Abstract
Metal–organic frameworks (MOFs) offer an exceptional platform for photocatalytic CO2 reduction (CO2RR) because metal nodes, organic linkers, defects and pore microenvironments can be engineered to integrate CO2 capture and light-driven redox chemistry. Yet, the intrinsic trade-offs of many pristine MOFs, limited conductivity, short carrier diffusion lengths, and framework instability under operating conditions often cap activity and selectivity. This review summarizes recent advances in MOF-based photocatalysts, focusing on the integration of MOFs with semiconductors, metal cocatalysts and plasmonic components to optimize band alignment, facilitate interfacial charge transfer and construct efficient catalytic microenvironments. Progress is discussed by major C1 products (CO, CH4, CH3OH and HCOOH), with emphasis on how node/linker electronics, defect chemistry, pore polarity and heterointerfaces govern CO2 activation, intermediate stabilization and product-determining pathways. We critically examine the correlation between enhanced CO2 adsorption and the higher photoreduction rates, and the dominant roles of mass transport and interfacial kinetics. Finally, we summarize emerging AI and machine-learning strategies for accelerating materials discovery and mechanistic understanding, and outline key challenges and opportunities toward scalable, selective and durable MOF-based CO2 photoconversion.
| Original language | English |
|---|---|
| Article number | 218177 |
| Journal | Coordination Chemistry Reviews |
| Volume | 566 |
| DOIs | |
| State | Published - 1 Nov 2026 |
Bibliographical note
Publisher Copyright:© 2026 Elsevier B.V.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Keywords
- CO photoreduction
- Machine learning
- Reaction mechanism
- Selectivity control
- Structure-activity relationships
ASJC Scopus subject areas
- General Chemistry
- Physical and Theoretical Chemistry
- Inorganic Chemistry
- Materials Chemistry
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