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SUMMARY:Application of Computational Alchemy to screen alloys of alumina (
 Al2O3) as a catalyst support
DTSTART;VALUE=DATE-TIME:20211202T104500Z
DTEND;VALUE=DATE-TIME:20211202T111500Z
DTSTAMP;VALUE=DATE-TIME:20260711T081956Z
UID:indico-contribution-1522@events.chpc.ac.za
DESCRIPTION:Speakers: Cecil  Ouma (HySA - Infrastracturte)\nDescriptors de
 rived from density functional theory (DFT) calculations have been the stan
 dard when it comes to screening any alloy configuration space. However\, d
 eriving descriptors using DFT comes with high computational costs since an
 y alloy configuration space is expansive. DFT derived descriptors have bee
 n used for scaling relationships (SR)\, quantitative structure property re
 lationships (QSPR) and of late artificial intelligence/machine learning (A
 I/ML) in screening for alloys and catalysts. However\, SR and QSPR still r
 equire lots of DFT calculations and AI/ML need lots of training data. Cata
 lyst support have not been intensively investigated. Much of the focus has
  been on the catalyst. However\, alumina (Al2O3) has been the most dominan
 t support in use.  Computational alchemy can be used to approximate a desc
 riptor on a large number of random/hypothetical alloy configurations with 
 low computational cost. This is because it only requires a single set of r
 eference DFT calculations. Transition metal doped Al2O3 has been reported 
 to possess excellent attributes\, such as the ability to promote surface d
 iffusion and prevent clustering/sintering by suppressing grain growth. In 
 this study\, using the binding energy as a descriptor\, we screen for rand
 om/hypothetical alloys of the catalyst support Al2O3 using computational a
 lchemy. We explore in this study\, some of the limitations of challenges o
 f this approach in screening for a broad range of alloys. Pt is introduced
  at different locations within the alloy matrix to make Al2O3 a conductor 
 and suitable for computational alchemy. Like previous studies\, on metal a
 lloys\, computational alchemy predicts adsorbate BEs in close agreement wi
 th those obtained using DFT calculations. This study provides insights on 
 how computational alchemy can be useful in materials’ predictions at low
  computational costs.\n\nhttps://events.chpc.ac.za/event/98/contributions/
 1522/
LOCATION:
URL:https://events.chpc.ac.za/event/98/contributions/1522/
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