Literature DB >> 29701917

Enabling Generalized Coordination Numbers to Describe Strain Effects.

Federico Calle-Vallejo1, Aliaksandr S Bandarenka2,3.   

Abstract

The world's growing energetic demand calls for efficient generation and interconversion of different types of energy. Heterogeneous catalysis can help cope with such demand, provided that rational, accurate and affordable design methods lead to the discovery of cost-effective and efficient catalysts. Here we derive a simple descriptor to simultaneously capture two parameters commonly used in catalytic materials design: strain and coordination. We test the descriptor with four different adsorbates on four active sites of two metals, and applying strain in the range of ±3 %, usually observed experimentally at catalytic metal surfaces. Furthermore, we use the descriptor to illustrate catalyst design availing strain and nearest-neighbor effects simultaneously for the oxygen reduction reaction, a reaction of high importance in fuel cells. The connection between coordination and strain helps in the search for robust yet rapid catalyst design methodologies.
© 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  adsorption energy; generalized coordination number; morphology; oxygen reduction reaction; strain

Year:  2018        PMID: 29701917     DOI: 10.1002/cssc.201800569

Source DB:  PubMed          Journal:  ChemSusChem        ISSN: 1864-5631            Impact factor:   8.928


  7 in total

1.  Influence of Van der Waals Interactions on the Solvation Energies of Adsorbates at Pt-Based Electrocatalysts.

Authors:  Laura P Granda-Marulanda; Santiago Builes; Marc T M Koper; Federico Calle-Vallejo
Journal:  Chemphyschem       Date:  2019-08-19       Impact factor: 3.102

Review 2.  Revealing the nature of active sites in electrocatalysis.

Authors:  Batyr Garlyyev; Johannes Fichtner; Oriol Piqué; Oliver Schneider; Aliaksandr S Bandarenka; Federico Calle-Vallejo
Journal:  Chem Sci       Date:  2019-07-23       Impact factor: 9.825

3.  An Element-Based Generalized Coordination Number for Predicting the Oxygen Binding Energy on Pt3M (M = Co, Ni, or Cu) Alloy Nanoparticles.

Authors:  Yusuke Nanba; Michihisa Koyama
Journal:  ACS Omega       Date:  2021-01-19

Review 4.  Applications of Machine Learning in Alloy Catalysts: Rational Selection and Future Development of Descriptors.

Authors:  Ze Yang; Wang Gao
Journal:  Adv Sci (Weinh)       Date:  2022-03-01       Impact factor: 17.521

5.  Fast identification of optimal pure platinum nanoparticle shapes and sizes for efficient oxygen electroreduction.

Authors:  Marlon Rück; Aliaksandr Bandarenka; Federico Calle-Vallejo; Alessio Gagliardi
Journal:  Nanoscale Adv       Date:  2019-06-03

6.  Density Functional Theory and Machine Learning Description and Prediction of Oxygen Atom Chemisorption on Platinum Surfaces and Nanoparticles.

Authors:  David S Rivera Rocabado; Yusuke Nanba; Michihisa Koyama
Journal:  ACS Omega       Date:  2021-07-01

7.  Structure-Dependent Strain Effects.

Authors:  Elisabeth M Dietze; Henrik Grönbeck
Journal:  Chemphyschem       Date:  2020-10-07       Impact factor: 3.102

  7 in total

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