Going beyond the Ordered Bulk: A Perspective on the Use of the Cambridge Structural Database for Predictive Materials Design

Ioanna Pallikara, Jonathan Skelton, Lauren E. Hatcher, Anuradha R Pallipurath

Research output: Contribution to journalArticlepeer-review

Abstract

When Olga Kennard founded the Cambridge Crystallographic Data Centre in 1965, the Cambridge Structural Database was a pioneering attempt to collect scientific data in a standard format. Since then, it has evolved into an indispensable resource in contemporary molecular materials science, with over 1.25 million structures and comprehensive software tools for searching, visualizing and analyzing the data. In this perspective, we discuss the use of the CSD and CCDC tools to address the multiscale challenge of predictive materials design. We provide an overview of the core capabilities of the CSD and CCDC software and demonstrate their application to a range of materials design problems with recent case studies drawn from topical research areas, focusing in particular on the use of data mining and machine learning techniques. We also identify several challenges that can be addressed with existing capabilities or through new capabilities with varying levels of development effort.
Original languageEnglish
Number of pages20
JournalCrystal Growth & Design
Early online date19 Aug 2024
DOIs
Publication statusE-pub ahead of print - 19 Aug 2024

Keywords

  • Cambridge Crystallographic Data Centre
  • Cambridge Structural Database,
  • predictive materials design
  • data-driven materials design
  • machine learning

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