About blackValue

Motivation and consortium

When recycling plastics, a distinction is essentially made between mechanical recycling, feedstock recycling and thermal recycling. At present, approximately 50 % of plastic waste is recycled in Europe. The recycling method most frequently used is thermal recycling, where the waste is incinerated to generate energy. The recyclate produced during the material recycling process is used to produce new products. Here, the recycling process is complicated by the large number of plastics and the different types of additives such as colorants, plasticizers, flame retardants or UV blockers. Products that are produced from mixed recyclate have poorer material properties than products made from new plastics. Sorting systems that are capable of identifying materials and are used in plastics recycling must therefore also be capable of correctly classifying material types, regardless of the additives that are used.

Due to the specific absorption behavior of black plastics, the sensor systems currently available on the market have great difficulty meeting the challenges associated with the separation of such plastics . This class of plastics, however, will play an increasingly important role in the future as the recycling of black plastics, particularly with regard to automobile recycling, is a key factor for meeting the agreed EU limits. This gap in the recycling loop must be closed with new technologies for the separation of black plastics. To achieve this goal, a strategic alliance comprising the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB in Karlsruhe and the Fraunhofer Institute for High Frequency Physics and Radar Techniques FHR in Wachtberg was formed.

Project goals

The process known as recycling involves several substeps, e.g. presorting, shredding, screening, separating, utilization. The project focuses on the core technical problem associated with the separation of colored or black plastics, namely the sensors. Thanks to terahertz technology, this problem can be solved at an industrial level. The sensors are not developed in isolation but integrated in state-of-the art sorting technology together with signal evaluation. Hereby, an industry-compatible method for the sorting of black plastics is now being introduced.

This project aims to carry out research on a sorting system, above all for black plastics, which facilitates the separation of black plastics in the recycling industry. Here, the central focus lies, in particular, on the cost-effective and flexible utilization of the system. To integrate the advantages of spectroscopic investigation between 0.1 and 1 terahertz in a recycling process, it is important that a suitable reduction of the measurement data be achieved to maximize the measurement speed. This data reduction is achieved through the utilization of targeted individual frequencies or small frequency bands to separate the plastics as opposed to complete spectroscopic investigations in the complete frequency range from 0.1 to 1 terahertz. This data reduction combined with submillimeter wave technology offers a novel approach to the development of a measuring instrument which can be used flexibly in the separation of various types of black plastic in the recycling area. Furthermore, the utilization of this technology with suitable algorithms allows a retropolation of material parameters, e.g. measurement of dielectric constants, which can be used to determine the plastic type.

The evaluation of different material-specific characteristics of the samples, such as damping, the spectral fingerprint and the dielectric properties, should facilitate the identification and validation of a suitable and cost-effective approach for the separation of a wide range of optically opaque plastics (black plastics) during the course of the project. One of the main challenges associated with the construction of such a system lies in the targeted selection of the frequencies to ensure that the created data volumes and the corresponding system costs are kept as low as possible. This concept has already been applied successfully by Fraunhofer IOSB for the sorting of colmanite in Turkey. It is also important to develop a multi-stage differentiation algorithm which not only factors in the characteristic absorption of the samples but also considers the dielectric properties. As the retropolation of the dielectric properties is an important element of the sorting algorithm, it is essential that different extraction approaches be investigated under realistic conditions. Two techniques deserve a particular mention here. One technique involves determining the thickness of the sample with an additional optical sensor whereby this height information and the phase shift of the implied submillimeter wave is subsequently used to calculate the dielectric properties. Another possibility for material parameter extraction involves the utilization of the reflection geometry of a measurement configuration. Cracks that occur in the characteristic impedance, caused by the boundary layers air/sample and sample/air, are specifically determined in the raw data set to acquire the necessary parameters for retropolation.