Evidence map›Paper›PMID 38499859›Full record

ArticleNature nanotechnology2024

Machine intelligence-accelerated discovery of all-natural plastic substitutes.

Tianle Chen, Zhenqian Pang, Shuaiming He, Yang Li, Snehi Shrestha, Joshua M Little, Haochen Yang, Tsai-Chun Chung, Jiayue Sun, Hayden Christopher Whitley and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature nanotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Review
  9. Oil-Coated Nanoplastics Induce Rapid Membrane Disruption and Severe Intestinal Injury.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Biodegradable Elastomers: Where Is the Solution?Chemistry (Weinheim an der Bergstrasse, Germany) · 2025
    Article
  18. Review
  19. Article
  20. 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

15 authors.

Tianle Chen *Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, USA.ORCID http://orcid.org/0000-0003-1332-0399
Zhenqian Pang *Department of Mechanical Engineering, University of Maryland, College Park, MD, USA.
Shuaiming He *Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, USA.
Yang LiDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, USA.
Snehi ShresthaDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, USA.
Joshua M LittleDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, USA.ORCID http://orcid.org/0000-0003-3601-3607
Haochen YangDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, USA.ORCID http://orcid.org/0000-0002-8367-9711
Tsai-Chun ChungDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, USA.
Jiayue SunDepartment of Chemistry and Biochemistry, University of Maryland, College Park, MD, USA.
Hayden Christopher WhitleyDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, USA.ORCID http://orcid.org/0009-0008-6377-5774
I-Chi LeeDepartment of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan.
Taylor J WoehlDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, USA.
Teng LiDepartment of Mechanical Engineering, University of Maryland, College Park, MD, USA. lit@umd.edu.ORCID http://orcid.org/0000-0001-6252-561X
Liangbing HuDepartment of Materials Science and Engineering, University of Maryland, College Park, MD, USA. binghu@umd.edu.ORCID http://orcid.org/0000-0002-9456-9315
Po-Yen ChenDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, USA. checp@umd.edu.ORCID http://orcid.org/0000-0003-0310-4748

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One possible solution against the accumulation of petrochemical plastics in natural environments is to develop biodegradable plastic substitutes using natural components. However, discovering all-natural alternatives that meet specific properties, such as optical transparency, fire retardancy and mechanical resilience, which have made petrochemical plastics successful, remains challenging. Current approaches still rely on iterative optimization experiments. Here we show an integrated workflow that combines robotics and machine learning to accelerate the discovery of all-natural plastic substitutes with programmable optical, thermal and mechanical properties. First, an automated pipetting robot is commanded to prepare 286 nanocomposite films with various properties to train a support-vector machine classifier. Next, through 14 active learning loops with data augmentation, 135 all-natural nanocomposites are fabricated stagewise, establishing an artificial neural network prediction model. We demonstrate that the prediction model can conduct a two-way design task: (1) predicting the physicochemical properties of an all-natural nanocomposite from its composition and (2) automating the inverse design of biodegradable plastic substitutes that fulfils various user-specific requirements. By harnessing the model's prediction capabilities, we prepare several all-natural substitutes, that could replace non-biodegradable counterparts as exhibiting analogous properties. Our methodology integrates robot-assisted experiments, machine intelligence and simulation tools to accelerate the discovery and design of eco-friendly plastic substitutes starting from building blocks taken from the generally-recognized-as-safe database.

Identifiers

PMID38499859
PMCPMC11186784

What Socratic 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 Socratic graph.