Evidence map›Paper›PMID 38903749›Full record

ArticleACS sustainable chemistry & engineering2024

Modeling Mechanochemical Depolymerization of PET in Ball-Mill Reactors Using DEM Simulations.

Elisavet Anglou, Yuchen Chang, William Bradley, Carsten Sievers, Fani Boukouvala

Abstract read
In one paragraph

Article in ACS sustainable chemistry & engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Frontiers in chemistry · 2024
    Review
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

5 authors.

Elisavet AnglouSchool of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta , Georgia 30332, United States.ORCID https://orcid.org/0009-0007-9651-2981
Yuchen ChangSchool of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta , Georgia 30332, United States.ORCID https://orcid.org/0000-0002-0997-4069
William BradleySchool of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta , Georgia 30332, United States.ORCID https://orcid.org/0000-0003-2505-6898
Carsten SieversSchool of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta , Georgia 30332, United States.
Fani BoukouvalaSchool of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta , Georgia 30332, United States.ORCID https://orcid.org/0000-0002-0584-1517

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developing efficient and sustainable chemical recycling pathways for consumer plastics is critical for mitigating the negative environmental implications associated with their end-of-life management. Mechanochemical depolymerization reactions have recently garnered great attention, as they are recognized as a promising solution for solvent-free transformation of polymers to monomers in the solid state. To this end, physics-based models that accurately describe the phenomena within ball mills are necessary to facilitate the exploration of operating conditions that would lead to optimal performance. Motivated by this, in this paper we develop a mathematical model that couples results from discrete element method (DEM) simulations and experiments to study mechanically-induced depolymerization. The DEM model was calibrated and validated via video experimental data and computer vision algorithms. A systematic study on the influence of the ball-mill operating parameters revealed a direct relationship between the operating conditions of the vibrating milling vessel and the total energy supplied to the system. Moreover, we propose a linear correlation between the high-fidelity DEM simulation results and experimental monomer yield data for poly(ethylene terephthalate) depolymerization, linking mechanical and energetic variables. Finally, we train a reduced-order model to address the high computational cost associated with DEM simulations. The predicted working variables are used as inputs to the proposed mathematical expression which allows for the fast estimation of monomer yields.

Identifiers

PMID38903749
PMCPMC11187622

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.