Recycled plastics aging

Industrial research is advancing new methods to evaluate how recycled plastics degrade after repeated recovery and reuse cycles. The goal is to improve the quality, safety, and reliability of recycled materials used in manufacturing and packaging applications.

A German research initiative called SpectralAIge is developing an innovative system that combines spectroscopy and artificial intelligence (AI) to analyze the aging process of plastics exposed to multiple recycling cycles. Researchers say current industrial methods cannot reliably predict how recycled polymers lose performance over time.

Why Recycled Plastics aging

Plastic materials gradually deteriorate during repeated processing and reuse. Heat, mechanical stress, oxidation, and contamination can weaken polymer structures, reducing durability and affecting product performance.

This degradation is especially important for commonly recycled plastics such as:

• Polyethylene (PE)
• Polypropylene (PP)
• Polyethylene terephthalate (PET)

Manufacturers and recyclers need reliable tools to determine whether recycled materials still meet quality and safety standards before they are reused in new products.

The SpectralAIge Research Project

The SpectralAIge project uses hyperspectral imaging (HSI) technology together with targeted fluorescence excitation generated by LED light sources.

Researchers analyze fluorescence spectra collected from aged plastic samples to identify signs of material degradation. The project combines these measurements with advanced chemometric analysis and AI-driven modeling systems.

The collected data is used to compare different analytical approaches and determine which method can most accurately detect process-induced aging in recycled plastics.

Artificial Intelligence and Spectroscopy Working Together

Artificial intelligence plays a central role in the project by helping researchers process large datasets and recognize degradation patterns that may not be visible through conventional inspection methods.

The final objective is to create software capable of automatically evaluating the aging level of recycled plastics during industrial processing.

This could help recyclers:

• Improve material sorting accuracy
• Maintain consistent product quality
• Reduce waste
• Increase confidence in recycled polymers
• Support circular economy goals

Lower-Cost Solutions for Industrial Use

Although hyperspectral imaging systems provide highly accurate results, they are also expensive. To make the technology more accessible for industrial applications, researchers are also developing lower-cost inverse spectrometers designed for specific recycling processes.

One targeted application involves PET bottle recycling systems managed through deposit-return facilities, where rapid and cost-effective material assessment is especially important.

Research Partners

The SpectralAIge project brings together several German research institutions and technology companies, including:

• SKZ Plastics Center in Würzburg
• Fraunhofer Institute for Factory Operation and Automation (IFF) in Magdeburg
• Silicann Systems
• HAIP Solutions

According to SKZ researcher Cosima Güttler, the project aims to strengthen product quality and safety standards within the circular economy while ensuring the technologies can be practically implemented in industrial environments.

Why This Matters for the Circular Economy

As global industries increase the use of recycled plastics, reliable quality assessment becomes increasingly important. Advanced AI-based monitoring systems could help manufacturers safely integrate more recycled content into products without compromising performance.

Improved material analysis may also support regulatory compliance, reduce resource consumption, and accelerate the transition toward more sustainable plastic recycling systems.

From Waste to Resource: Why Industry Can No Longer Ignore Recycled Plastic

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