关于在温和条件下制备苯甲醇光氧化光催化剂的支撑剂选择的比较研究

Solids Pub Date : 2024-04-01 DOI:10.3390/solids5020012
Lénaïck Hervé, S. Heyte, Maya Marinova, Sébastien Paul, R. Wojcieszak, J. Thuriot-Roukos
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引用次数: 0

摘要

在应对全球变暖的过程中,传统的热化学工艺正在让位于选择性光催化技术,这是一种在更温和的条件下使用水等良性溶剂的环保方法。苯甲醛是一种用途广泛的化合物,可用于农用工业、制药和化妆品,是各种精细化学品的基本成分。本研究旨在利用苯甲醇的光氧化反应提高苯甲醛生产的可持续性。基于金纳米粒子的催化剂因其在氧化生物基分子方面的卓越效率而闻名。在这项研究中,金纳米颗粒被锚定在三种不同的载体上:TiO2、ZrO2 和石墨氮化碳(g-C3N4)。目的是研究支撑材料对苯甲醇选择性光催化的影响。在制备 g-C3N4 时,选择了三种不同的前驱体--三聚氰胺、尿素和二者 50:50 的混合物,以分析它们对催化剂性能的影响。在酸性条件(pH = 2)下,在 365 纳米波长下辐照 4 小时后,使用尿素前驱体合成的氮化石墨碳载体上的金光催化剂(Au@g-C3N4(脲))显示出转化率(75%)和选择性(85%)之间的最佳平衡。这种配方优于基准 Au@TiO2,后者的转化率(80%)与 Au@TiO2 相似,但选择性较低(55%)。
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A Comparative Study on the Choice of the Support in the Elaboration of Photocatalysts for the Photooxidation of Benzyl Alcohol under Mild Conditions
In the quest to combat global warming, traditional thermal chemistry processes are giving way to selective photocatalysis, an eco-friendly approach that operates under milder conditions, using benign solvents like water. Benzaldehyde, a versatile compound with applications spanning agroindustry, pharmaceuticals, and cosmetics, serves as a fundamental building block for various fine chemicals. This study aims at enhancing benzaldehyde production sustainability by utilizing photooxidation of benzyl alcohol. Gold nanoparticle-based catalysts are renowned for their exceptional efficiency in oxidizing bio-based molecules. In this research, Au nanoparticles were anchored onto three distinct supports: TiO2, ZrO2, and graphitic carbon nitride (g-C3N4). The objective was to investigate the influence of the support material on the selective photocatalysis of benzyl alcohol. In the preparation of g-C3N4, three different precursors—melamine, urea, and a 50:50 mixture of both—were chosen to analyze their impact on catalyst performance. After 4 h of irradiation at 365 nm, operating under acidic conditions (pH = 2), the Au photocatalyst on graphitic carbon nitride support synthesized using urea precursor (Au@g-C3N4(urea)) displayed the optimal balance between conversion (75%) and selectivity (85%). This formulation outperformed the benchmark Au@TiO2, which achieved a similar conversion rate (80%) but exhibited lower selectivity (55%).
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