Evidence map›Paper›PMID 38824129›Full record

ArticleNature communications2024

Machine intelligence accelerated design of conductive MXene aerogels with programmable properties.

Snehi Shrestha, Kieran James Barvenik, Tianle Chen, Haochen Yang, Yang Li, Meera Muthachi Kesavan, Joshua M Little, Hayden C Whitley, Zi Teng, Yaguang Luo and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Article
  6. Tailoring optical response of MXene thin films.Nanophotonics (Berlin, Germany) · 2025
    Article
  7. Review and Perspectives on the Sustainability of Organic Aerogels.ACS sustainable chemistry & engineering · 2025
    Review
  8. Review
  9. Review
  10. Review
  11. 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

12 authors.

Snehi ShresthaDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA.
Kieran James BarvenikDepartment of Mechanical Engineering, University of Maryland, College Park, MD, 20742, USA.
Tianle ChenDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA.ORCID http://orcid.org/0000-0003-1332-0399
Haochen YangDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA.ORCID http://orcid.org/0000-0002-8367-9711
Yang LiDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA.
Meera Muthachi KesavanDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA.
Joshua M LittleDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA.
Hayden C WhitleyDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, USA.
Zi TengUS Department of Agriculture, Agricultural Research Service, Food Quality Laboratory and Environment Microbial Food Safety Laboratory, Beltsville Agricultural Research Center, Beltsville, MD, 20725, USA.
Yaguang LuoUS Department of Agriculture, Agricultural Research Service, Food Quality Laboratory and Environment Microbial Food Safety Laboratory, Beltsville Agricultural Research Center, Beltsville, MD, 20725, USA.
Eleonora TubaldiDepartment of Mechanical Engineering, University of Maryland, College Park, MD, 20742, USA. etubaldi@umd.edu.ORCID http://orcid.org/0000-0002-5604-1181
Po-Yen ChenDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20742, 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

Designing ultralight conductive aerogels with tailored electrical and mechanical properties is critical for various applications. Conventional approaches rely on iterative, time-consuming experiments across a vast parameter space. Herein, an integrated workflow is developed to combine collaborative robotics with machine learning to accelerate the design of conductive aerogels with programmable properties. An automated pipetting robot is operated to prepare 264 mixtures of Ti

Identifiers

PMID38824129
PMCPMC11144242

What OpenQuestion holds

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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.