Literature DB >> 31624817

First principles analysis of surface dependent segregation in bimetallic alloys.

Lida Farsi1, N Aaron Deskins.   

Abstract

Stability is an important aspect of alloys, and proposed alloys may be unstable due to unfavorable atomic interactions. Segregation of an alloy may occur preferentially at specific exposed surfaces, which could affect the alloy's structure since certain surfaces may become enriched in certain elements. Using density functional theory (DFT), we modeled surface segregation in bimetallic alloys involving all transition metals doped in Pt, Pd, Ir, and Rh. We not only modeled common (111) surfaces of such alloys, but we also modeled (100), (110), and (210) facets of such alloys. Segregation is more preferred for early and late transition metals, with middle transition metals being most stable within the parent metal. We find these general trends in segregation energies for the parent metals: Pt > Rh > Pd > Ir. A comparison of different surfaces suggests no consistent trends across the different parent hosts, but segregation energies can vary up to 2 eV depending on the exposed surface. We also developed a statistical model to predict surface-dependent segregation energies. Our model is able to distinguish segregation at different surfaces (as opposed to generic segregation common in previous models), and agrees well with the DFT data. The present study provides valuable information about surface-dependent segregation and helps explain why certain alloy structures occur (e.g. core-shell).

Entities:  

Year:  2019        PMID: 31624817     DOI: 10.1039/c9cp03984h

Source DB:  PubMed          Journal:  Phys Chem Chem Phys        ISSN: 1463-9076            Impact factor:   3.676


  2 in total

1.  A First-Principles Study on the Multilayer Graphene Nanosheets Anode Performance for Boron-Ion Battery.

Authors:  Mustapha Umar; Chidera C Nnadiekwe; Muhammad Haroon; Ismail Abdulazeez; Khalid Alhooshani; Abdulaziz A Al-Saadi; Qing Peng
Journal:  Nanomaterials (Basel)       Date:  2022-04-09       Impact factor: 5.719

2.  Predicting Segregation Energy in Single Atom Alloys Using Physics and Machine Learning.

Authors:  Maya Salem; Michael J Cowan; Giannis Mpourmpakis
Journal:  ACS Omega       Date:  2022-01-28
  2 in total

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