The “Tasteful” initiative was launched to advance a novel tracer‑based sorting technology for post‑consumer plastic packaging. The core idea is to embed small, fluorescent tracer particles into packaging materials. When illuminated with a suitable excitation source, the tracers emit a characteristic visible light signal that can be detected independently of the polymer type. By combining different tracer codes, a wide range of sorting criteria can be encoded, enabling the separation of fractions that are currently indistinguishable by conventional near‑infrared (NIR) spectroscopy, such as multilayer films, black plastics or food‑contact‑approved containers. The project aimed to demonstrate that the tracer approach can be made economically viable and technologically robust enough for market deployment, and to integrate the detection system with object‑recognition and machine‑learning algorithms for automated sorting.

The scientific work focused on the synthesis and optical characterization of upconversion (UC) nanoparticles based on the host lattice Gd₂O₂S (GOS). The particles were co‑doped with Yb³⁺ and Er³⁺ ions, and in some series with additional activators such as Ti⁴⁺, Ti³⁺, Cr³⁺, Mn²⁺, or with the host lattice replaced by SrY₂O₄, BaY₂O₄, or Y₂BaZnO₅. Powder X‑ray diffraction confirmed phase purity for all compositions. UC luminescence spectra were recorded under 980 nm excitation, revealing strong red (≈ 660 nm) and green (≈ 540 nm) emission bands. The relative intensity ratio (R/G) was used as a quantitative tracer code. Systematic studies showed that increasing the Yb³⁺ concentration from 5 mol % to 20 mol % raised the R/G ratio from roughly 0.8 to 1.6, while raising the Er³⁺ content from 1 mol % to 5 mol % lowered the ratio, indicating a trade‑off between energy transfer efficiency and cross‑relaxation. Adjusting the Gd₂O₃/Na₂CO₃ precursor ratio further tuned the lattice parameters and improved crystallinity, which in turn sharpened the emission peaks and reduced background fluorescence. For the Y₂BaZnO₅ host, an optimal Yb³⁺/Er³⁺ ratio of 15 mol %/3 mol % yielded an R/G value of 1.4, while maintaining a narrow full‑width at half maximum of 12 nm for the red band. These spectral fingerprints were then encoded into a digital database and linked to specific sorting rules.

Beyond material synthesis, the project developed a compact excitation module based on a 980 nm laser diode and a fiber‑coupled detection head equipped with a CMOS sensor and narrow‑band interference filters. The sensor was calibrated against a reference spectrometer, achieving a detection sensitivity of 10⁻⁶ W cm⁻² for the red emission. Real‑time image processing algorithms extracted the R/G ratio from each detected particle, and a machine‑learning classifier (random forest) was trained on a dataset of 10,000 labeled samples to discriminate between up to eight tracer codes with an accuracy exceeding 95 %. Integration tests on a conveyor‑based sorting line demonstrated that the tracer system could operate at 30 items per second, matching the throughput of existing NIR sorters while providing additional discrimination power.

The “Tasteful” consortium comprised the University of Pforzheim as the lead institution, collaborating with the Fraunhofer Institute for Applied Polymer Research, the Technical University of Munich, and several industry partners from the packaging and recycling sectors. The project was funded by the German Federal Ministry of Education and Research (BMBF) under grant number 033R195A, with a total budget of €2.5 million. Work was carried out over a three‑year period from 2021 to 2023, with interim milestones delivered in 2022 and a final demonstration event held in late 2023. The consortium published five peer‑reviewed papers and presented at three international conferences, and the results are now being incorporated into the next generation of automated recycling facilities.