Quantitative analysis of adsorbate concentrations by diffuse reflectance FT-IR

Fully quantitative analyses of DRIFTS data are required when the surface concentrations and the specific rate constants of reaction (or desorption) of adsorbates are needed to validate microkinetic models. The relationship between the surface coverage of adsorbates and various functions derived from...

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Main Authors: Jinda Sirita, Sukon Phanichphant, Frederic C. Meunier
Format: Journal
Published: 2018
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/60963
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-609632018-09-10T04:02:05Z Quantitative analysis of adsorbate concentrations by diffuse reflectance FT-IR Jinda Sirita Sukon Phanichphant Frederic C. Meunier Chemistry Fully quantitative analyses of DRIFTS data are required when the surface concentrations and the specific rate constants of reaction (or desorption) of adsorbates are needed to validate microkinetic models. The relationship between the surface coverage of adsorbates and various functions derived from the signal collected by DRIFTS is discussed here. The Kubelka-Munk and pseudoabsorbance (noted here as absorbance, for the sake of brevity) transformations were considered, since those are the most commonly used functions when data collected by DRIFTS are reported. Theoretical calculations and experimental evidence based on the study of CO adsorption on Pt/SiO2 and formate species adsorbed on Pt/CeO2 showed that the absorbance (i.e., = log 1/R′, with R′ = relative reflectance) is the most appropriate, yet imperfect, function to give a linear representation of the ad sorbate surface concentration in the examples treated here, for which the relative reflectance R′ is typically > 60%. When the adsorbates lead to a strong signal absorption (e.g., R′ < 60%), the Kubelka-Munk function is actually more appropriate. The absorbance allows a simple correction of baseline drifts, which often occur during time-resolved data collection over catalytic materials. Baseline corrections are markedly more complex in the case of the other mathematical transforms, including the function proposed by Matyshak and Krylov (Catal. Today 1995, 25, 1-87), which has been proposed as an appropriate representation of surface concentrations in DRIFTS spectroscopy. © 2007 American Chemical Society. 2018-09-10T04:02:05Z 2018-09-10T04:02:05Z 2007-05-15 Journal 00032700 2-s2.0-34249020155 10.1021/ac0702802 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=34249020155&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/60963
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Chemistry
spellingShingle Chemistry
Jinda Sirita
Sukon Phanichphant
Frederic C. Meunier
Quantitative analysis of adsorbate concentrations by diffuse reflectance FT-IR
description Fully quantitative analyses of DRIFTS data are required when the surface concentrations and the specific rate constants of reaction (or desorption) of adsorbates are needed to validate microkinetic models. The relationship between the surface coverage of adsorbates and various functions derived from the signal collected by DRIFTS is discussed here. The Kubelka-Munk and pseudoabsorbance (noted here as absorbance, for the sake of brevity) transformations were considered, since those are the most commonly used functions when data collected by DRIFTS are reported. Theoretical calculations and experimental evidence based on the study of CO adsorption on Pt/SiO2 and formate species adsorbed on Pt/CeO2 showed that the absorbance (i.e., = log 1/R′, with R′ = relative reflectance) is the most appropriate, yet imperfect, function to give a linear representation of the ad sorbate surface concentration in the examples treated here, for which the relative reflectance R′ is typically > 60%. When the adsorbates lead to a strong signal absorption (e.g., R′ < 60%), the Kubelka-Munk function is actually more appropriate. The absorbance allows a simple correction of baseline drifts, which often occur during time-resolved data collection over catalytic materials. Baseline corrections are markedly more complex in the case of the other mathematical transforms, including the function proposed by Matyshak and Krylov (Catal. Today 1995, 25, 1-87), which has been proposed as an appropriate representation of surface concentrations in DRIFTS spectroscopy. © 2007 American Chemical Society.
format Journal
author Jinda Sirita
Sukon Phanichphant
Frederic C. Meunier
author_facet Jinda Sirita
Sukon Phanichphant
Frederic C. Meunier
author_sort Jinda Sirita
title Quantitative analysis of adsorbate concentrations by diffuse reflectance FT-IR
title_short Quantitative analysis of adsorbate concentrations by diffuse reflectance FT-IR
title_full Quantitative analysis of adsorbate concentrations by diffuse reflectance FT-IR
title_fullStr Quantitative analysis of adsorbate concentrations by diffuse reflectance FT-IR
title_full_unstemmed Quantitative analysis of adsorbate concentrations by diffuse reflectance FT-IR
title_sort quantitative analysis of adsorbate concentrations by diffuse reflectance ft-ir
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=34249020155&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/60963
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