process, and the current and charge distribution are controlled by modified Faraday's law; (6) Intelligent control and optimization: The particle swarm optimization algorithm is introduced to optimize the process parameters such as temperature, solution ratio and metal extraction time in real time.

2. The process according to claim 1, characterized in that: Screening efficiency model for the pretreatment process of electronic waste Where S f is the screening efficiency, d is the particle diameter, d0 is the sieve hole diameter, and k is the screening coefficient.

3. The process according to claim 1, characterized in that: Separation of magnetic materials using a dynamic magnetic field model B(t)=B0sin(ωt) Where B(t) is the magnetic induction intensity at time t, B0 is the initial magnetic induction intensity, and ω is the magnetic field frequency.

4. The process according to claim 1, characterized in that: Metal complexation reactions using the coordination field energy model Where \ΔE is the coordination field energy, D q is the field strength parameter, e g and t 2g They represent the number of electron energy level occupancy.

5. The process according to claim 1, characterized in that: The metal precipitation process is governed by the solubility equilibrium equation: Where K sp is the solubility product constant, ΔH° and ΔS° are the standard enthalpy change and standard entropy change, respectively.

6. The process according to claim 1, characterized in that: In the process of wastewater treatment, membrane separation uses the nanofiltration model J=L p (ΔP-σΔπ) Where J is the permeate flow rate, L p is the permeability of the membrane, ΔP is the pressure difference, σ is the reflection coefficient, and Δπ is the osmotic pressure difference.

7. The process according to claim 1, characterized in that: Electrolytic refining uses the modified Faraday's law: Where M is the metal mass, Z is the electrochemical equivalent, F is the Faraday constant, I is the current, t is the time, n is the number of electrons, η c is the current efficiency.

8. The process according to claim 1, characterized in that: Particle swarm optimization algorithm is used to optimize process parameters: v i (t+1)=wv i (t)+c1r1(p i -x i (t))+c2r2(g-x i (t)) where v i (t+1) is the velocity of particle i, w is the inertia weight, c1 and c2 are acceleration coefficients, and r1 and r2 are random numbers.

9. The process according to claim 1, characterized in that: A dynamic ratio strategy is adopted in the green solvent selection process to optimize the complexation degree of the solution as the temperature and concentration change.

10. The process according to claim 1, characterized in that: The system is able to retrain models in real time during the monitoring process and automatically update separation and extraction strategies based on the type of material detected.

Images