Evidence map›Paper›PMID 39264121›Full record

ArticleJournal of chemical theory and computation2024

Stability and Dynamics of Zeolite-Confined Gold Nanoclusters.

Siddharth Sonti, Chenghan Sun, Zekun Chen, Robert Michael Kowalski, Joseph S Kowalski, Davide Donadio, Surl-Hee Ahn, Ambarish R Kulkarni

Abstract read
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In one paragraph

Article in Journal of chemical theory and computation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Siddharth SontiDepartment of Chemical Engineering, University of California, Davis, Davis, California 95616, United States.ORCID 0000-0003-1192-8229
Chenghan SunDepartment of Chemical Engineering, University of California, Davis, Davis, California 95616, United States.
Zekun ChenDepartment of Chemistry, University of California, Davis, Davis, California 95616, United States.
Robert Michael KowalskiDepartment of Chemical Engineering, University of California, Los Angeles, Los Angeles, California 90095, United States.
Joseph S KowalskiDepartment of Biomedical Engineering, University of California, Davis, Davis, California 95616, United States.
Davide DonadioDepartment of Chemistry, University of California, Davis, Davis, California 95616, United States.ORCID 0000-0002-2150-4182
Surl-Hee AhnDepartment of Chemical Engineering, University of California, Davis, Davis, California 95616, United States.ORCID 0000-0002-3422-805X
Ambarish R KulkarniDepartment of Chemical Engineering, University of California, Davis, Davis, California 95616, United States.ORCID 0000-0001-9834-8264

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanoengineered metal@zeolite materials have recently emerged as a promising class of catalysts for several industrially relevant reactions. These materials, which consist of small transition metal nanoclusters confined within three-dimensional zeolite pores, are interesting because they show higher stability and better sintering resistance under reaction conditions. While several such hybrid catalysts have been reported experimentally, key questions such as the impact of the zeolite frameworks on the properties of the metal clusters are not well understood. To address such knowledge gaps, in this study, we report a robust and transferable machine learning-based potential (MLP) that is capable of describing the structure, stability, and dynamics of zeolite-confined gold nanoclusters. Specifically, we show that the resulting MLP maintains

Identifiers

PMID39264121
PMCPMC11428131

What OpenQuestion holds

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Registered trials

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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.