Evidence map›Paper›PMID 39262856›Full record

ArticlePNAS nexus2024

Predicting and understanding photocatalytic CO

Yanxia Wang, Yanjuan Sun, Xinyan Liu, Fan Dong

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PNAS nexus, 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. Advanced TiOMolecules (Basel, Switzerland) · 2025
    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

4 authors.

Yanxia WangSchool of Resources and Environment, Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, 2006 Xiyuan Road, Chengdu 611731, China.
Yanjuan SunSchool of Resources and Environment, Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, 2006 Xiyuan Road, Chengdu 611731, China.
Xinyan LiuSchool of Resources and Environment, Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, 2006 Xiyuan Road, Chengdu 611731, China.
Fan DongSchool of Resources and Environment, Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, 2006 Xiyuan Road, Chengdu 611731, China.ORCID https://orcid.org/0000-0003-2890-9964

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The highly selective conversion of carbon dioxide into value-added products is extremely valuable. However, even with the aid of in situ characterization techniques, it remains challenging to directly correlate extensive spectral data carrying microscopic information with macroscopic performance. Herein, we adopted advanced machine learning (ML) approaches to establish an accurate and interpretable relationship between vibrational spectral signals and catalytic performances to uncover hidden physical insights. Focusing on photocatalytic CO

Indexed as

CO2 reductionmachine learningphotocatalytic reactionreaction pathwayselectivity

Identifiers

PMID39262856
PMCPMC11389833

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.