Evidence map›Paper›PMID 41438048›Full record

ArticleiScience2025

First-principles calculations steered multi-task transformer model to screen dual-atom catalysts for C-H activation.

BaiRan Wang, WeiHang Xu, XiaoYing Sun, Qi Ji, LingLing Shang, Zhen Zhao, Bo Li

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2025. 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. Article
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

7 authors.

BaiRan WangInstitute of Catalysis for Energy and Environment, College of Chemistry and Chemical Engineering, Shenyang Normal University, Shenyang 110034, China.
WeiHang XuInstitute of Catalysis for Energy and Environment, College of Chemistry and Chemical Engineering, Shenyang Normal University, Shenyang 110034, China.
XiaoYing SunInstitute of Catalysis for Energy and Environment, College of Chemistry and Chemical Engineering, Shenyang Normal University, Shenyang 110034, China.
Qi JiInstitute of Catalysis for Energy and Environment, College of Chemistry and Chemical Engineering, Shenyang Normal University, Shenyang 110034, China.
LingLing ShangInstitute of Catalysis for Energy and Environment, College of Chemistry and Chemical Engineering, Shenyang Normal University, Shenyang 110034, China.
Zhen ZhaoInstitute of Catalysis for Energy and Environment, College of Chemistry and Chemical Engineering, Shenyang Normal University, Shenyang 110034, China.
Bo LiInstitute of Catalysis for Energy and Environment, College of Chemistry and Chemical Engineering, Shenyang Normal University, Shenyang 110034, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Activating C-H bonds in light alkanes (methane, ethane, and propane) remains a major challenge in heterogeneous catalysis due to their high stability, while dual-atom catalysts (DACs) offer a promising balance of activity and durability. Herein, we developed an optimized multi-task transformer model to accelerate active DACs design by integrating first-principles calculations with machine learning. Over 200 DACs composed of fourth/fifth period transition metals anchored on N-doped graphene were studied. The transformer, modified with additional decoder layers and attention head, outperformed conventional methods (K-nearest neighbors, resource description framework, and gradient boosting regression) for small datasets, achieving R

Indexed as

CatalysisChemical reactionComputational chemistryMolecular modeling

Identifiers

PMID41438048
PMCPMC12719781

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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.