1. Density - based Sorting Method

• Principle
  The density - based sorting method capitalizes on the fact that different plastics possess distinct densities. For example, high - density polyethylene (HDPE) typically has a density ranging from 0.941 - 0.965 g/cm³, while polypropylene (PP) has a density around 0.90 - 0.91 g/cm³. By immersing plastics in a liquid medium with a specific density, plastics with a lower density than the liquid will float, and those with a higher density will sink.
• Procedure
  First, prepare a series of liquid media with different density gradients, such as saltwater solutions with varying salt concentrations. Then, place the mixed plastics into these solutions. Plastics will separate based on their buoyancy. For instance, in a density - adjusted saltwater solution, HDPE products like milk jugs will float, while PET (polyethylene terephthalate) bottles, which have a higher density, will sink.
• Advantages
  This method is relatively straightforward and cost - effective. It does not require highly sophisticated equipment, making it accessible for small - to - medium - scale recycling operations. It can effectively separate common plastics with significant density differences.
• Limitations
  The presence of impurities in plastics can affect their buoyancy and lead to inaccurate sorting. Also, maintaining the stability of the liquid medium density can be challenging, and temperature changes may influence the density of both the plastics and the liquid, potentially causing sorting errors.

2. Near - Infrared (NIR) Sorting Method

• Principle
  Each type of plastic has a unique molecular structure, which results in a characteristic near - infrared absorption and reflection pattern. NIR sorting equipment emits near - infrared light onto the plastic materials. Sensors then detect the reflected light. By comparing the detected NIR spectra with a pre - stored database of plastic spectra, the system can accurately identify the type of plastic.
• Procedure
  Mixed plastics are conveyed on a conveyor belt under the NIR detection unit. The NIR light source illuminates the plastics, and the sensors capture the reflected light signals. These signals are then processed by a computer algorithm that matches them with the known spectra in the database. Once the plastic type is identified, an ejection mechanism, such as an air jet, is activated to direct the plastic to the appropriate collection bin.
• Advantages
  It offers high sorting accuracy and can distinguish between plastics with similar physical properties. It can handle complex mixtures of plastics, including those with different additives and colorations. This method is suitable for high - volume recycling operations and can be integrated into automated recycling lines.
• Limitations
  The equipment is relatively expensive to purchase and maintain. Regular calibration of the NIR sensors and the database is required to ensure accurate sorting. The performance may be affected by factors such as the thickness and surface condition of the plastic samples.

3. Electrostatic Sorting Method

• Principle
  When plastics are subjected to certain processes, they can acquire different electrostatic charges. For example, through triboelectric charging, where plastics are rubbed against each other or a specific material, some plastics will become positively charged, while others will be negatively charged. In an electrostatic field, these charged plastics will move in different directions, enabling separation.
• Procedure
  Mixed plastics are first fed into a charging chamber, where they are triboelectrically charged. Then, they pass through an electrostatic field generated by electrodes. The charged plastics are deflected according to their charge polarity and magnitude. For instance, positively charged plastics will be attracted towards the negatively charged electrode, while negatively charged plastics will move towards the positively charged electrode. Collection bins are placed at the end of the sorting path to gather the separated plastics.
• Advantages
  This method can effectively separate plastics that are difficult to distinguish by other means, especially those with similar densities. It can be used to separate plastics with different additives or surface treatments that affect their electrostatic properties.
• Limitations
  The electrostatic sorting process is sensitive to humidity. High humidity levels can reduce the charging efficiency and cause charge dissipation, leading to inaccurate sorting. The surface condition of the plastics, such as the presence of contaminants or coatings, can also impact the charging and sorting results.

4. Visual Sorting Method

• Principle
  Visual sorting relies on the differences in color, shape, and transparency of plastics. Different types of plastics often have distinct visual characteristics. For example, PET bottles are usually transparent or have a slightly blue - tinted transparency, and they have a characteristic cylindrical shape with a specific neck design. PVC (polyvinyl chloride) products may have a different color range and texture compared to other plastics.
• Procedure
  Trained workers or automated optical sorting systems are used. In manual visual sorting, workers visually inspect the plastics on a conveyor belt or sorting table and separate them into different categories based on their appearance. Automated optical sorting systems use cameras and image - recognition software. The cameras capture images of the plastics, and the software analyzes the color, shape, and transparency features, comparing them with a pre - set database of plastic visual characteristics to identify and sort the plastics.
• Advantages
  Manual visual sorting is a simple and low - cost method, suitable for small - scale operations or when the quantity of plastic waste is not large. Automated optical sorting can be fast and efficient for large - scale sorting, especially when dealing with plastics with distinct visual differences.
• Limitations
  Manual visual sorting is labor - intensive and prone to human error, especially when sorting large volumes of plastics for extended periods. Automated optical sorting may face challenges when plastics have been discolored due to aging, contamination, or when their shapes are irregular, leading to misidentification.