Evidence map›Paper›PMID 41120351›Full record

ArticleNature communications2025

Solar-hybrid biocatalyst for methane hydroxylation to methanol.

Jinha Jang, Devashish Das, Rowina Lestari, Jung-Kul Lee, Chan Beum Park

Abstract read
In one paragraph

Article in Nature communications, 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

5 authors.

Jinha Jang *Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
Devashish Das *Department of Chemical Engineering, Konkuk University, Seoul, Republic of Korea.
Rowina Lestari *Department of Chemical Engineering, Konkuk University, Seoul, Republic of Korea.
Jung-Kul LeeDepartment of Chemical Engineering, Konkuk University, Seoul, Republic of Korea. jkrhee@konkuk.ac.kr.ORCID http://orcid.org/0000-0001-7384-5301
Chan Beum ParkDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea. parkcb@kaist.ac.kr.ORCID http://orcid.org/0000-0002-0767-8629

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Methane hydroxylation presents a promising approach to produce high-energy methanol from potent greenhouse gases, thereby contributing to a more sustainable future. Despite its environmental importance, current research on this process remains challenging due to the harsh operating conditions for the activation of inert C-H bond in methane. In nature, methane monooxygenase converts methane by activating the C-H bonds through its hydroxylase, under ambient conditions, receiving electrons from NADH via a reductase. Beyond the traditional biological approach, the development of NADH-independent biocatalytic systems could open new avenues for cost-effective and sustainable methane conversion. Herein, we report an NADH-free biosolar platform that activates hydroxylase for eco-friendly methanol production. The xanthene-based light harvester spontaneously associates with hydroxylase and directly transfers its photoexcited electrons to the diiron active site, eliminating the need for a cofactor or reductase. Halogenation of xanthene accelerates direct electron transfer to the active site by increasing the polarizability and spin-orbit coupling of the light harvesters. Accordingly, the direct photobiocatalytic platform achieved a methanol time yield of 7.52 mmol g

Identifiers

PMID41120351
PMCPMC12540872

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.