Journal of environmental management · 2026
Performance testing of fabricated green-synthesised binary and ternary nanohybrids for light-induced reduction of CO2 to gaseous fuel.
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Thomas Noel Abraham, Aristo Dona, Krishna Batchu Radhika, Rao Dilip, Lakshmi Thillai, Ms Ramyashree, Priya S Shanmuga, George Sajan Daniel, Tahir Muhammad
Аннотация
Greenhouse gas emissions worldwide continue to rise, and rising atmospheric CO2 is accelerating global warming and putting the 1.5 °C climate goal in jeopardy. The energy sector is still the biggest polluter because of the continued use of fossil fuels. Photocatalytic CO2 reduction driven by solar energy provides a sustainable pathway for the transformation of CO2 into useful fuels and chemicals. Metal-organic frameworks (MOFs) constitute an exciting class of materials for CO2 capture and conversion, due to their high surface areas, tunable porosity and rich functionality. Bio-MOFs are composed of renewable biological resources and thus offer a sustainable alternative to conventional MOFs. Their structural tunability, functional diversity and self-assembly properties can improve CO2 adsorption, selective capture in humid conditions, recyclability and industrial applicability. Thus, bio-based MOFs represent promising platforms for sustainable and efficient photocatalytic CO2 conversion and carbon utilisation. This study explains bio-based MOF synthesis strategies and develops binary and ternary MOF nanocomposites containing metallic and metal oxide components for photocatalytic CO2 reduction under halogen-lamp irradiation, followed by analysis of the reaction products. The synthesised materials were comprehensively characterised using FE-SEM/EDS, XRD, UV-Vis DRS, FTIR, PL, Mott-Schottky analysis, XPS, and BET surface area analysis to evaluate their morphological, structural, elemental, optical, electronic, surface-chemical, and textural properties. The composites were then tested for reduction reactions under visible light irradiation and quantified using gas chromatography (GC). Furthermore, Design of Experiments (DOE) using the two-factorial method was applied to optimise process parameters.