Efficient PET Glycolysis with Suppressed Diethylene Glycol Formation and Beneficial Residue Effects Using an Organic Phosphonate Catalyst.

Xin-Yu Hao, Xing Cao, Yan-Peng Ni

Abstract read

In one paragraph

Article in Molecules (Basel, Switzerland), 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

3 authors.

Xin-Yu HaoInstitute of Functional Textiles and Advanced Materials, College of Textiles & Clothing, Qingdao Key Laboratory of Flame-Retardant Textile Materials, Shandong Key Laboratory of Polymeric Materials Recycling and Upcycling, National Engineering Research Center for Advanced Fire-Safety Materials D & A (Shandong), Qingdao 266071, China.

Xing CaoInstitute of Functional Textiles and Advanced Materials, College of Textiles & Clothing, Qingdao Key Laboratory of Flame-Retardant Textile Materials, Shandong Key Laboratory of Polymeric Materials Recycling and Upcycling, National Engineering Research Center for Advanced Fire-Safety Materials D & A (Shandong), Qingdao 266071, China.

Yan-Peng NiInstitute of Functional Textiles and Advanced Materials, College of Textiles & Clothing, Qingdao Key Laboratory of Flame-Retardant Textile Materials, Shandong Key Laboratory of Polymeric Materials Recycling and Upcycling, National Engineering Research Center for Advanced Fire-Safety Materials D & A (Shandong), Qingdao 266071, China.

Funding

Department of Science and Technology of Shandong Province No. tsqn202312176Ministry of Science and Technology of the People's Republic of China 2020YFC1910305

6 · The paper itself

Abstract

Glycolysis of poly(ethylene terephthalate) (PET) offers a promising route for chemical recycling, yet conventional homogeneous catalysts often suffer from low selectivity, severe side reactions (especially diethylene glycol, DEG formation), and detrimental metal residues that compromise the quality of recycled products. To address these challenges, we herein develop dipotassium phenylphosphonate (PPOA-K) as an efficient homogeneous catalyst for PET glycolysis. Under optimized conditions (1 wt% catalyst, 197 °C, EG/PET mass ratio 3:1, 90 min, atmospheric pressure), PPOA-K achieves 100% PET depolymerization and a high BHET yield of 86.0%, and the reaction follows apparent first-order kinetics with an activation energy of 70.3 kJ·mol

Indexed as

chemical recyclingdiethylene glycolglycolysisrecycled PETside reaction suppression

Identifiers

PMID42357556

DOI10.3390/molecules31122160

PMCPMC13304949

What OpenQuestion holds

Textmetadata

LicenceCC BY

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.