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Title: Is There a Negative Thermal Expansion in Supported Metal Nanoparticles? An in Situ X-ray Absorption Study Coupled with Neural Network Analysis

Journal Article · · Journal of Physical Chemistry. C
 [1];  [2]; ORCiD logo [3]
  1. Fritz-Haber-Inst. of the Max Planck Society, Berlin (Germany)
  2. Univ. of Central Florida, Orlando, FL (United States)
  3. Fritz-Haber-Inst. of the Max Planck Society, Berlin (Germany); Univ. of Central Florida, Orlando, FL (United States)

Interactions with their support, adsorbates, and unique structural motifs are responsible for many intriguing properties and potential applications of supported metal nanoparticles (NPs). At the same time, they complicate the interpretation of experimental data. In fact, the methods and approaches that work well for the ex situ analysis of bulk materials may be inaccurate or introduce artifacts in the in situ analysis of nanomaterials. Here, we revisit the controversial topic of negative thermal expansion and anomalies in the Debye temperature reported for oxide-supported metal NPs. In situ X-ray absorption experimental data collected for Pt NPs in ultrahigh vacuum and an advanced data analysis approach based on an artificial neural network demonstrate that Pt NPs do not exhibit intrinsic negative thermal expansion. Similarly, as for bulk materials, in the absence of adsorbates and strong particle-support interaction, the bond lengths in metal NPs increase with temperature. Lastly, the previously reported anomalies in particle-size-dependent Debye temperatures can also be linked to the artifacts in the interpretation of conventional X-ray absorption data of disordered materials such as NPs.

Research Organization:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Organization:
National Science Foundation (NSF); European Research Council (ERC)
Grant/Contract Number:
ERC-725915; OPERANDOCAT; NSF-CHEM-1213182; NSF- DMR-1207065
OSTI ID:
1575996
Journal Information:
Journal of Physical Chemistry. C, Vol. 123, Issue 33; ISSN 1932-7447
Publisher:
American Chemical SocietyCopyright Statement
Country of Publication:
United States
Language:
ENGLISH
Citation Metrics:
Cited by: 14 works
Citation information provided by
Web of Science

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Cited By (1)

Mapping XANES spectra on structural descriptors of copper oxide clusters using supervised machine learning journal October 2019