Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/118847
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dc.contributorDepartment of Applied Biology and Chemical Technology-
dc.creatorZhang, Yen_US
dc.creatorYou, Jen_US
dc.creatorWang, Ken_US
dc.creatorYao, Den_US
dc.creatorLu, Hen_US
dc.creatorVongsvivut, Jen_US
dc.creatorHou, Jen_US
dc.creatorChen, Pen_US
dc.creatorJin, Yen_US
dc.creatorLiu, Gen_US
dc.creatorWang, Zen_US
dc.creatorWang, Len_US
dc.date.accessioned2026-05-21T07:57:15Z-
dc.date.available2026-05-21T07:57:15Z-
dc.identifier.issn0002-7863en_US
dc.identifier.urihttp://hdl.handle.net/10397/118847-
dc.language.isoenen_US
dc.publisherAmerican Chemical Societyen_US
dc.rights© 2026 The Authors. Published by American Chemical Societyen_US
dc.rightsThis article is licensed under CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)en_US
dc.rightsThe following publication Zhang, Y., You, J., Wang, K., Yao, D., Lu, H., Vongsvivut, J., Hou, J., Chen, P., Jin, Y., Liu, G., Wang, Z., & Wang, L. (2026). Metal–Metal Oxide Interaction Modulated Photocatalytic Methane Conversion. Journal of the American Chemical Society, 148(16), 17094–17103 is available at https://doi.org/10.1021/jacs.6c01783.en_US
dc.titleMetal-metal oxide interaction modulated photocatalytic methane conversionen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage17094en_US
dc.identifier.epage17103en_US
dc.identifier.volume148en_US
dc.identifier.issue16en_US
dc.identifier.doi10.1021/jacs.6c01783en_US
dcterms.abstractMetal–metal oxide (M–MO) interactions are important in catalysis. However, insights into how such interactions modulate lattice oxygen activity and stabilize critical reaction intermediates are scarce. In this work, using photocatalytic oxidative coupling of methane (POCM) as an example, we develop a simple and predictive model that defines M–MO interactions using two key factors: oxygen vacancy formation energy (EOV) and the methyl (*CH3) adsorption energy difference (ΔE*CH3) across metal and oxide sites. Interfacial coupling comodulates EOV and ΔE*CH3. EOV governs lattice-oxygen reactivity and the initial C–H activation, while ΔE*CH3 controls CH3 distribution between metal and oxide sites and thereby C–C coupling selectivity. Correlating EOV and ΔE*CH3 with activity and selectivity reveals a unifying principle. Efficient methane conversion requires moderately labile lattice oxygen whereas selective C–C bond formation demands a large ΔE*CH3 to drive methyl coupling for multicarbon products. Specifically, a AgPd/TiO2 catalyst achieves an optimal balance in experimental testing, delivering over a methane conversion yield of 30 mmol g–1 h–1, a selectivity of 92% for C2 products, and an operation stability of around 160 h. More broadly, the EOV–ΔE*CH3 framework provides a predictive descriptor map for M–MO photocatalysts selection in POCM. This study fills a critical gap by establishing a quantitative framework for M–MO interactions, identifying interfacial synergy as the principal determinant of performance, and enabling rational M–MO catalyst design.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of the American Chemical Society, 29 Apr. 2026, v. 148, no. 16, p. 17094-17103en_US
dcterms.isPartOfJournal of the American Chemical Societyen_US
dcterms.issued2026-04-29-
dc.identifier.scopus2-s2.0-105037435115-
dc.identifier.pmid41991322-
dc.identifier.eissn1520-5126en_US
dc.description.validate202605 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_TA-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextZ.W. and L.W. acknowledge the support of the Australian Research Council through its Future Fellowship (FT230100251), DECRA (DE210100930), Discovery (DP200101900) and Laureate Fellowship (FL190100139) schemes. G.L. acknowledges the support by the National Natural Science Foundation of China (Nos. 52120105003, 52425201). The authors acknowledge the facilities, and the scientific and technical assistance, of the Australian Microscopy and Microanalysis Research Facility at the Centre for Microscopy and Microanalysis, The University of Queensland. This research was undertaken on the PD, XAS and IRM beamlines at the Australian Synchrotron, part of ANSTO. This research was undertaken with the assistance of resources from the National Computational Infrastructure (NCI Australia), an NCRIS enabled capability supported by the Australian Government. This work was supported by resources provided by the Pawsey Supercomputing Research Centre’s Setonix Supercomputer (10.48569/18sb-8s43), with funding from the Australian Government and the Government of Western Australia. L.W. acknowledges the financial support from HKSAR Global STEM Professorship, and the JC STEM Lab of Renewable Energy Materials funded by The Hong Kong Jockey Club Charities Trust.en_US
dc.description.pubStatusPublisheden_US
dc.description.TAACS (2026)en_US
dc.description.oaCategoryTAen_US
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