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• W4387380028 abstract "Controlling and understanding reaction temperature variations in catalytic processes are crucial for assessing the performance of a catalyst material. Local temperature measurements are challenging, however. Luminescence thermometry is a promising remote-sensing tool, but it is cross-sensitive to the optical properties of a sample and other external parameters. In this work, we measure spatial variations in the local temperature on the micrometer length scale during carbon dioxide (CO2) methanation over a TiO2-supported Ni catalyst and link them to variations in catalytic performance. We extract local temperatures from the temperature-dependent emission of Y2O3:Nd3+ particles, which are mixed with the CO2 methanation catalyst. Scanning, where a near-infrared laser locally excites the emitting Nd3+ ions, produces a temperature map with a micrometer pixel size. We first designed the Y2O3:Nd3+ particles for optimal temperature precision and characterized cross-sensitivity of the measured signal to parameters other than temperature, such as light absorption by the blackened sample due to coke deposition at elevated temperatures. Introducing reaction gases causes a local temperature increase of the catalyst of on average 6–25 K, increasing with the reactor set temperature in the range of 550–640 K. Pixel-to-pixel variations in the temperature increase show a standard deviation of up to 1.5 K, which are attributed to local variations in the catalytic reaction rate. Mapping and understanding such temperature variations are crucial for the optimization of overall catalyst performance on the nano- and macroscopic scale." @default.
• W4387380028 created "2023-10-06" @default.
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• W4387380028 date "2023-10-05" @default.
• W4387380028 modified "2023-10-16" @default.
• W4387380028 title "Mapping Temperature Heterogeneities during Catalytic CO₂ Methanation with <i>Operando</i> Luminescence Thermometry" @default.
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• W4387380028 doi "https://doi.org/10.1021/acsnano.3c05622" @default.
• W4387380028 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37797269" @default.
• W4387380028 hasPublicationYear "2023" @default.
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