Materials Map

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2023First‐Principles Density Functional Theory and Machine Learning Technique for the Prediction of Water Adsorption Site on PtPd‐Based High‐Entropy‐Alloy Catalysts10citations

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Boonchuay, Suphawich
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Noppakhun, Jakapob
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2023

Co-Authors (by relevance)

  • Boonchuay, Suphawich
  • Noppakhun, Jakapob
  • Setasuban, Sorawee
  • Praserthdam, Supareak
  • Khajondetchairit, Patcharaporn
  • Ektarawong, Annop
  • Alling, Björn
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article

First‐Principles Density Functional Theory and Machine Learning Technique for the Prediction of Water Adsorption Site on PtPd‐Based High‐Entropy‐Alloy Catalysts

  • Boonchuay, Suphawich
  • Noppakhun, Jakapob
  • Setasuban, Sorawee
  • Praserthdam, Supareak
  • Khajondetchairit, Patcharaporn
  • Ektarawong, Annop
  • Alling, Björn
  • Aumnongpho, Nuttanon
Abstract

<jats:title>Abstract</jats:title><jats:p>The water‐gas shift reaction (WGSR) is employed in industry to obtain high‐purity H<jats:sub>2</jats:sub> from syngas, where H<jats:sub>2</jats:sub>O adsorption is an important step that controls H<jats:sub>2</jats:sub>O dissociation in WGSR. Therefore, exploring catalysts exhibiting strong H<jats:sub>2</jats:sub>O adsorption energy (<jats:italic>E</jats:italic><jats:sub>ads</jats:sub>) is crucial. Also, high‐entropy alloys (HEA) are promising materials utilized as catalysts, including in WGSR. The PtPd‐based HEA catalysts are explored via density functional theory (DFT) and Gaussian process regression. The input features are based on the microstructure data and electronic properties: d‐band center (<jats:italic>ε</jats:italic><jats:sub>d</jats:sub>) and Bader net atomic charge (<jats:italic>δ</jats:italic>). The DFT calculation reveals that the <jats:italic>ε</jats:italic><jats:sub>d</jats:sub> and <jats:italic>δ</jats:italic> of each active site of all HEA surfaces are broadly scattered, indicating that the electronic properties of each atom on HEA are non‐uniform and influenced by neighboring atoms. The strong H<jats:sub>2</jats:sub>O‐active‐site interaction determined by a highly negative <jats:italic>E</jats:italic><jats:sub>ads</jats:sub> is used as a criterion to explore good PtPd‐based WGSR catalyst candidates. As a result, the potential candidates are found to have Co, Ru, and Fe as an H<jats:sub>2</jats:sub>O adsorption site with Ag as a neighboring atom, that is, PtPdRhAgCo, PtPdRuAgCo, PtPdRhAgFe, and PtPdRuAgFe.</jats:p>

Topics
  • density
  • impedance spectroscopy
  • microstructure
  • surface
  • theory
  • density functional theory
  • machine learning