Pair Distribution Function Obtained from Electron Diffraction: An Advanced Real-Space Structural Characterization Tool

Author(s)

Souza Junior, Joao Batista ^[1] ; Schleder, Gabriel Ravanhani ^{[2, 1]} ; Bettini, Jefferson ^[1] ; Nogueira, Icamira Costa ^[3] ; Fazzio, Adalberto ^{[2, 1]} ; Leite, Edson Roberto ^{[4, 1]}

Affiliation

^[1] Brazilian Ctr Res Energy & Mat CNPEM, Brazilian Nanotechnol Natl Lab LNNano, BR-13083970 Campinas, SP - Brazil

^[2] Fed Univ ABC UFABC, BR-09210580 Santo Andre, SP - Brazil

^[3] Fed Univ Amazonas UFAM, BR-69080900 Manaus, Amazonas - Brazil

^[4] Univ Fed Sao Carlos, Dept Chem, BR-13565905 Sao Carlos, SP - Brazil

• Document type: Review article
• Source: MATTER; v. 4, n. 2, p. 441-460, FEB 3 2021.
• Web of Science Citations: 0

Abstract

Atomic-scale structure determination is crucial to the understanding of nanomaterial properties and development of new technologies. Although pair distribution function (PDF) analysis by neutrons and X-ray scattering profile has been used to study materials, electron diffraction can offer advantages to characterize the atomic structure of clusters, amorphous samples, and nanomaterials. Electrons have higher scattering power than X-rays, allowing the acquirement of PDF from electron diffraction (ePDF) for small sample amounts and with time-efficient data acquisition. Compared with synchrotron X-rays and neutrons as sources for PDF, the availability of electron microscopes worldwide is advantageous. Nowadays, with the rise of methodologies and specific software for ePDF data analysis, the scientific community can benefit from advanced transmission electron microscopy (TEM) structure determination integrating commonly available TEM analyses?size, distribution, shape, and high-resolution TEM atomic visualization? with ePDF atomic structure determination, both for bulk and surface configurations. Therefore, ePDF has the potential to become a routine and advanced characterization tool for nanomaterials science. (AU)

• FAPESP's process: 13/07296-2 - CDMF - Center for the Development of Functional Materials
• Grantee: Elson Longo da Silva
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
• FAPESP's process: 17/18139-6 - Machine learning for Materials Science: 2D materials discovery and design
• Grantee: Gabriel Ravanhani Schleder
• Support Opportunities: Scholarships in Brazil - Doctorate
• FAPESP's process: 18/05159-1 - Static and dynamic self-assembly of inorganic nanoparticles
• Grantee: João Batista Souza Junior
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 17/02317-2 - Interfaces in materials: electronic, magnetic, structural and transport properties
• Grantee: Adalberto Fazzio
• Support Opportunities: Research Projects - Thematic Grants