Evidence map›Paper›PMID 41545451›Full record

ArticleScientific reports2026

ZrO

Elka Kraleva, Maria Luisa Saladino, Cristina Giordano, Rosina Celeste Ponterio, Udo Armbruster

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

5 authors.

Elka KralevaLeibniz Institute for Catalysis, Albert-Einstein-Str. 29A, 18059, Rostock, Germany. elka.kraleva@catalysis.de.
Maria Luisa SaladinoDepartment of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF)-University of Palermo, Viale delle Scienze, Bld.17, Palermo, I-90128, Italy.
Cristina GiordanoSchool of Physical and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK.
Rosina Celeste PonterioInstitute for Chemical and Physical Processes IPCF-Messina, CNR, Viale Ferdinando Stagno d'Alcontres 37, Messina, I-98158, Italy.
Udo ArmbrusterLeibniz Institute for Catalysis, Albert-Einstein-Str. 29A, 18059, Rostock, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The catalytic hydrogenation of carbon dioxide (CO₂) to light olefins provides a sustainable route for producing key chemical intermediates and reducing dependence on fossil-based feedstocks. In this study, FeK, FeCoK, and FeCuK catalysts supported on ZrO₂ were synthesized by a simple wet impregnation method and evaluated for CO₂ hydrogenation. The goal of the study was to understand how secondary metal promoters (Co or Cu) influence the structural and electronic properties of K-promoted Fe/ZrO₂ catalysts and how these modifications affect CO₂ conversion and product selectivity. Among the catalysts tested, FeCoK/ZrO₂ showed the highest performance, achieving around 40% CO₂ conversion and 30% light-olefin selectivity, compared with 40% conversion and 22% selectivity for FeCuK/ZrO₂ under identical conditions (400 °C, 3 MPa, H₂/CO₂ = 3). The FeCuK catalyst exhibited higher CO yield, suggesting enhanced reverse water–gas shift (RWGS) activity, while Co promotion facilitated the formation and stabilization of iron carbides, improving chain growth and olefin selectivity. These findings demonstrate that the addition of Co or Cu effectively tunes the competition among RWGS, methanation, and hydrocarbon chain-growth pathways. Furthermore, the simple impregnation method yielded catalytic behavior comparable to more complex synthesis approaches, highlighting its potential scalability for CO₂-to-olefin conversion.

Indexed as

CO2 hydrogenationIron-potassium catalystsLight olefinZrO2 support

Identifiers

PMID41545451
PMCPMC12820173

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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.