Evidence map›Paper›PMID 41884415›Full record

ArticleACS catalysis2026

One-Step Photocatalytic Oxidation of Cumene with Mesoporous Carbon Nitride.

Sonia Żółtowska, Gabriel Chan, Tim Tjardts, Paolo Giusto

Abstract read
In one paragraph

Article in ACS catalysis, 2026. 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
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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

4 authors.

Sonia ŻółtowskaDepartment of Colloid Chemistry, Max Planck Institute of Colloids and Interfaces, 14476 Potsdam, Germany.
Gabriel ChanDepartment of Colloid Chemistry, Max Planck Institute of Colloids and Interfaces, 14476 Potsdam, Germany.
Tim TjardtsInstitute of Material Science, Christian-Albrechts-Universität zu Kiel, 24143 Kiel, Germany.
Paolo GiustoDepartment of Colloid Chemistry, Max Planck Institute of Colloids and Interfaces, 14476 Potsdam, Germany.ORCID https://orcid.org/0000-0003-4181-6500

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The shift toward mild, low-impact chemical conversion is pivotal for future development. Photocatalytic energy conversion, which harnesses light to drive reactions under mild conditions, offers a powerful alternative to conventional energy-intensive synthetic routes. Here, we establish mesoporous graphitic carbon nitride (mpg-CN) as a highly efficient, metal-free photocatalyst for the selective oxidation of benzylic substrates, using cumene as a representative example. Optimized conditions enabled the selective oxidation of cumene to acetophenone and 1-methoxyethylbenzene with high efficiency, underscoring the catalyst's reaction selectivity and synthetic value. The system readily accommodates structurally related substrates with radical stability and steric hindrance playing defining roles in reactivity. Sensitivity analyses revealed critical parameters governing reaction performance, while spin-trapping experiments under oxygen-rich conditions identified hydroperoxide radicals as key intermediates initiating α-carbon oxidation. Notably, scaling the reaction 10-fold preserved 66% conversion and 70% selectivity, and a further scale-up to gram scale of precursor delivered 50% acetophenone after 72 h. Furthemore, solvent recovery and reuse maintained high catalytic efficiency over the initial reuse cycles, demonstrating the operational durability of the system. Collectively, these findings position mpg-CN as a robust, scalable, and metal-free photocatalyst, a compelling platform for next-generation chemical manufacturing.

Indexed as

benzylic oxidationcarbon nitridecumenemetal-free catalystphotocatalysisscale-up

Identifiers

PMID41884415
PMCPMC13011261

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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.