Bibliometric review and recent advances in total scattering pair distribution function analysis: 21 years in retrospect

• Published in: European journal of materials Vol. 3; no. 1; pp. 1 - 35
• Main Authors: Akamo, Damilola O., Ijaola, Ahmed Olanrewaju, George, Toyosi T., Page, Katharine, Keffer, David J., Li, Yuzhan, Goswami, Monojoy, LaClair, Tim J., Gluesenkamp, Kyle, Rios, Orlando
• Format: Journal Article
• Language: English
• Published: Taylor & Francis Group 31-12-2023
• Subjects: bibliometric analysis; local structure; neutron diffraction; pair distribution function; total scattering; x-ray diffraction
• ISSN: 2688-9277; 2688-9277
• DOI: 10.1080/26889277.2022.2150897

Global research activities have been driven by the quest to develop and characterize novel materials for technological advancements. The total scattering pair distribution function (TSPDF) is a powerful and versatile characterization technique for examining the structural details of diverse complex materials including liquid, amorphous, disordered crystalline, and nanostructured materials. Thus, it is critical to keep track of research progress, identify research gaps, and future research directions of the application of the TSPDF technique in materials development and discovery. In this work, a bibliometric analysis of literature regarding the TSPDF technique between 2000 and 2021 was conducted using datasets retrieved from the Web of Science database. The research trends based on publication outputs, research subject distribution, co-authorships among institutions, countries/regions, co-citation of referenced sources, and keyword co-occurrence are evaluated and discussed herein. The impact of the TSPDF technique is projected to increase due to its importance in probing emerging functional materials, and the advances in specialized facilities and instrumentation among the scientific communities engaged with it. Finally, current and emerging research hotspots related to TSPDF technique such as catalysis, computer modeling and simulation, pharmaceutics, machine learning, hydrogen storage, battery materials, and layered structured materials are also identified and discussed.