Evidence map›Paper›PMID 41634048›Full record

ReviewNature communications2026

Cracking the code of multi-layer films to promote circularity in single-use plastic packaging.

Ethan C Quinn, Levi J Hamernik, Jeffrey N Law, Ryan W Clarke, Maya Milrod, Shivani Kozarekar, Rebecca M Mick, Margaret J Sobkowicz, Linda J Broadbelt, Brandon C Knott and 1 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Nature communications, 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

11 authors.

Ethan C Quinn *Department of Chemistry, Colorado State University, Fort Collins, CO, USA.ORCID http://orcid.org/0000-0002-9609-806X
Levi J Hamernik *Renewable Resources and Enabling Sciences Center, National Laboratory of the Rockies, Golden, CO, USA.
Jeffrey N Law *Renewable Resources and Enabling Sciences Center, National Laboratory of the Rockies, Golden, CO, USA.ORCID http://orcid.org/0000-0003-2828-1273
Ryan W ClarkeHexion Inc., Columbus, OH, USA.
Maya MilrodDepartment of Chemistry, Northwestern University, Evanston, IL, USA.ORCID http://orcid.org/0000-0002-6118-7476
Shivani KozarekarDepartment of Chemical and Biological Engineering, McCormick School of Engineering and Applied Science, Northwestern University, Evanston, IL, USA.
Rebecca M MickAssociation of Plastic Recyclers, Washington, DC, USA.
Margaret J SobkowiczDepartment of Plastics Engineering, University of Massachusetts Lowell, Lowell, MA, USA.
Linda J BroadbeltDepartment of Chemical and Biological Engineering, McCormick School of Engineering and Applied Science, Northwestern University, Evanston, IL, USA.
Brandon C KnottRenewable Resources and Enabling Sciences Center, National Laboratory of the Rockies, Golden, CO, USA. brandon.knott@nrel.gov.ORCID http://orcid.org/0000-0003-3414-3897
Katrina M KnauerRenewable Resources and Enabling Sciences Center, National Laboratory of the Rockies, Golden, CO, USA. katrina.knauer@nrel.gov.ORCID http://orcid.org/0000-0002-0125-7532

Funding

U.S. Department of Energy (DOE) DEAC36-08GO28308
6 · The paper itself

Abstract

Multi-layer film packaging (MLF) revolutionized food preservation by combining diverse material layers to optimize barrier properties, mechanical strength, and shelf-life. These materials are essential for transporting perishables across various climates and allow for access to fresh goods in "food deserts", but they pose significant recycling challenges due to their structural complexity. This perspective examines key structure-property relationships governing barrier performance and highlights innovations in material design. We explore how machine learning can predict performance metrics and propose recyclable alternatives, integrating data-driven approaches with material science insights. By challenging the status quo of MLF design, we advocate for circularity in food packaging, inspiring innovation at the intersection of sustainability, material science, and artificial intelligence.

Identifiers

PMID41634048
PMCPMC12886869

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.