Recent advances in designing UiO-66-based photocatalysts for CO2 reduction and related photocatalytic applications: Structural tuning and emerging role of machine learning

Fuel Processing Technology 2026 Open access

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Authors: Roshanak Jalali, Seyed Reza Shabanian, Mohsen Ghorbani
DOI: 10.1016/j.fuproc.2026.108497
Cited by: 4
References: 299

Abstract

• Structure-property roadmap for improving UiO-66-based photocatalysts across reactions. • Toolbox: Linker/node tuning, defects, heterojunctions, hydrophobicity, single-atom sites. • Analysis of roles in light absorption, charge separation and oxidation/reduction enhancement. • Applications: CO 2 reduction, H 2 and NH 3 production, NO x removal, pollutant degradation. • Synthesis and optimization of photocatalysts using machine learning. • Challenges: stability, scalability, electron transfer, life cycle.

Fields of Study & Subjects

Advanced Photocatalysis Techniques TiO2 Photocatalysis and Solar Cells CO2 Reduction Techniques and Catalysts

Publication details

Journal / source
Fuel Processing Technology
Publisher
Elsevier BV
Volume
289
Pages
108497–108497
Publication date
28 May 2026
Language
EN