Evidence map›Paper›PMID 41039980›Full record

ArticleJournal of chemical information and modeling2025

Segmentation for Learning Adsorption Patterns and Residence-Time Kinetics on Amorphous Surfaces.

Mattia Turchi, Ivan Lunati

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Mattia TurchiLaboratory for Computational Engineering, Swiss Federal Laboratories for Materials Science and Technology, Empa, 8600 Dübendorf, Switzerland.ORCID 0000-0001-6893-8335
Ivan LunatiLaboratory for Computational Engineering, Swiss Federal Laboratories for Materials Science and Technology, Empa, 8600 Dübendorf, Switzerland.ORCID 0000-0002-3205-7429

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heterogeneous surfaces such as amorphous silica are characterized by highly heterogeneous local atomic environments that govern the adsorption of gas molecules through spatial arrangements. These surfaces exhibit properties that are particularly relevant for adsorption and catalytic applications. Here, we investigate CO

Indexed as

Carbon DioxideMachine LearningAdsorptionKineticsSilicon DioxideSurface PropertiesCarbon DioxideSilicon Dioxide

Identifiers

PMID41039980
PMCPMC12570132

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.