Evidence map›Paper›PMID 42737181›Full record

ArticlePolymers2026

Investigating the Deinking of Polyethylene Post-Consumer Waste Flakes Using Industrially Applicable Surfactants.

Steven Zimmer, Lisa Leuchtenberger-Engel, Achim Grefenstein, Rainer Dahlmann

Abstract read
In one paragraph

Article in Polymers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Steven ZimmerInstitute for Plastics Processing (IKV) in Industry and Craft, RWTH Aachen University, Seffenter Weg 201, 52074 Aachen, Germany.ORCID 0009-0006-1305-5336
Lisa Leuchtenberger-EngelInstitute for Plastics Processing (IKV) in Industry and Craft, RWTH Aachen University, Seffenter Weg 201, 52074 Aachen, Germany.
Achim GrefensteinInstitute for Plastics Processing (IKV) in Industry and Craft, RWTH Aachen University, Seffenter Weg 201, 52074 Aachen, Germany.
Rainer DahlmannInstitute for Plastics Processing (IKV) in Industry and Craft, RWTH Aachen University, Seffenter Weg 201, 52074 Aachen, Germany.ORCID 0000-0003-2519-3972

Funding

LoopCycling
6 · The paper itself

Abstract

In recycling of plastic packaging, the deinking of post-consumer waste (PCW) is a key technology to achieve high-quality recyclates that can be used in demanding applications. Removing printing inks minimises the contamination in the mechanical recycling process, enabling the production of (semi)-transparent recycled films with low odour and fewer defects. While the deinking of uniformly printed model films is thoroughly researched and the general mechanism well understood, these findings are not readily transferable to industrial implementation on household PCW. This study systematically investigates the deinking of household PCW flakes using industrially available surfactants. Deinking parameters (water temperature, washing time, lye concentration) are varied with no surfactant added as well as for four industrially available surfactant formulations. The deinking efficiency is determined via an image-based statistical analysis. Via a multiple linear regression, median grey values of the experiments allow insights into the deinking mechanism of PCW flakes. Depending on the surfactant and deinking parameters, either the hydrolysis of the binding agent by sodium hydroxide (NaOH) or the surfactant-based decrease of interfacial energy on the printed surface proved dominant for the overall deinking mechanism.

Indexed as

circular economydeinkingpolymer recyclingstatistical analysiswaste management

Identifiers

PMID42737181
PMCPMC13568254

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.