Sort Plastic Waste Using Nir Spectroscopy

The plastic waste issue is a significant global problem, with over 430 million tons produced annually (OECD 2022). Only a small amount is recycled, leading to environmental impacts such as overflowing landfills, polluted waterways, and harm to wildlife. Approximately 19-23 million tonnes of plastic waste leak into aquatic ecosystems each year, causing pollution in lakes, rivers, and seas (UNEP 2021). Microplastics have been found in drinking water, seafood, and the air, posing potential health risks. Effective management of plastic waste is crucial due to its widespread use and persistent presence in landfills, oceans, and ecosystems. Sorting plastic waste is a critical step in recycling, involving categorizing plastics based on their polymer type, color, density, and other characteristics, and various techniques are used to improve recycling efficiency.

Figure 1: Plastic waste problem after use.

INTRODUCTION

Traditional sorting methods often rely on manual labor or mechanical processes, which can be labor-intensive, time-consuming, and prone to errors. However, the advent of Near-Infrared (NIR) spectroscopy offers a promising alternative, revolutionizing the way plastic waste is sorted and recycled.

NIR spectroscopy utilizes the unique spectral signatures of materials to identify and classify them rapidly and accurately. By analyzing the interaction of near-infrared light with plastic polymers, NIR spectroscopy can distinguish between different types of plastics based on their chemical composition, color, and other intrinsic properties. By automating the sorting process and minimizing human intervention, NIR spectroscopy minimizes errors and ensures a higher purity of recycled plastics. Furthermore, it enables the recycling of complex plastic mixtures that are challenging to separate using conventional methods, thus expanding the scope of recyclable materials, and promoting a more circular economy.

Key Advantages of NIR in sort plastic:

• Accuracy and Precision: NIR spectroscopy provides highly accurate and precise identification and classification of plastic polymers based on their unique spectral signatures. This reduces the risk of misclassification and ensures the purity of sorted materials, contributing to higher-quality recycled products.
• Non-Destructive Analysis: Unlike traditional sorting methods that may involve destructive sampling or alter the physical properties of materials, NIR spectroscopy enables non-destructive analysis. This means that plastic samples can be analyzed without altering their integrity, preserving their value and usability in recycling processes.
• Real-Time Analysis: NIR spectroscopy allows for real-time analysis of plastic waste streams, facilitating rapid sorting and decision-making in recycling facilities. By providing instantaneous results, it enhances the efficiency of sorting operations and minimizes processing time, leading to increased throughput and productivity.
• Versatility and Flexibility: NIR spectroscopy can analyze a wide range of plastic materials, including various polymer types, colors, and forms (e.g., flakes, pellets, films). This versatility enables the sorting of diverse plastic waste streams, including mixed or contaminated materials, which may be challenging to separate using conventional methods.

Figure 2: NIR spectra of plastics and schematic of NIR plastic sorting.

EXPERIMENTAL METHODS

A reflectance system is used in this application. Classifying plastics based on reflectance spectrum is a common method used to distinguish different types of plastics. The principle of this method is that each type of plastic has its characteristic reflection spectrum. These reflectance spectra can be used to identify the type of plastic.

Specifically, a reflectance spectrometer will emit light onto a plastic sample and measure its reflection at different wavelengths. The data is then compared with known reference samples to determine the type of plastic. Characteristic reflectance spectra for each plastic type will allow accurate classification of the plastic-type without the need to conduct complex chemical analysis.

Figure 3: Reflectance spectra at different platics.

After obtaining the reflectance spectra, calibration models are developed to correlate the NIR spectra of plastic samples with their corresponding properties of interest, such as polymer type, color, or composition. Multivariate analysis techniques are then used to develop predictive models that relate the spectral data to the target properties.

SORT PLASTIC SYSTEM

INTINS can provide a complete system for this application. NIRQuest+ spectrometer from Ocean Optics (Ocean Insight) features an improved optical bench design to deliver highly sensitive performance. High sensitivity allows for more accurate measurements especially in low light conditions. The long wavelength ranges from 900 - 2450 nm is a spectrometer suitable for plastic recycling applications, which can be used in the laboratory or on the industrial line.

Besides, the system also includes a specific software called DK-PMS. DK-PMS with a user-friendly interface, is easy to use in the industrial line. With just extremely simple steps, you can control the sort of plastic system to operate flexibly and effectively. The software connects to the system simply and quickly via USB.

Figure 4: Overview of the software interface

DK-PMS has smart algorithms that help customers classify plastics accurately, quickly, and extremely effectively with high performance. Currently, we classify four main types of plastics: PE, PS, PP, and PET. Other plastics are classified as "OTHER".

DK-PMS software uses an optical switch to measure 6 samples corresponding to 6 channels on a conveyor belt. With a measurement speed of 170 ms per sample when switching channels (about 1 second for 6 channels). The software achieves approximately 100% accuracy for all current models.

With the existing plastic classification system, INTINS is confident to be a reputable supplier of high-quality, accurate, and easy-to-use plastic classification systems for users.