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Prospect of making XPS a high-throughput analytical method illustrated for a Cu(x)Ni(1−x)O(y) combinatorial material library
Combinatorial material science crucially depends on robust, high-throughput characterization methods. While X-ray photoelectron spectroscopy (XPS) may provide detailed information about chemical and electronic properties, it is a time-consuming technique and, therefore, is not viewed as a high-throu...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The Royal Society of Chemistry
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982450/ https://www.ncbi.nlm.nih.gov/pubmed/35424741 http://dx.doi.org/10.1039/d1ra09208a |
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author | Bodenstein-Dresler, Lucas C. W. Kama, Adi Frisch, Johannes Hartmann, Claudia Itzhak, Anat Wilks, Regan G. Cahen, David Bär, Marcus |
author_facet | Bodenstein-Dresler, Lucas C. W. Kama, Adi Frisch, Johannes Hartmann, Claudia Itzhak, Anat Wilks, Regan G. Cahen, David Bär, Marcus |
author_sort | Bodenstein-Dresler, Lucas C. W. |
collection | PubMed |
description | Combinatorial material science crucially depends on robust, high-throughput characterization methods. While X-ray photoelectron spectroscopy (XPS) may provide detailed information about chemical and electronic properties, it is a time-consuming technique and, therefore, is not viewed as a high-throughput method. Here we present preliminary XPS data of 169 measurement spots on a combinatorial 72 × 72 cm(2) Cu(x)Ni(1−x)O(y) compositional library to explore how characterization and evaluation routines can be optimized to improve throughput in XPS for combinatorial studies. In particular, two quantification approaches are compared. We find that a simple integration (of XPS peak regions) approach is suited for fast evaluation of, in the example system, the [Cu]/([Cu] + [Ni]) ratio. Complementary to that, the time-consuming (XPS peak-) fit approach provides additional insights into chemical speciation and oxidation state changes, without a large deviation of the [Cu]/([Cu] + [Ni]) ratio. This insight suggests exploiting the fast integration approach for ‘real time’ analysis during XPS data collection, paving the way for an ‘on-the-fly’ selection of points of interest (i.e., areas on the sample where sudden composition changes have been identified) for detailed XPS characterization. Together with the envisioned improvements when going from laboratory to synchrotron-based excitation sources, this will shorten the analysis time sufficiently for XPS to become a realistic characterization option for combinatorial material science. |
format | Online Article Text |
id | pubmed-8982450 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-89824502022-04-13 Prospect of making XPS a high-throughput analytical method illustrated for a Cu(x)Ni(1−x)O(y) combinatorial material library Bodenstein-Dresler, Lucas C. W. Kama, Adi Frisch, Johannes Hartmann, Claudia Itzhak, Anat Wilks, Regan G. Cahen, David Bär, Marcus RSC Adv Chemistry Combinatorial material science crucially depends on robust, high-throughput characterization methods. While X-ray photoelectron spectroscopy (XPS) may provide detailed information about chemical and electronic properties, it is a time-consuming technique and, therefore, is not viewed as a high-throughput method. Here we present preliminary XPS data of 169 measurement spots on a combinatorial 72 × 72 cm(2) Cu(x)Ni(1−x)O(y) compositional library to explore how characterization and evaluation routines can be optimized to improve throughput in XPS for combinatorial studies. In particular, two quantification approaches are compared. We find that a simple integration (of XPS peak regions) approach is suited for fast evaluation of, in the example system, the [Cu]/([Cu] + [Ni]) ratio. Complementary to that, the time-consuming (XPS peak-) fit approach provides additional insights into chemical speciation and oxidation state changes, without a large deviation of the [Cu]/([Cu] + [Ni]) ratio. This insight suggests exploiting the fast integration approach for ‘real time’ analysis during XPS data collection, paving the way for an ‘on-the-fly’ selection of points of interest (i.e., areas on the sample where sudden composition changes have been identified) for detailed XPS characterization. Together with the envisioned improvements when going from laboratory to synchrotron-based excitation sources, this will shorten the analysis time sufficiently for XPS to become a realistic characterization option for combinatorial material science. The Royal Society of Chemistry 2022-03-11 /pmc/articles/PMC8982450/ /pubmed/35424741 http://dx.doi.org/10.1039/d1ra09208a Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by/3.0/ |
spellingShingle | Chemistry Bodenstein-Dresler, Lucas C. W. Kama, Adi Frisch, Johannes Hartmann, Claudia Itzhak, Anat Wilks, Regan G. Cahen, David Bär, Marcus Prospect of making XPS a high-throughput analytical method illustrated for a Cu(x)Ni(1−x)O(y) combinatorial material library |
title | Prospect of making XPS a high-throughput analytical method illustrated for a Cu(x)Ni(1−x)O(y) combinatorial material library |
title_full | Prospect of making XPS a high-throughput analytical method illustrated for a Cu(x)Ni(1−x)O(y) combinatorial material library |
title_fullStr | Prospect of making XPS a high-throughput analytical method illustrated for a Cu(x)Ni(1−x)O(y) combinatorial material library |
title_full_unstemmed | Prospect of making XPS a high-throughput analytical method illustrated for a Cu(x)Ni(1−x)O(y) combinatorial material library |
title_short | Prospect of making XPS a high-throughput analytical method illustrated for a Cu(x)Ni(1−x)O(y) combinatorial material library |
title_sort | prospect of making xps a high-throughput analytical method illustrated for a cu(x)ni(1−x)o(y) combinatorial material library |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982450/ https://www.ncbi.nlm.nih.gov/pubmed/35424741 http://dx.doi.org/10.1039/d1ra09208a |
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